SAMJ Vol 108, No 1 (2018)

JANUARY 2018

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CME Bleeding disorders (part 1) IN PRACTICE Nutrition for TB patients A cool ECG RESEARCH South African clinical practice guidelines: A landscape analysis Opportunities to optimise colistin stewardship Alcohol use and abuse in South Africa Prevalence of tobacco use in Johannesburg Drowning surveillance in South Africa

For first-line treatment in bleeding oesophageal varices 1

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At the ready to save lives References: 1. Ioannou GN, Doust J, Rockey DC. Terlipressin for acute esophageal variceal hemorrhage (Review). Cochrane Database of Systematic Reviews 2003, Issue 1. Art. No.: CD002147.

DOI:10.1002/14651858.CD002147. 2. Levacher S, Letoumelin P, Pateron D, et al. Early administration of terlipressin plus glyceryl trinitrate to control active upper gastrointestinal bleeding in cirrhotic patients. Lancet 1995; 346: 865-868. 3. Söderlund C, Magnusson I, Törngren S, Lundell L. Terlipressin (triglycyl-lysine vasopressin) controls acute bleeding oesophageal varices. Scand J Gastroenterol 1990; 25: 622-630. 4. Feu F, D’Amico G, Bosch J. The acute bleeding episode: advances in drug therapy. In: Arroyo V, Bosch J, Rodés J (eds). Treatments in Hepatology. Masson, Barcelona 1995: 9-22.

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JANUARY 2018 PRINT EDITION

FROM THE EDITOR 4

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EDITOR Bridget Farham, BSc (Hons), PhD, MB ChB

Alcohol harms – the next challenge B Farham

EDITORS EMERITUS Daniel J Ncayiyana, MD (Groningen), FACOG, MD (Hon), FCM (Hon) JP de V van Niekerk, MD, FRCR

EDITOR’S CHOICE

ASSOCIATE EDITORS Q Abdool Karim, A Dhai, R C Pattinson, A Rothberg, A A Stulting, J Surka, B Taylor, M Blockman, J M Pettifor, W Edridge, R P Abratt, D L Clarke

IZINDABA 8

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30 days in medicine B Farham

HMPG

OBITUARIES Johan Benjamin Janeke M van Dyk

CEO AND PUBLISHER Hannah Kikaya Email: hannahk@hmpg.co.za

Christopher John Bretherton Hundleby S Sellars

MANAGING EDITORS Claudia Naidu Naadia van der Bergh

CONTINUING MEDICAL EDUCATION 11

GUEST EDITORIAL Bleeding disorders (part 1) N Alli

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ARTICLE Inherited bleeding disorders N Alli, J Vaughan, S Louw, E Schapkaitz, J Mahlangu

TECHNICAL EDITORS Emma Buchanan Kirsten Morreira Paula van der Bijl PRODUCTION MANAGER Emma Jane Couzens DTP AND DESIGN Clinton Griffin Travis Arendse

IN PRACTICE 19

COCHRANE CORNER Nutritional supplements for people being treated for active tuberculosis: A technical summary L Grobler, S Durao, S M van der Merwe, J Wessels, C E Naude

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MEDICINE AND THE LAW ‘Covering doctors’ standing in for unavailable colleagues: What is the legal position?

D J McQuoid-Mason

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CLINICAL UPDATE A cool ECG S Lahri

CHIEF OPERATING OFFICER Diane Smith | Tel. 012 481 2069 Email: dianes@hmpg.co.za SALES MANAGER (CAPE TOWN) Azad Yusuf JOURNAL ADVERTISING Reneé Hinze Ladine van Heerden Makhadzi Mulaudzi Charmalin Comalie ONLINE SUPPORT Gertrude Fani

RESEARCH 25

South African clinical practice guidelines: A landscape analysis M Wilkinson, T Wilkinson, T Kredo, K MacQuilkan, C Mudara, A Winch, Y Pillay, K J Hofman

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Opportunities to optimise colistin stewardship in hospitalised patients in South Africa: Results of a multisite utilisation audit A P Messina, A J Brink, G A Richards, S van Vuuren

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Self-reported alcohol use and binge drinking in South Africa: Evidence from the National Income Dynamics Study, 2014 - 2015 N G Vellios, C P van Walbeek

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Prevalence of tobacco use in selected Johannesburg suburbs J A Teare, N Naicker, P Albers, A Mathee

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Predictors of treatment success in smoking cessation with varenicline combined with nicotine replacement therapy v. varenicline alone F Noor, C F N Koegelenberg, T M Esterhuizen, E M Irusen

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Good correlation between the Afinion AS 100 analyser and the ABX Pentra 400 analyser for the measurement of glycosylated haemoglobin and lipid levels in older adults in Durban, South Africa N S Abbai, M Nyirenda, T Reddy, G Ramjee

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January 2018, Print edition

FINANCE Tshepiso Mokoena HMPG BOARD OF DIRECTORS Prof. M Lukhele (Chair), Dr M R Abbas, Mrs H Kikaya, Dr M Mbokota, Dr G Wolvaardt ISSN 0256-9574 SAMA website: www.samedical.org Journal website: www.samj.org.za

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Anaemia, renal dysfunction and in-hospital outcomes in patients with heart failure in Botswana* J C Mwita, M G M D Magafu, B Omech, M J Dewhurst, Y Mashalla

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Keeping our heads above water: A systematic review of fatal drowning in South Africa* C J Saunders, D Sewduth, N Naidoo *Abstract only, full article available online.

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Members of the South African Medical Association receive the SAMJ only on request, as part of their membership benefit.

Subscriptions: Tel. 012 481 2071 Email: members@samedical.org The SAMJ is published monthly by the Health and Medical Publishing Group (Pty) Ltd, Co. registration 2004/0220 32/07, a subsidiary of SAMA. HEAD OFFICE Health and Medical Publishing Group (Pty) Ltd Block F, Castle Walk Corporate Park, Nossob Street, Erasmuskloof Ext. 3, Pretoria, 0181 Tel. 012 481 2069 Email: dianes@hmpg.co.za EDITORIAL OFFICE Suite 11, Lonsdale Building, Lonsdale Way, Pinelands, 7405 Tel. 021 532 1281 | Cell. 072 635 9825 Email: publishing@hmpg.co.za Please submit all letters and articles for publication online at http://www.editorialmanager.com/samj © Copyright: Health and Medical Publishing Group (Pty) Ltd, a subsidiary of the South African Medical Association Use of editorial material is subject to the Creative Commons Attribution – Non-commercial Works Licence. https://creativecommons.org/licenses/bync/4.0 Printed by TANDYM PRINT

JANUARY 2018

Background photo: A newborn baby at Caia District Hospital in central Mozambique | Shaun Swingler

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CME Bleeding disorders (part 1) IN PRACTICE Nutrition for TB patients A cool ECG RESEARCH South African clinical practice guidelines: A landscape analysis

Box photos: Factor IX, one of the serine proteases of the coagulation system | Shutterstock; Empty wine bottles | emily kate; Toddlers can drown in a bucket of water | emily kate

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January 2018, Print edition

Opportunities to optimise colistin stewardship Alcohol use and abuse in South Africa Prevalence of tobacco use in Johannesburg Drowning surveillance in South Africa

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FROM THE EDITOR

Alcohol harms – the next challenge This first issue of the SAMJ for 2018 once again raises the problems with alcohol use and misuse in South Africa (SA). An article[1] reports on information from the National Income Dynamics Study, which took place from 2014 to 2015. Interestingly, it appears that only about 30% of the population in the study drank alcohol – more men than women by quite a long way, 47.7% of men compared with 20.2% of women. However, binge drinking was reported by 48.2% of men who were drinkers, and 32.4% of women. In this study, binge drinking was defined as reported consumption of more than five standard drinks on an average drinking day. This means that in SA, one in three people drink alcohol, and one in seven report binge drinking.

The levels of so-called ‘safe’ alcohol consumption are highly contentious, evidenced by the frequent changes to recommended numbers of standard drinks in countries such as the UK, which is also trying to introduce minimum alcohol pricing levels. In resourcerich countries, the main harms of alcohol are seen in rising levels of alcohol-related diseases. I am not going to comment on the clinical side of alcohol harms. However, any one of us who has been in clinical practice, particularly in our provincial hospitals, will have seen the social harms of alcohol misuse in our country. I would be willing to bet that those of you who regularly work in emergency units find that a large percentage of your cases are trauma and injury due to alcohol misuse. I am writing this as we approach the holiday season, when traffic becomes even worse than usual as large numbers of people return to the rural areas or drive to holiday destinations.

And every year the dashboard of holiday driving-related deaths and injuries is completely unacceptable – much of it related to alcohol.

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As I write we are entering the 16 Days of Activism for No Violence Against Women and Children – which should, of course, not be just for 16 days of the year. Again, alcohol misuse plays a large role in this violence.

As a country, we have done extremely well in stopping advertising for tobacco products, banning smoking in public places and generally reducing the numbers of people smoking. Perhaps it is time to start taking a similar stand against alcohol – another dangerous drug when misused. Anyone who knows me well enough will know that I enjoy a glass or two, so I am no teetotaller with an anti-alcohol agenda.

But we need consistency. If we are going to ban advertising and sponsorship by tobacco companies, alcohol should be subject to the same scrutiny. The adverts for alcohol on television, in cinemas and on billboards, like those we used to see for tobacco, equate drinking alcohol with financial and social success – ironical in the face of the effect the substance has on many of those who drink it.

Bridget Farham Editor ugqirha@iafrica.com 1. Vellios NG, van Walbeek CP. Self-reported alcohol use and binge drinking in South Africa: Evidence from the National Income Dynamics Study, 2014 - 2015. S Afr Med J 2018;108(1):33-39. https://doi. org/10.7196/SAMJ.2018.v108i1.12615

S Afr Med J 2018;108(1):3. DOI:10.7196/SAMJ.2018.v108i1.13045

January 2018, Print edition

PATS & SATS

CONGRESS 2018 12 - 15 April Durban ICC - South Africa

WWW.PATS2018.COM CALL FOR ASBTRACT

The Scientific committee invites the submission of abstracts to be considered for oral and poster presentations.

The deadline for the submission of abstracts is 12 January 2018.

Registrars and post graduate students are specifically invited to present.

Please submit your abstract online.Faxed abstracts will not be accepted.

All appropriate abstracts will be reviewed by the Scientific Committee. All abstracts received will be acknowledged, and authors will be sent acceptance or rejection letters by the 15th February 2018.

Please note that authors of accepted abstracts must be registered delegates. All costs, including registration, are for the authors' own expense.

Young Investigator awards are available for best abstracts by young investigators working in African institutions or linked to an African University. A young investigator is defined as any individual who obtained their last qualification (such as an Undergraduate degree in general medicine; Masters degree as a Physician or Paediatrician; or Certificate in Paediatric Pulmonology or Adult Pulmonology) within the last 5 years. The awards will cover congress registration, travel and accommodation. In order to be considered for these awards, kindly check the 'Young Investigator Award' box on the abstract submission page.

INSTRUCTIONS TO AUTHORS: 1. Each abstract must clearly state the following: -Abstract title (the title of the abstract must not exceed 25 words) -Name of list of author(s). The name of the presenting author must appear first in the list of authors.

-Affiliation of author(s).

-Contact details of first author (telephone numbers, e-mail address etc) 2. Abstracts must be typed in English, single line spacing, Arial font size 12.

3. The body of the text must not exceed 350 words (this excludes the information listed in point 1) 4. Please adhere to the following format: -Introduction: should be brief and informative and state the aim of the study -Methods: include description of subjects and research methodology -Results: outline the findings of the study supported by statistics as appropriate. Do not use figures, graphs or tables in the abstract. The data provided must be sufficient to permit peer review of the abstract -Conclusion: provide summary and relevance of the main findings

Supported by:

EDITOR’S CHOICE

CME: Bleeding disorders (part 1)

Haemostasis is a physiological process that stops blood loss at the site of injury, while maintaining normal blood flow in the rest of the circulation. This is accomplished in three physiological steps that occur in rapid sequence: (i) vasoconstriction; (ii) formation of a platelet plug (primary haemostasis); and (iii) stabilisation of clot through cross-linking of insoluble fibrin (secondary haemostasis).

The fibrin mesh that is incorporated into and around the platelet plug serves to strengthen and stabilise the blood clot. Apart from limiting blood loss, the clot allows for vessel and tissue repair.

Anticoagulant mechanisms regulate the coagulation system to ensure formation of a clot that is proportional to the injury. A delicate balance between procoagulant and anticoagulant systems is critical for proper haemostasis and for avoiding pathological bleeding or thrombosis. The clot is finally dissolved by the fibrinolytic system, the function of which is also to prevent blood clots in healthy blood vessels.

To appreciate the rationale for using the various clotting tests towards achieving a diagnosis, an understanding of the coagulation cascade is necessary. A simplified schematic representation – Fig. 1 in the article in this issue[1] – is intended to orientate the reader with regard to the pathophysiology of the respective bleeding disorders.

For the purpose of discussion in this two-part CME series, bleeding disorders are divided into two broad categories: (i) inherited (part 1, current issue);[1] and (ii) acquired (part 2, forthcoming issue).

Keeping our heads above water: A systematic review of fatal drowning in South Africa

Drowning is defined as the process of experiencing respiratory impairment from submersion/immersion in liquid, and can have one of three outcomes – no morbidity, morbidity or mortality.

The World Health Organization African region accounts for approximately 20% of global drowning, with a drowning mortality rate of 13.1 per 100 000 population. The strategic implementation of intervention programmes driven by evidence-based decisions is of prime importance in resource-limited settings such as South Africa (SA).

In this systematic review of published literature, Saunders et al.[2] look at the available epidemiological data on fatal drowning in SA in order to identify gaps in the current knowledge base and priority intervention areas. In addition, an internet search for grey literature, including technical reports, describing SA fatal drowning epidemiology was conducted.

A total of 13 published research articles and 27 reports obtained through a grey literature search met the inclusion and exclusion criteria. These 40 included articles and reports, covered data collection periods between 1995 and 2016, and were largely focused on urban settings. The fatal drowning burden in SA is stable at approximately 3.0 per 100 000 population, but is increasing as a proportion of all non-natural deaths. Drowning mortality rates are high in children aged <15 years, particularly in those aged <5.

The review suggests that SA drowning prevention initiatives are currently confined to the early stages of an effective injury prevention strategy. The distribution of mortality across age groups and drowning location differs substantially between urban centres and provinces. There is therefore a need for detailed drowning surveillance to monitor national trends and identify risk factors in all SA communities.

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Anaemia, renal dysfunction and in-hospital outcomes in patients with heart failure in Botswana

Anaemia and renal dysfunction are associated with an increased morbidity and mortality in heart failure (HF) patients. Mwita et al.[3] estimated the frequency and impact of anaemia and renal dysfunction on in-hospital outcomes in patients with HF. A total of 193 consecutive patients with HF admitted to Princess Marina Hospital, Gaborone, Botswana, from February 2014 to February 2015 were studied. Anaemia was defined as haemoglobin <13 g/dL for men and <12 g/dL for women. Renal dysfunction was defined by an estimated glomerular filtration rate (eGFR) <60 mL/ min/1.73 m2, calculated by the simplified Modification of Diet in Renal Disease formula. The in-hospital outcomes included length of hospital stay and mortality.

The mean (standard deviation (SD)) age was 54.2 (17.1) years and 53.9% of the patients were men. The overall median eGFR was 75.9 mL/min/1.73 m2 and renal dysfunction was detected in 60 patients (31.1%). Renal dysfunction was associated with hypertension (p=0.01), diabetes mellitus (p=0.01) and a lower haemoglobin level (p=0.008). The mean (SD) haemoglobin was 12.0 (3.0) g/dL and 54.9% of the patients were anaemic. Microcytic, normocytic and macrocytic anaemia were found in 32.1%, 57.5% and 10.4% of patients, respectively. The mean (SD) haemoglobin level for males was significantly higher than for females (12.4 (3.3) g/dL v. 11.5 (2.5) g/dL; p=0.038). Anaemia was more common in patients with diabetes (p=0.028) and in those with increasing left ventricular ejection fraction (p=0.005). Neither renal dysfunction nor anaemia was significantly associated with length of hospital stay or in-hospital mortality.

Anaemia and renal dysfunction are prevalent in HF patients, but neither was an independent predictor of length of stay or in-hospital mortality in this population. These findings indicate that HF data in developed countries may not apply to sub-Saharan African countries and call for more studies to be done in this region.

Self-reported alcohol use and binge drinking in SA: Evidence from the National Income Dynamics Study, 2014 - 2015

Although the SA government has implemented alcohol control measures, alcohol consumption remains high.

The objectives of this study by Vellios and Van Walbeek[4] were to quantify the prevalence of self-reported current drinking and binge drinking in SA, and to determine important covariates.

The authors used the 2014 - 2015 National Income Dynamics Study, a nationally representative dataset of just over 20 000 individuals aged ≥15 years. Multiple regression logit analyses were performed separately by gender for self-reported current drinkers (any amount), self-reported bingers as a proportion of drinkers, and self-reported bingers as a proportion of the total population.

An individual was defined as a binge drinker if he/she reported consumption of ≥5 standard drinks on an average drinking day.

Current alcohol use (any amount) in 2014 - 2015 was reported by 33.1% of the population (47.7% males, 20.2% females). Of drinkers, 43.0% reported binge drinking (48.2% males, 32.4% females). The prevalence of self-reported binge drinking as a percentage of the total population was 14.1% (22.8% males, 6.4% females). Although black African males and females were less likely than white males and females to report drinking any amount, they were more likely to report binge drinking. Coloured (mixed race) females were more likely than black African females to report drinking any amount.

January 2018, Print edition

Males and females who professed a religious affiliation were less likely than those who did not to report drinking any alcohol. The prevalence of self-reported binge drinking was highest among males and females aged 25 - 34 years.

Smoking cigarettes substantially increased the likelihood of drinking any amount and of binge drinking for both genders.

In SA, one in three individuals reported drinking alcohol, while one in seven reported binge drinking on an average day on which alcohol was consumed. Strong, evidencebased policies are needed to reduce the detrimental effects of alcohol use.

Predictors of treatment success in smoking cessation with varenicline combined with nicotine replacement therapy v. varenicline alone

Identification of the predictors of treatment success in smoking cessation may help healthcare workers to improve the effectiveness of attempts at quitting.

Noor et al.[5] aimed to identify the predictors of success in a randomised controlled trial comparing varenicline alone or in combination with nicotine replacement therapy (NRT).

A post hoc analysis of the data on 435 subjects who participated in a 24-week, multicentre trial in SA was performed. Logistic regression was used to analyse the effect of age, sex, age at smoking initiation, daily cigarette consumption, nicotine dependence, and reinforcement assessment on abstinence rates at 12 and 24 weeks. Point prevalence and continuous abstinence rates were selfreported and confirmed biochemically with exhaled carbon monoxide readings.

The significant predictors of continuous abstinence at 12 and 24 weeks on multivariate analysis were lower daily cigarette consumption (odds ratio (OR) 1.86, 95% confidence interval (CI) 1.21 - 2.87; p=0.005 and OR 1.83, 95% CI 1.12 - 2.98; p=0.02, respectively) and older age (OR 1.52, 95% CI 1.00Â 2.31; p=0.049 and OR 1.79, 95% CI 1.13 - 2.84; p=0.01, respectively). There was no difference in the predictors of success in the univariate analysis, except that older age predicted point prevalence abstinence at 12 weeks (OR 1.47, 95% CI 1.00 - 2.15; p=0.049). The findings were inconclusive for an association between abstinence and lower nicotine dependence, older age at smoking initiation and positive reinforcement.

Older age and lower daily cigarette consumption are associated with a higher likelihood of abstinence in patients using varenicline, regardless of the addition of NRT. BF 1. Alli N, Vaughan J, Louw S, Schapkaitz E, Mahlangu J. Inherited bleeding disorders. S Afr Med J 2018;108(1):9-15. https://doi.org/10.7196/SAMJ.2018.v108i1.13020 2. Saunders CJ, Sewduth D, Naidoo N. Keeping our heads above water: A systematic review of fatal drowning in South Africa. S Afr Med J 2018;108(1):56-63. https://doi. org/10.7196/SAMJ.2018.v108i1.11090 3. Mwita JC, Magafu MGMD, Omech B, Dewhurst MJ, Mashalla Y. Anaemia, renal dysfunction and in-hospital outcomes in patients with heart failure in Botswana. S Afr Med J 2018;108(1):64-68. https://doi.org/10.7196/SAMJ.2018.v108i1.12686 4. Vellios NG, van Walbeek CP. Self-reported alcohol use and binge drinking in South Africa: Evidence from the National Income Dynamics Study, 2014 â&#x20AC;&#x201C; 2015. S Afr Med J 2018;108(1):33-39. https://doi.org/10.7196/SAMJ.2018.v108i1.12615 5. Noor F, Koegelenberg CFN, Esterhuizen TM, Irusen EM. Predictors of treatment success in smoking cessation with varenicline combined with nicotine replacement therapy v. varenicline alone. S Afr Med J 2018;108(1):45-49. https://doi.org/10.7196/SAMJ.2018. v108i1.12671

These open-access articles are distributed under Creative Commons licence CC-BY-NC 4.0.

IZINDABA

30 days in medicine Antenatal exposure to indoor air pollution and tobacco smoke associated with wheezing in infants

A study of infants in Paarl, South Africa, suggests that antenatal exposure to indoor air pollution and tobacco smoke are the predominant risk factors for lower respiratory tract infection (LRTI) and wheezing illnesses in infants. Mother-infant pairs were enrolled over 3 years in a birth cohort study in two centres and followed up during the first year of life. Exposure to internal air pollution (particulate matter, nitrogen dioxide, sulphur dioxide, carbon monoxide and the volatile organic compounds benzene and toluene) was measured antenatally and postnatally. Exposure to tobacco smoke was assessed by reports from mothers and urine continine tests.

Between March 2012 and March 2015, 1 137 mothers with 1 143 live births were enrolled. Exposures associated with LRTI were maternal smoking or particulate matter. Toluene was a novel exposure associated with severe LRTI. Antenatally, wheezing was associated with maternal passive smoke exposure and postnatally, with any household member smoking.

Vanker A, Barnett W, Workman L, et al. Early-life exposure to indoor air pollution or tobacco smoke and lower respiratory tract illness and wheezing in African infants: A longitudinal birth cohort study. Lancet Planet Health 2017;1(8):e328-e336. https://doi.org/10.1016/S2542-5196(17)30134-1

Upper hypertension limit for healthy over-60s raised

New guidelines published by the American College of Physicians and the American Academy of Family Physicians recommend that the threshold for treating hypertension in otherwise healthy adults aged >60 years be raised. The current threshold for treatment is a systolic blood pressure reading of 140 mmHg. The new recommendation is that only those aged >60 years with a persistent reading of ≥150 mmHg should start treatment for hypertension.

The new guidelines are the result of a systematic review of randomised controlled trials and observational studies. Deaths from all causes, together with illnesses, harms and deaths linked to stroke and major cardiac events, were analysed to evaluate the evidence. The evidence did not allow recommendations about diastolic blood pressure targets.

Qaseem A, Wilt TJ, Rich R, Humphrey LJ, Frost J, et al. Pharmacologic treatment of hypertension in adults aged 60 years or older to higher versus lower blood pressure targets: A clinical practice guideline from the American College of Physicians and the American Academy of Family Physicians. Ann Intern Med 2017;166(6):430-437. https://doi.org/10.7326/M16-1785

Heavy smoking and drinking ages us

Recent Danish research shows that heavy smoking and drinking lead to physical signs of ageing that cause you to look older than you

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are. The findings are based on information from more than 11 500 adults aged >20 years (average age 51), whose heart and visible ageing signs were tracked for an average of 11.5 years as part of the Copenhagen Heart Study, which began in 1976. Participants were asked about their lifestyle and general health, including how much they drank or smoked, and were checked for signs of ageing that had previously been linked to an increased risk of cardiovascular disease or death – earlobe creases, arcus cornea, xanthelasmata and malepattern baldness.

Average alcohol consumption was 2.6 drinks per week for women and 11.4 for men, and just over half the women (57%) and two-thirds of the men (67%) were current smokers. Arcus cornea was the most common sign of ageing in both sexes, and more common among men aged >70 and women aged >80. Xanthelasmata was the least common sign. Analysis of drinking and smoking patterns showed a consistently increased risk of looking older than true age among people who smoked and drank heavily.

Schou AL, Mølbak ML, Schnor P, Grønbæk M, Tolstrup JS. Alcohol consumption, smoking and development of visible age-related signs: A prospective cohort study. J Epidemiol Comm Health 2017;71(12):1177-1184. https://doi.org/10.1136/jech-2016-208568

Coffee is good for you

Drinking three to four cups of coffee daily is associated with health benefits across a range of diseases and conditions, according to a review published in the British Medical Journal. The study identified 201 meta-analyses of observational research and 17 of interventional research finding that coffee consumption was more beneficial than harmful.

Consumption of three cups a day was associated with a 19% lower risk of mortality from cardiovascular disease, a 16% lower risk of mortality from coronary heart disease and a 30% lower risk of stroke mortality. There was no harm associated with increasing to four cups a day, but the beneficial effects were less pronounced. A metaanalysis of 40 cohort studies suggested that there is a lower incidence of cancer among people who consumed large amounts of coffee than among those who drank little. Coffee drinkers also have a 29% lower risk of non-alcoholic fatty liver disease, a 27% lower risk of liver fibrosis and a 39% lower risk of liver cirrhosis.

The outcomes are mixed for coffee in pregnancy, however, with high consumption associated with a higher risk of low birth weight.

Poole R, Kennedy OJ, Roderick P, Fallowfield JA, Hayes PC, Parkes J. Coffee consumption and health: Umbrella review of meta-analyses of multiple health outcomes. BMJ 2017;359:j5024. https://doi. org/10.1136/bmj.j5024

B Farham Editor ugqirha@iafrica.com

January 2018, Print edition

IZINDABA

OBITUARIES Johan Benjamin Janeke

Dr Johan Janeke, an esteemed ear, nose and throat surgeon, died in September 2017.

He was 78.

Dr Janeke succumbed to multilobar pneumonia after a valiant forty-day struggle.

He was the first South African ENT surgeon to perform a cochlear implant.

After attaining his MB ChB at the University of Pretoria in 1963, he completed a PhD in otolaryngology at the University of

Amsterdam six years later. He then trained at Baylor College of Medicine in Houston, Texas, where received the prestigious Ben Schuster award for outstanding research in nasal reconstruction. At one time he treated Elvis Presley there. In 1975 he commenced private practice in Johannesburg.

Dr Janeke’s life was bejewelled with encounters with famous people. He met Bob Hope and was for three years an anatomy demonstrator under Prof. Phillip Tobias at Wits Medical School. But most precious to him was a meeting with Nelson Mandela.

Dr Janeke was passionate in his profession, connecting with patients and their families in a special way. Although learned and gifted with wisdom, he was a humble man who made it his mission to treat people at every level with the same care, dignity and respect as the rich and famous. In recognition of this he was presented with the prestigious Christiaan Barnard Memorial Award and medal for his contribution to medicine and the people of South Africa.

Alongside his career in private practice, Dr Janeke was a passionate scholar, an academic and an author. He wrote and published

several books in the field of otolaryngology, including ENT Out of Africa, which was later translated into French and used for medical training in North Africa. The English version was used at Wits Medical School. Dr Janeke wrote articles for several medical journals. He served on the editorial board of Modern Medicine.

He was innovative and sought new, costeffective ways to help the hearing impaired.

He developed the ABC Implant as an affordable alternative to the costly cochlear implant.

When he was no longer able to practise, Dr Janeke turned his hand to painting.

He soon developed an easy style that he used to capture his fascination with nature, particularly trees.

Dr Janeke was unapologetically Christian, and those values showed through in his personal life as well as in his practice. He leaves his wife Margaret, six children and six grandchildren.

Mike van Dyk Johannesburg, South Africa mike@modernmedia.co.za

Christopher John Bretherton Hundleby

Dr Christopher John Bretherton Hundleby, a general practitioner in Cape Town, died on 6 October 2017 at age of 86 years. He was a very special person, a truly humble and gentle man with an abundance of

courtesy, kindness, consideration, compassion and goodwill. These attributes, coupled with his intelligence, intuition, thoughtfulness, sincerity, commitment and sense of responsibility, made him an exceptional husband, father, friend and medical practitioner.

He was born in the Eastern Cape on 29 March 1931, the first child of Charles and Constance Hundleby, teachers at St Matthew’s Mission. His mother was also the mission organist and his father an Anglican lay minister, as well as being head of St Matthew’s Teachers’ Training College.

Later his father became Dean of the Faculty of English at the University of Fort Hare, and later still was honoured by Rhodes University with an honorary doctorate and by the Anglican Church with the Order of Simon of Cyrene. It was within this culture and its altruistic doctrine that Chris Hundleby was brought up and developed his profound respect for Africa and its people.

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At the age of eight he went as a boarder to St Andrew’s College in Grahamstown, where he excelled academically, such that when the time came his teachers recommended that he further his education at Cambridge University. His housemaster’s recommendation for entry to Magdalene College at that university reads: ‘... He is a first rate young man and one with a particularly good academic record. He wishes to study medicine; no sudden whim this. From the day he arrived, Hundleby’s job in life has been clear before him. He sees in medicine not a means to an assured income but a study that interests him intensely and a profession of vital importance in the development of his country …’ This letter is signed ‘Charles Fortune, Housemaster’.

Chris entered Cambridge University in 1949 to read Natural Sciences, receiving his BA degree in 1952. From there he went to St Mary’s Hospital in London to pursue his clinical training, obtaining his

IZINDABA

Cambridge medical and surgical degrees in 1956. Subsequently he worked in the British National Health Service until he returned to South Africa in 1962 to convalesce from a serious illness that had hospitalised him for three months. He joined a large Queenstown general practice, in which he was able to pursue his interest in anaesthesia, and then two years later went back to England, this time to Cambridge, primarily to support his younger brother James in his studies. While working there at Addenbrooke’s Hospital Chris met his future wife, Rosemary Faith Milne, a nursing sister at that hospital. In 1966 they married in her home town of Aylsham in Norfolk, and it was typical of him that the marriage was conditional on he and his bride returning to Africa, which he did as a specialist anaesthetist. However, instead of continuing in anaesthetics in Cape Town, he took his wife and their two young daughters to the Ciskei to take up an appointment as district surgeon in the Stockenstroom area. There over nine years he built up a flourishing and vibrant clinical practice with an expanding infrastructure, dedicated nursing staff and loyal support services. He dealt with his responsibilities, which were heavy and varied, with characteristic thoroughness. For example, during a meningitis outbreak he and his team vaccinated 600 ‘at-risk’ patients during one day.

Faith and Chris were very happy in the Ciskei. A loving and open home was created in Seymour, a third daughter arrived, the practice was thriving, and Chris was in his element. These were their happiest and most fulfilling, indeed golden years. However, the

children’s education took priority and their return to Cape Town became inevitable.

Their leaving was a time of regret and sadness for many. A local paper of that time stated that ‘… During the past nine years there have been tremendous improvements in the medical services in the whole area, all initiated and financed by the doctor. The consulting rooms and outpatient facilities have been enlarged and replanned, and as a result of requests from the people of the outlying districts, through the magistrate for medical services, Dr Hundleby purchased and started a mobile clinic with trained and qualified nursing sisters. At one period there were five but the number has been reduced to two at the present time, all salaries being paid for by Dr Hundleby. Mrs Hundleby has also been active in the life of the community … Their going will leave a gap hard to fill.’

It is no wonder that the community wept when the Hundleby family departed.

To return to hospital practice was not for Chris; he needed the intimacy of personal patient contact, so he set about establishing a consulting general practice near Mowbray Station. The local residents objected strongly, but the City Council smartly overruled all objections. So from humble beginnings, some days with only one patient, his reputation across the Cape Flats and far beyond grew such that eighty patients a day would attend. Why? Because he ran a model practice, efficient, comprehensive and productive; because of his own unique humanity and spiritual qualities of caring, compassion and competence; and because of his ability to converse with his patients in their own language. He would treat with

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successful outcomes, and when he foresaw that he could not, he would refer to the hospital up the hill. He sold his practice a few years ago, but went on working there, remarkably until the day before he recently left Cape Town for Johannesburg. And that at the age of 86.

Chris Hundleby was a family man, a devoted and most loving husband, who with Faith had a model marriage – how loyal she was, and how supportive of him in all his efforts of goodwill to others and caring of so many. She made him a wonderful home, and she raised and nurtured a wonderful family. His devotion to her was exemplified by his concern for and care of her during her protracted and debilitating final illness.

He was for Faith a tower of strength, of attention and of care. When she died in August 2016 he was devastated, and clearly his grief never resolved. But despite his own emotional distress he put his affairs in order, sold his house, and made his move to Johannesburg. He was too a model father, who adored his three daughters and in time their children, and they in their turn adored him. They were his treasures, and to their credit they have lived by his example, his standards and his values.

Christopher Hundleby was the quintessential medical practitioner, for whom agape and altruism were his primary way of life; and yet more so, as a son of Africa, he gave tangible meaning to the fundamental principles of ubuntu.

Sean Sellars Cape Town, South Africa sean_sellars@yahoo.com

This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

CME

GUEST EDITORIAL

Bleeding disorders (part 1) Haemostasis is a physiological process that stops blood loss at the site of injury, while maintaining normal blood flow in the rest of the circulation. This is accomplished in three physiological steps that occur in rapid sequence: (i) vasoconstriction; (ii) formation of a platelet plug (primary haemostasis); and (iii) stabilisation of clot through cross-linking of insoluble fibrin (secondary haemostasis). The fibrin mesh that is incorporated into and around the platelet plug serves to strengthen and stabilise the blood clot. Apart from limiting blood loss, the clot allows for vessel and tissue repair. Anticoagulant mechanisms regulate the coagulation system to ensure formation of a clot that is proportional to the injury. A delicate balance between procoagulant and anticoagulant systems is critical for proper haemostasis and for avoiding pathological bleeding or thrombosis. The clot is finally dissolved by the fibrinolytic system, which also performs the function of preventing blood clots in healthy blood vessels.

For the purpose of discussion in this two-part CME series, bleeding disorders are divided into two broad categories: (i) inherited (part 1, current issue);[1] and (ii) acquired (part 2, forthcoming issue).

Inherited bleeding disorders (IBDs) should be suspected when there is a family history of a bleeding disorder or abnormal bleeding during early childhood, such as the neonatal period or infancy. However, IBD patients may also present for the first time during adulthood.

Investigation of abnormal bleeding requires a comprehensive history, thorough physical examination and systematic laboratory work-up. For the laboratory work-up, an algorithmic approach is included in the article in this edition of CME (Fig. 2).[1] To appreciate the rationale for using the various clotting tests towards achieving a diagnosis, an understanding of the coagulation cascade is necessary. A simplified schematic representation â&#x20AC;&#x201C; Fig. 1 in the article in this issue[1] â&#x20AC;&#x201C; is intended to orientate the reader with regard to the pathophysiology of the respective bleeding disorders.

The article discusses a wide range of IBDs and provides a diagnostic approach and available therapeutic options for the general practitioner.

Patients diagnosed with a bleeding diathesis should ideally be referred to a tertiary healthcare facility such as a haemophilia centre for management and follow-up. von Willebrand disease and haemophilia, being the most common IBDs, are discussed in greater detail. However, a comprehensive review

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of the various bleeding disorders with elaborate detail, such as pathophysiological mechanisms and genetic defects, is beyond the scope of this CME. There has been significant progress with regard to the treatment of haemophilia, where the current standard of care is to prevent bleeding by prophylactic infusions of the deficient clotting factor as opposed to on-demand infusions following a bleed. This preventive strategy that is sure to reduce the hospitalisation and complication rates, comes at a cost, which is a limiting factor. Newer technologies with development of modified factor VIII products with an extended half-life and less immunogenic potential are emerging. With less frequent factor infusions, the prospect of prophylactic therapy is likely to become more affordable in economically challenged environments such as South Africa. This is an exciting yet realistic prospect that would allow haemophiliacs to lead almost normal lives. For any disease a cure is the ultimate aim, and in this context gene therapy has recently emerged as a potential therapeutic option for haemophilia B. The authors are indeed grateful for the opportunity to discuss the subject of bleeding disorders, which is an important and dynamic sphere of coagulation.

N Alli Department of Molecular Medicine and Haematology, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, and National Health Laboratory Service, Johannesburg, South Africa nazeer.alli@nhls.ac.za

1. Alli N, Vaughan J, Louw S, Schapkaitz E, Mahlangu J. Inherited bleeding disorders. S Afr Med J 2018;108(1):9-15. DOI:10.7196/SAMJ.2018.v108i1.13020.

S Afr Med J 2018;108(1):8. DOI:10.7196/SAMJ.2018.v108i1.13019

January 2018, Print edition

This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

CME

Inherited bleeding disorders N Alli, MB BCh, FCPathHaem (SA); J Vaughan, MB BCh, FCPathHaem (SA), MMed Haem; S Louw, MB BCh, FCPathHaem (SA), MMed Haem; E Schapkaitz, MB BCh, FCPathHaem (SA), MMed Haem; J Mahlangu, BSc, MB BCh, FCPathHaem (SA), MMed Haem, Cert Clin Haem Department of Molecular Medicine and Haematology, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, and National Health Laboratory Service, Johannesburg, South Africa Corresponding author: N Alli (nazeer.alli@nhls.ac.za)

Abnormal bleeding is a common clinical presentation in general practice, and a rational approach to this problem is therefore required.

Investigation of a suspected bleeding disorder necessitates a comprehensive history, thorough physical examination and systematic laboratory work-up. Inherited bleeding disorders (IBDs) typically manifest in childhood, but may present later in life after a haemostatic challenge (such as trauma, surgery, tooth extraction). This two-part CME series is intended to provide insight to the medical practitioner on the clinical spectrum, diagnosis and management of bleeding disorders. Bleeding due to inherited disorders is the subject of discussion in part 1 (current issue), and in part 2 (forthcoming issue) the focus is on bleeding from acquired causes. Patients diagnosed with an IBD should ideally be referred to a dedicated tertiary healthcare facility, e.g. haemophilia centre, for management and follow-up.

S Afr Med J 2018;108(1):9-15. DOI:10.7196/SAMJ.2018.v108i1.13020

Haemostasis is a biological process that stops blood loss at the site of injury. This is accomplished in three physiological steps that occur in rapid sequence: (i) vasoconstriction; (ii) formation of a platelet plug (primary haemostasis); and (iii) stabilisation of clot through crosslinking of insoluble fibrin (secondary haemostasis). The clot is finally dissolved by the fibrinolytic system (Fig. 1).

The presence of an inherited bleeding disorder (IBD) should be suspected on presentation in early childhood or when there is a Intrinsic pathway

Common pathway

Extrinsic pathway

FX

FVII TF

FIX FIXa

FVIIIa

TF-FVIIa

FXa FVa

FXIa +

II FXIII

Thrombin

(FXII)

FXIIIa

I

FXI

Fibrin

XL fibrin

FDPs _ Plasminogen

Plasmin

Fibrinolytic system

Îą2-AP

_ tPA

PAI

Fig 1. A simplified schematic representation of the coagulation cascade and fibrinolytic system. Factor XII is not an active participant towards haemostasis in vivo, but is activated in vitro by PTT reagent; hence its inclusion in the cascade as factor XII (in parenthesis), which activates factor XI. (F = factor; I = fibrinogen; II = prothrombin; PTT = partial thromboplastin time; FDPs = fibrin/fibrinogen degradation products; PAI = plasminogen activator inhibitor; Îą2-AP = alpha 2-antiplasmin inhibitor; tPA = tissue plasminogen activator.)

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longstanding history of easy bruising, in cases of recurrent and/or severe bleeding (particularly at unusual sites) and in patients with a family history of the condition.

IBDs include a spectrum of disorders that affect clotting factors, platelets or the vessel wall, and the clinical manifestation varies depending on the underlying cause. For instance, patients with platelet and vessel wall disorders usually present with mucocutaneous bleeding (petechiae, purpura, ecchymosis, epistaxis, menorrhagia, haematuria and/or gastrointestinal tract blood loss), while clotting factor deficiencies may also cause joint and deep muscle bleeding.

The most common IBD is von Willebrand disease (vWD), which affects both platelet adhesion to the vessel wall and factor VIII levels, and may therefore present with a mixed bleeding profile. The clinical history of patients should focus on the site and severity of previous episodes of bleeding, including requirements for blood transfusion, nature of the provoking injury, consequences of exposure to previous haemostatic challenges (such as surgery, tooth extraction, childbirth) and presence of a family history. A basic initial workup includes a full blood count (FBC) with peripheral blood smear review, prothrombin time (PT)/international normalised ratio (INR) and partial thromboplastin time (PTT). If these are normal, further investigations are warranted.

The algorithm in Fig. 2 provides a diagnostic approach for a patient presenting with a bleeding disorder. Laboratory test results of the various inherited bleeding conditions are summarised in Table 1. Each coagulation factor has a plasma half-life that determines its stability after blood sample collection. This should be kept in mind when performing laboratory tests of specific factor levels (Table 1).

To appreciate the rationale for using the various clotting tests towards achieving a diagnosis, an understanding of the coagulation cascade is necessary. Fig. 1 is a simplified schematic representation of the coagulation cascade. This is by no means complete and is intended to orientate the reader on the pathophysiology of the respective bleeding disorders. The coagulation cascade is categorised into intrinsic, extrinsic and common pathways, which are in vitro observations that assist with identifying the factor deficiency. The reagent employed to calculate the PTT activates factor XII and so measures factors in the

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CME

intrinsic and common pathways. The reagent employed for the INR estimation activates factor VII and so measures the extrinsic and common pathways.

Suspected inherited bleeding disorder Baseline screening: PT/INR, PTT, FBC and smear

FVIII and FIX levels

PT/INR N PTT N

↓platelets, abnormal morphology

FV, FX, FII levels†

vWD testing

Exclude acquired thrombocytopenia Refer for specialist work-up if inherited platelet disorder suspected

↓ FVIII or IX

Normal FXI and FXII levels*

FVII levels†

Background and epidemiology

PT/INR ↑ PTT ↑

PTT N PT/INR ↑

PTT ↑‡ INR N

Haemophilia

Normal

↓VIII: Haemophilia A Exclude vWD ↓FIX: Haemophilia B

Fibrinogen level Repeat vWD testing x 2 Urea clot lysis time Platelet aggregometry

Abnormal vWD

↓ FXI: Haemophilia C ↓ FXII: Not associated with bleeding, seek another cause

Fig. 2. Algorithmic approach to a suspected inherited bleeding disorder. (vWD = von Willebrand disease; PTT = partial thromboplastin time; PT = prothrombin time; INR = international normalised ratio; FBC = full blood count; F = factor; N = normal.) *Also consider testing for a lupus anticoagulant. † Also consider acquired causes (e.g. liver disease, vitamin K deficiency, warfarin/super-warfarin effect, DIC = disseminated intravascular coagulation). ‡Mixing studies with normal plasma differentiate true factor deficiency (if PTT corrects) from the presence of an inhibitor (if PTT fails to correct), such as heparin, lupus anticoagulant or antifactor inhibitor.

Haemophilia is an IBD due to deficiency or dysfunction of clotting factor VIII or factor IX. Clotting factor VIII is deficient in haemophilia A and factor IX is deficient in haemophilia B. Haemophilia C refers to deficiency of clotting factor XI. The incidence is 1 in 10 000 live births in haemophilia A and 1 in 25 000 live births in haemophilia B.[1] Among the inherited bleeding disorders, vWD is the most common, followed by haemophilia A and B. It is estimated that there are at least 400 000 haemophilia sufferers globally.[2] Both haemophilia A and B are inherited in an X-linked fashion, with male carriers of the mutant gene afflicted with the bleeding diathesis and females being obligate carriers.

Although haemophilia has a strong family history in the majority of cases, up to 30% of haemophilia cases are caused by spontaneous mutations, with no prior family history.

Table 1. Expected results of laboratory tests for various inherited bleeding conditions

Inherited bleeding condition ↓ Fibrinogen

INR/PT ↑

PTT ↑

TT ↑

Dysfibrinogenaemia (bleeding disorder) ↓ Prothrombin ↓ Factor V ↓ Factor VII ↓ Factor VIII ↓ Factor IX ↓ Factor X ↓ Factor XI ↓ Factor XIII

↑

↑

↑

↑ ↑ ↑ N N ↑ N N

↑ ↑ N ↑† ↑† ↑ ↑ N

N N N N N N N N

↓ α2-antiplasmin vWD

N N

N N/↑

N N

Inherited platelet defects

N

N

N

Bleeding time/ PFA Other tests N/↑* Platelet aggregation N/↓* N FDPs may be ↑ Reptilase time ↑ N 2-stage assay abnormal N Factor V assay N Factor VII assay N Factor VIII assay N Factor IX assay N Factor X assay N Factor XI assay N Abnormal UCLT, ↓ fibrinogen N Abnormal UCLT, ↓ fibrinogen, α2-AP assay ↑ vWF Ag and activity Factor VIII level Ristocetin-induced platelet aggregation ± multimer analysis ↓ Platelet count N/↓ Microscopy: may reveal giant platelets Platelet aggregometry Flow cytometry ± EM of platelet ultrastructure

Plasma half-life 2-4d 3-4d 36 h 4-6h 10 - 14 h 25 h 40 - 60 h 50 h 9 - 12 d 72 h 12 h

In vivo: ~5 d Transfused: 3 - 4 d‡

INR = international normalised ratio; PT = prothrombin time; PTT = partial thromboplastin time; TT = thrombin time; UCLT = urea clot lysis time; PFA = platelet function assay; α2-AP = alpha 2-antiplasmin; vWF = von Willebrand factor; vWD = von Willebrand disease; Ag = antigen; EM = electron microscopy; N = normal; FDP = fibrin/fibrinogen degradation products. *Abnormal test result due to defect in fibrinogen-dependent platelet function. † May be normal in mild haemophilia. ‡ Depends on: (i) time span between collection and transfusion; and (ii) presence of antibodies.

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CME

Table 2. Classification of haemophilia[4] Classification Severe

Factor level, % <1

Moderate

1-5

Mild

6 - 40

Bleeding phenotype Bleed spontaneously without injury Bleed on minor haemostatic challenge/injury Bleed on major haemostatic challenge/injury

Clinical presentation

The clinical presentation of haemophilia takes a number of forms, including acute bleeding episodes, chronic synovitis and haemophilic arthropathy. Bleeding in haemophilia can be spontaneous or follow trauma. The hallmark of haemophilia is spontaneous intra-articular bleeding. The most commonly affected joint is the knee, followed by the ankle, elbow and hip joints.[3] Bleeding into muscle, soft tissue and mucous membranes is less common, but may be organ or life threatening, e.g. intraocular bleeding, central nervous system (CNS) bleeding, and bleeds causing airway obstruction.

There is generally close correlation between the bleeding phenotype and plasma level of clotting factor, although some patients show a discrepancy between the factor level and clinical phenotype. In this regard, haemophilia is classified into severe, moderate and mild phenotypes based on the clotting factor level (Table 2).

Repeated bleeding into joints initiates a vicious cycle of synovial damage, synovial hypertrophy, neovascularisation, and repeated bleeding from the new vessels with further synovial damage.

Untreated synovial damage causes harm to cartilage and articular surfaces, with consequent joint pain and ultimately joint dysfunction.

Diagnosis

Haemophilia is diagnosed by taking an appropriate bleeding history, performing a directed physical examination and confirmatory coagulation tests. A family history with an X-linked pattern of inheritance, together with intra-articular bleeding, is almost certainly associated with haemophilia.

The clinical examination may show evidence of acute joint bleeding or complications of intra-articular bleeding, such as chronic synovitis, joint deformity and limited mobility. The Haemophilia Joint Health Score and the Haemophilia Activity List are useful tools for objective assessment of joint function.

Musculoskeletal radiological assessment, where indicated, includes the affected joints, with the radiographs scored with either the Patterson or Arnold-Hilgartner scoring system. The radiological scoring systems are useful, not only in the cross-sectional assessment but also for the long-term follow-up of patients as pointers for interventions, where the scores indicate worsening joint structure.

The diagnosis of haemophilia should be confirmed with coagulation and/or genetic testing. Haemophilia typically shows a prolonged activated PTT (aPTT) with a normal INR. In the absence of neutralising antibodies, otherwise known as inhibitors, the aPTT corrects with normal plasma, indicating factor deficiency. If the prolonged aPTT does not correct, an inhibitor should be suspected.

An inhibitor assay is performed using either the Bethesda or Nijmegen assay to quantify the level of the inhibitor.

Genotyping is performed to establish the nature of the mutation in the factor VIII or IX gene, as well as for inhibitor risk profiling, as certain genotypes are associated with the risk of inhibitor development. To limit costs, selective genotyping is done, i.e. inversion 22 in

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haemophilia A, as it is the most common genotype associated with inhibitors. Where possible, genetic testing for prenatal diagnosis should be encouraged.

Treatment

The aim of haemophilia treatment is to replace the missing clotting factor to treat or prevent bleeding. The source of clotting factor concentrate (CFC) has evolved in the last seven decades from blood and blood products to recombinant products. Both plasma-derived and recombinant CFCs are currently used. In South Africa, the CFCs are intermediate purity plasma-derived products (Haemosolvate Factor VIII and Haemosolvex Factor IX), which are fractionated locally from blood donor plasma.

Acute bleeding episodes are managed by infusing the missing clotting factor, as well as applying adjunct measures. The dose will depend on the site of bleeding. For haemarthrosis, the recommended peak factor level is 40 - 60 IU/dL for factor VIII and factor IX.[1] In limb and life-threatening bleeds, the target peak level is higher – 80 - 100 IU/dL. The duration of treatment is usually 1 or 2 days, but also depends on the nature of the product used, site of bleeding and severity of bleeding.

The current standard of care in haemophilia is to prevent bleeding by prophylactic infusion of the deficient clotting factor. This dose depends on the trough level to be achieved and potential risk factors for bleeding. The frequency of infusion depends on the pharmacokinetic properties of the infused clotting factor. When using standard half-life products, target trough levels are 1 - 2%, while higher trough levels are achieved with extended half-life products. Standard halflife clotting factor VIII and factor IX are infused 2 - 3 times per week and 1 - 2 times per week, respectively. When using extended half-life products, the dosing interval for factor VIII and factor IX may be increased to 1 - 2 times a week and every 10 - 14 days, respectively.

With the evolving switch from plasma-derived to recombinant products and effective antiviral measures, transfusion-transmitted infections have essentially been eliminated. However, clotting factor replacement therapy is associated with development of neutralising antibodies, i.e. inhibitors, which render replacement of factor ineffective. These occur with a frequency of 20 - 30% in both plasma-derived and recombinant products. The therapeutic strategy in patients who have developed high responding inhibitors is two-fold, i.e. treatment of acute bleeding episodes and eradication of the inhibitor. For acute bleeding episodes, bypassing agents, i.e. activated prothrombin complex concentrate (aPCC) or recombinant activated factor VII (FVIIa), are shown to be safe and efficacious.

The registered dose for rFVIIa is 90 µg/kg × 3 or 270 µg/kg administered once, and that for aPCC is 50 - 100 IU/kg repeated at 12-hourly intervals. Inhibitor eradication strategies take the form of a number of protocols, including the Malmö protocol, Bonn regimen and Dutch protocol. The aim of eradication therapy is to remove the inhibitor so that patients can be treated with standard replacement therapy again. The efficacy of eradication therapy is variable, with most success rates of 80 - 100% seen in the paediatric population in the early phase of inhibitor development.

von Willebrand disease Background

vWD is a common IBD affecting 1.3% of the population.[5,6] It is caused by a quantitative (reduced amount) or qualitative (abnormal function) deficiency in von Willebrand factor (vWF), combinations of which result in the various vWD subtypes (Table 3). vWF is synthesised by endothelial cells and megakaryocytes and is a complex

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CME

Table 3. Classification of von Willebrand disease Defects Quantitative vWF defects

Qualitative vWF defects

Subtype Molecular defect 1 Partial quantitative deficiency

Clinical severity Mild - moderate

3

Virtually complete absence of vWF

2A

↓ vWF-dependent platelet adhesion

2B

Gain of function mutation with ↑ vWF platelet adhesion

2M

↓ vWF platelet adhesion

2N

↓ vWF affinity for factor VIII

Laboratory features vWF levels: 5 - 30% of normal Severe: presents early vWF levels: in life very low or absent Moderate - severe vWF plasma levels: variably ↓ vWF-platelet interaction: markedly ↓ with loss of HMW multimers Moderate - severe vWF plasma levels: usually ↓ Loss of HMW vWF multimers and ↑ vWF-platelet binding Moderate - severe vWF plasma levels: variably ↓ vWF-platelet interaction: variably ↓ without loss of HMW multimers Moderate - severe vWF level: normal Factor VIII level: markedly ↓

Frequency 60 - 80% of vWD Rare: 1 - 5% of vWD 15 - 20% of vWD

Rare

Rare

Rare

HMW = high molecular weight; vWF = von Willebrand factor, vWD = von Willebrand disease.

plasma protein with multiple functions, including binding to exposed sub-endothelial collagen and platelet glycoprotein Ib (GPIb) receptors, thus facilitating platelet adhesion at the site of vessel damage (primary haemostasis). vWF further binds to and prolongs the half-life of circulating coagulation factor VIII, delivering it to sites of vascular injury (secondary haemostasis). Larger vWF molecules with high molecular weight (HMW vWF multimers) facilitate better anchoring of platelets and thus thrombus formation, achieving more effective haemostasis. The complex functions of vWF can be measured by individual laboratory tests.[5-7]

Clinical presentation

Patients suffering from vWD usually present with mucocutaneous bleeding, including epistaxis, easy bruising, menorrhagia and excessive bleeding from minor wounds, tooth extractions and surgery. The clinical presentation is, however, very heterogeneous and the rate of spontaneous bleeding may be low, even in patients with severe vWF deficiency. There is frequently a family history of abnormal bleeding and excessive bruising, as vWD is an inherited disorder that most frequently displays an autosomal dominant pattern. Although the autosomal inheritance pattern would suggest an equal distribution between both genders, the disease is more often diagnosed in females because of female-specific haemostatic challenges, including menstruation and childbirth. vWF levels do not always correlate with bleeding symptoms and can be variable between affected family members. As factor VIII is usually only mildly reduced or normal in vWD, the manifestations in patients with haemophilia, a severe coagulation factor deficiency disorder, such as haemarthrosis and deep muscle haematomas, are rare, except in type 3 disease. Gastrointestinal bleeding also occurs and can be difficult to manage, especially in patients lacking HMW multimers. Bleeding after dental extraction is the most frequent postoperative bleeding manifestation, whereas bleeding

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after surgery may occur in more severely affected types 1 and 3 vWD patients. Bleeding in the postpartum period is rarely observed in type 1 vWD, as factor VIII/vWF levels correct at the end of pregnancy in mild type 1 cases. Patients with vWD types 2A, 2B and 3 usually require replacement therapy post-partum to prevent immediate or delayed haemorrhage.[5-8]

Diagnosis

The diagnosis of vWD, and in particular type 1, may be difficult owing to clinical heterogeneity and difficulties in standardising laboratory tests. In vWD patients, the platelet count is usually normal, except in the relatively rare type 2B subtype, in which a mild to moderate thrombocytopenia can occur. The PT is normal, whereas the aPTT may be prolonged, depending on the plasma factor VIII levels. Unfortunately, there is no single test to diagnose vWD. The standard diagnostic tests include measurement of total vWF protein (vWF antigen), a vWF activity (such as ristocetin-cofactor activity) and ristocetin-induced platelet aggregation (RIPA), which determine the ability of vWF to bind platelets. Coagulation factor VIII levels are also measured. Specialised tests, such as vWF multimers and vWF binding to platelets and factor VIII, assist with the sub-classification of vWD. Various physiological and pathological events, including pregnancy, stress and bleeding, can temporarily normalise vWF levels in patients with the condition and should be taken into account when testing for vWD. The exclusion of vWD, depending on the results of laboratory tests, is therefore only made once three normal tests separated in time are obtained. Levels of vWF vary among different ethnic groups and blood types.[6,7,9]

Treatment

Treatment of vWD is based on normalising vWF and factor VIII levels in cases of bleeding or before a planned intervention, such as surgery or delivery. This can be achieved with desmopressin (DDAVP) or

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CME

by infusing exogenous coagulation factors in the form of a highpurity vWF concentrate or low-purity factor VIII/vWF concentrate.[6] Desmopressin, an analogue of human antidiuretic hormone (ADH), releases vWF and factor VIII from endothelial cells into the circulation. vWF concentrates are used for the treatment of active bleeding or prophylaxis of bleeding with invasive procedures. There is currently no recommendation for any vWF product for routine prophylaxis to prevent recurrent, spontaneous or incidental haemorrhage.[10] General measures include antifibrinolytic therapy, e.g. tranexamic acid, the combined oral contraceptive pill, avoidance of antiplatelet agents (such as aspirin) and treatment of resultant anaemia.[8]

Other clotting factor deficiencies

These are less common than haemophilia A and B, and include deficiencies of factors V, VII, X, XI, XIII and fibrinogen, and protease inhibitors. The mode of inheritance is usually autosomal recessive.

The expected results of diagnostic tests are summarised in Table 1.

Fibrinogen abnormalities

Afibrinogenaemia/hypofibrinogenaemia This bleeding disorder is rare and surprisingly less severe than haemophilia, where 20% of patients develop haemarthrosis. Patients generally present with bleeding at mucosal sites, e.g. menorrhagia and umbilical stump bleeding in neonates. Although severe bleeding is uncommon, intracranial haemorrhage in childhood is the leading cause of death.[11] First-trimester abortion is common in females with afibrinogenaemia.

Dysfibrinogenaemias are qualitative defects that may be associated with bleeding or thrombosis, depending on the site of mutation.

Patients may present with defective wound healing and recurrent miscarriages. The mode of inheritance is autosomal dominant.

Treatment for bleeding due to fibrinogen abnormalities is on-demand fibrinogen replacement with fresh frozen plasma, cryoprecipitate or fibrinogen concentrate during bleeding episodes.

For frequent or life-threatening bleeding episodes, prophylactic fibrinogen replacement every 7 - 14 days should be considered.

Prothrombin, and factors V, VII and X

Deficiencies of any of the above-mentioned factors are rare, of which factor VII deficiency is the most common autosomal recessive coagulation disorder (frequency 1:500 000) and prothrombin deficiency the rarest (1:2 000 000). Severity of bleeding episodes is variable and may occur at various sites, including mucosal surfaces, intra-articular sites, gastrointestinal tract and CNS. Spontaneous haemorrhage is uncommon.

Combined factor V and factor VIII deficiency has been described in some families,[12] and should be treated with replacement of factor in various preparations, depending on availability, i.e. fresh frozen plasma, PCC, factor VII concentrate or recombinant factor preparations.

Factor XI deficiency (haemophilia C)

Factor XI deficiency occurs at an overall frequency of 1:1 000 000, but is more common in Ashkenazi Jews with homozygous and heterozygous frequencies of 0.3% and 8.0%, respectively. The extent of bleeding manifestations is variable, but usually occurs after surgery or trauma.

Spontaneous bleeding is uncommon. Treatment includes factor XI replacement (fresh frozen plasma, factor XI concentrate) or antifibrinolytic agents.

Kindred with combined factor XI and factor IX deficiency have been described.[13] Factor XI deficiency may be encountered in Gaucherâ&#x20AC;&#x2122;s disease and Noonanâ&#x20AC;&#x2122;s syndrome.[14,15]

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Factor XIII deficiency

Factor XIII stabilises the clot by forming intermolecular covalent bonds between fibrin molecules. In deficient states, bleeding may occur with varying severity at different sites, including mucosal surfaces, soft tissue, intra-articular, intraperitoneal and CNS sites.

Severe bleeding episodes in neonates are common, viz. umbilical stump (80%) and CNS bleeding (up to 30%). Deficiency of factor XIII should be suspected when there is delayed wound healing or a bleeding disorder in the presence of a normal PTT, PT/INR, bleeding time and platelet count.

As factor XIII has a long half-life, prophylactic replacement therapy every 4 weeks with factor XIII concentrate or cryoprecipitate is effective as a preventive strategy.

Protease inhibitors

Protease inhibitors include alpha 2-antiplasmin, plasminogen activator inhibitor-1 and alpha 1-antitrypsin.

Alpha 2-antiplasmin deficiency is inherited as a rare autosomal recessive disorder. The homozygous form causes severe bleeding episodes. Suspicion of the condition is aroused when the fibrinogen level is decreased and the urea clot lysis time is shortened.

Confirmation of the diagnosis is obtained through fluorometric or chromogenic assays.

Vitamin K-dependent coagulation factor deficiency

The vitamin K-dependent factors II, VII, IX and X require gammacarboxylation of glutamic acid residues to enable binding to Ca++.

Vitamin K-dependent coagulation factor deficiency is caused by deficiency of enzymes responsible for gamma-carboxylation. Patients present with bleeding of varying degrees of severity and may have associated skeletal abnormalities.

The mode of treatment is parenteral vitamin K administration, and fresh frozen plasma or PCC if response is suboptimal.

Inherited platelet function disorders Platelet structure and function

Platelets are small (2 Âľm) anuclear cells produced by megakaryocytes in the bone marrow. In the resting state, platelets have a smooth discoid shape and contain cytoplasmic organelles, cytoskeletal elements, platelet-specific alpha and dense granules and an invaginating opencannalicular phospholipid membrane. In the outer plasma membrane there are numerous receptors for ligands, such as fibrinogen, collagen, thrombin and vWF for primary haemostasis.

Platelets promote primary haemostasis by four mechanisms.[16] The initial step is platelet adhesion. Following damage to the vessel wall, platelets undergo rapid activation by thrombin. vWF is a large, multimeric protein secreted from endothelial cells. At high shear rates, the platelet GP1b undergoes a conformational change, which promotes platelet adhesion to vWF. Platelet adhesion stimulates Table 4. Investigations for platelet disorders Screening tests Full blood count and smear review Bleeding time Platelet function analyser Diagnostic tests Platelet aggregation Flow cytometry Platelet secretion testing Electron microscopy

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intracellular signalling, leading to granule release of alpha granules (platelet factor 4, thrombospondin, platelet-derived growth factor, factor V, fibrinogen, vWF, beta-thromboglobulin) and dense granules (calcium, adenosine diphosphate (ADP), serotonin). ADP release causes a conformational change of the fibrinogen receptor, GPIIb/ IIIa. Fibrinogen forms a bridge between adjacent platelets, resulting in platelet aggregation and the formation of a primary platelet plug.

Activated platelets also expose negatively charged phospholipids on the surface membrane, which provides a procoagulant surface for the formation of a secondary stable clot. Platelet disorders can be classified according to disorders of platelet function.

Clinical presentation

Inherited platelet disorders are a rare, wide spectrum of disorders characterised by a variable bleeding pattern. This usually presents as prolonged bleeding after haemostatic challenges or in childhood, with spontaneous mucocutaneous bleeding from gastrointestinal and genitourinary sites.[17]

Laboratory investigations

A careful medical, drug and family bleeding history should be taken and a physical examination should be performed before requesting laboratory investigations for platelet disorders (Table 4).[18] The traditional screening tests include a FBC, peripheral blood smear review and bleeding time/platelet function assay. The normal range for the platelet count is 150 - 400 × 109/L. Qualitative platelet disorders can be distinguished by morphological features. The bleeding time test has largely been replaced with automated platelet function assays as a screening test to evaluate platelet function because of the poor reproducibility and wide variability of bleeding time tests.[19] Definitive diagnosis requires specific tests, which are available in specialist laboratories.[20] Platelet aggregation studies measure the ability of agonists to cause in vitro platelet activation and binding. Flow cytometry is used to diagnose deficiencies of platelet glycoproteins with fluorescently labelled antibodies. Lastly, electron microscopy (EM) is useful for the evaluation of the ultrastructure of platelets.

The more common inherited platelet disorders

• Glanzmann thrombasthenia is a severe, autosomal recessive bleeding disorder caused by a deficiency of GPIIb/IIIa, the receptor responsible for platelet aggregation. The diagnosis is made on platelet aggregation or flow cytometry studies. No aggregation response to ADP agonists, collagen, adrenaline and arachidonic acid occurs.

• Bernard-Soulier syndrome is an autosomal recessive deficiency of the platelet GP1b/IX/V receptor, which is responsible for platelet adhesion. Patients with Bernard-Soulier syndrome also have a moderate thrombocytopenia, with large platelets. The diagnosis can be confirmed on platelet aggregation or flow cytometry studies. There is a normal aggregation response to ADP agonists, collagen, adrenaline and arachidonic acid, but aggregation is absent with the addition of ristocetin.

• Secretory disorders occur secondary to deficiencies of alpha and/ or dense granules or defects in signal transduction. Dense granule storage pool disorders (SPDs) have decreased aggregation with ADP, adrenaline and collagen and often occur in association with other hereditary disorders. EM usually shows decreased dense granules. Gray platelet syndrome is an autosomal dominant alpha SPD characterised by mild bleeding symptoms. Platelets appear grey due to decreased alpha granules.

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• May-Hegglin anomaly is a group of autosomal dominant thrombocytopenias consisting of May-Hegglin anomaly and Sebastian, Fechtner and Epstein syndromes and is characterised by large platelets and thrombocytopenia (20 - 130 × 109/L). It presents as a mild bleeding disorder. There is a normal aggregation response.

EM confirms the diagnosis.

• Scott syndrome is a rare congenital disorder due to defective platelet membrane flip-flop action, with decreased exposure of procoagulant platelet membrane surfaces.

Management

The cornerstone of management is supportive care. Antifibrinolytics, e.g. tranexamic acid, are an important adjuvant. Specific management depends on the particular type of disorder, as well as the severity of the bleeding. Desmopressin has been shown to be effective in SPDs and mild platelet function disorders, and may be of benefit in Bernard-Soulier syndrome. Platelet transfusions and rFVIIa are used in cases of severe/life-threatening bleeding.

In summary, inherited platelet disorders are a rare group of disorders characterised by mild to severe mucocutaneous bleeding.

A careful bleeding history should be taken before referring patients to specialist laboratories for investigations for platelet disorders. The latter should be managed at specialist haemophilia centres.[21]

Vessel wall defects

Vessel wall abnormalities are among the IBDs that are associated with normal screening tests. They include hereditary haemorrhagic telangiectasia (HHT) (an autosomal dominant structural vascular abnormality) and hereditary connective tissue disorders (such as Ehlers-Danlos syndrome and osteogenesis imperfecta). Of these, HHT is the most common, with an incidence of ~1:5 000 - 10 000.

It presents in the 2nd or 3rd decade of life with telangiectatic lesions (0.5 - 1 mm red lesions that blanche with pressure), which are typically seen on the lips, oral mucosa and finger tips. It is typified by mucosal bleeding (commonly epistaxis or gastrointestinal blood loss), with consequent iron deficiency. Catastrophic bleeding is uncommon. HHT may have associated arteriovenous malformations/fistulae of solid organs (particularly the lung, liver and CNS). Arteriovenous fistulae may be associated with significant complications, such as embolic phenomena, high-output cardiac failure and portal hypertension.

Management includes iron supplementation, laser ablation and, in the case of arteriovenous fistulae, embolisation.

Conclusion

Abnormal bleeding is commonly encountered in general practice, and a rational approach to this problem is therefore required. Investigation of abnormal bleeding requires a comprehensive history, thorough physical examination and systematic laboratory work-up. Patients diagnosed with an IBD should be referred to a tertiary healthcare facility, such as a haemophilia centre for long-term management.

Acknowledgements. Mr C Moodly for reviewing the technical aspects of laboratory tests.

Author contributions. Selected sub-sections prepared by respective authors listed. NA and JV: review of manuscript; and NA: co-ordination and editing of information.

Funding. None.

Conflicts of interest. None.

1. Srivastava A, Brewer AK, Mauser-Bunschoten EP, et al. Guidelines for the management of hemophilia.

Haemophilia 2013;19(1):e1-e47. https://dx.doi.org/10.1111/j.1365-2516.2012.02909.x

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2. Stonebraker JS, Bolton-Maggs PH, Soucie JM, Walker I, Brooker M. A study of variations in the reported haemophilia: A prevalence around the world. Haemophilia 2010;16(1):20-32. https://dx.doi. org/10.1111/j.1365-2516.2011.02588.x 3. Mahlangu JN, Gilham A. Guideline for haemophilia treatment in South Africa. S Afr Med J 2008;98(2):126-140.

4. White GC, Rosendaal F, Aledort LM, Lusher JM, Rothschild C, Ingerslev J. Definitions in hemophilia.

Recommendation of the scientific subcommittee on factor VIII and factor IX of the scientific and standardization committee of the International Society on Thrombosis and Haemostasis. Thromb Haemost 2001;85(3):560.

5. Echahdi H, El Hasbaoui B, El Khorassani M, et al. Von Willebrand’s disease: Case report and review of literature. Pan Afr Med J 2017;27:147. https://dx.doi.org/10.11604/pamj.2017.27.147.12248 6. Leebeek FW, Eikenboom JC. Von Willebrand’s Disease. N Engl J Med 2017;376(7):701-702. https:// dx.doi.org/10.1056/NEJMc1616060 7. Bowman ML, James PD. Controversies in the diagnosis of type 1 von Willebrand disease. Int J Lab Hematol 2017;39(Suppl 1):61-68. https://dx.doi.org/ 10.1111/ijlh.12653 8. Castaman G, Linari S. Diagnosis and treatment of von Willebrand disease and rare bleeding disorders.

Clin Med 2017;6(4):E45. https://dx.doi.org/10.3390/jcm6040045.

9. Montgomery RR, Flood VH. What have we learned from large population studies of von Willebrand disease? Hematol Am Soc Hematol Educ Program 2016;2016(1):670-677. https://dx.doi.org/10.1182/ asheducation-2016.1.670 10. Neff AT. Current controversies in the diagnosis and management of von Willebrand disease. Ther Adv Hematol 2015;6(4):209-216. https://doi.org/10.1177/2040620715587879 11. Montgomery R, Natelson SE. Afibrinogenemia with intracerebral hematoma: Report of a successfully treated case. Am J Dis Child 1977;131:555-556.

12. Seligsohn U, Zivelin A, Zwang E. Combined factor V and factor VIII deficiency among non-Ashkenazi Jews. N Engl J Med 1982;307(19):1191-1195. https://dx.doi.org/10.1056/NEJM198211043071907 13. Soff GA, Levin J, Bell WR. Familial multiple coagulation deficiencies. Combined factor VIII, IX and XI deficiency and combined IX and XI deficiency: Two previously uncharacterized familial multiple factor deficiency syndromes. Sem Thromb Hemost 1981;7(2):149-169. https://dx.doi. org/10.1055/s-2007-1005074

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14. Berrebi A, Malnick SDH, Vorst EJ, et al. High incidence of factor XI deficiency in Gaucher’s disease.

Am J Hematol 1992;40(2):153. https://dx.doi.org/10.1002/ajh.2830400215 15. Kitchens CS, Alexander JA. Partial deficiency of coagulation factor XI as a newly diagnosed feature of Noonan syndrome. J Pediatr 1983;102(2):224-227. https://doi.org/10.1016/s0022-3476(83)80525-3 16. Gresele P; Subcommittee on Platelet Physiology of the International Society on Thrombosis and Hemostasis. Diagnosis of inherited platelet function disorders: Guidance from the SSC of the ISTH. J Thromb Haemost 2015;13(2):314-322. https://doi.org/10.1111/jth.12792 17. Kenny D, Mezzano D, Mumford AD, et al. Diagnosis of suspected inherited platelet function disorders: Results of a worldwide survey. J Thromb Haemost 2014;12(9):1562-1592. https://dx.doi.org/10.1111/ jth.12650 18. Israels SJ, El-Ekiaby M, Quiroga T, Mezzano D. Inherited disorders of platelet function and challenges to diagnosis of mucocutaneous bleeding. Haemophilia 2010;16:152-159. https://dx.doi.org/10.1111/ j.1365-2516.2010.02314.x 19. Hayward CP, Rao AK, Cattaneo M. Congenital platelet disorders: Overview of their mechanisms, diagnostic evaluation and treatment. Haemophilia 2006;12(3):128-136. https://dx.doi.org/10.1111/ j.1365-2516.2006.01270.x 20. Bolton-Maggs PH, Chalmers EA, Collins PW, et al. A review of inherited platelet disorders with guidelines for their management on behalf of the UKHCDO. Br J Haematol 2006;135(5):603-633. https://dx.doi.org/10.1111/j.1365-2141.2006.06343.x 21. Geddis AE. Inherited thrombocytopenias: An approach to diagnosis and management. Int J Lab Hematol 2012;35(1):14-25. https://dx.doi.org/10.1111/j.1751-553X.2012.01454.x 22. Kumar N, Garg N, Khunger M, Gupta A. Optimal management of hereditary hemorrhagic telangiectasia. J Blood Med 2014;5:191-206. https://doi.org/10.2147/JBM.S45295

Accepted 24 November 2017.

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This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

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Nutritional supplements for people being treated for active tuberculosis: A technical summary L Grobler,1 PhD, BSc Hons, BSc; S Durao,2,3 MPH, BScDiet; S M van der Merwe,4 MNutr, BDiet; J Wessels,5 BScDiet; C E Naude,1,2 PhD, MNutr, BScDiet Centre for Evidence-Based Health Care, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa Cochrane Nutrition, hosted jointly by the Centre for Evidence-Based Health Care, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa, and Cochrane South Africa, South African Medical Research Council 3 Cochrane South Africa, South African Medical Research Council, Cape Town, South Africa 4 Integrated Nutrition Programme, Mpumalanga Department of Health, Nelspruit, South Africa 5 Standerton Tuberculosis Specialised Hospital, Mpumalanga Department of Health, Standerton, South Africa 1 2

Corresponding author: L Grobler (liesl.nicol@gmail.com)

Tuberculosis and nutrition are intrinsically linked in a complex relationship. Altered metabolism and loss of appetite associated with tuberculosis may result in undernutrition, which in turn may worsen the disease or delay recovery. We highlight an updated Cochrane review assessing the effects of oral nutritional supplements in people with active tuberculosis who are receiving antituberculosis drug therapy. The review authors conducted a comprehensive search (February 2016) for all randomised controlled trials comparing any oral nutritional supplement, given for at least 4 weeks, with no nutritional intervention, placebo or dietary advice only in people receiving antituberculosis treatment. Of the 35 trials (N=8 283 participants) included, seven assessed the provision of free food or high-energy supplements, six assessed multi-micronutrient supplementation, and 21 assessed single- or dual-micronutrient supplementation. There is currently insufficient evidence to indicate whether routinely providing free food or high-energy supplements improves antituberculosis treatment outcomes (i.e. reduced death and increased cure rates at 6 and 12 months), but it probably improves weight gain in some settings.

Plasma levels of zinc, vitamin D, vitamin E and selenium probably improve with supplementation, but currently no reliable evidence demonstrates that routine supplementation with multi-, single or dual micronutrients above the recommended daily intake has clinical benefits (i.e. reduced death, increased cure rate at 6 and 12 months, improved nutritional status) in patients receiving antituberculosis treatment. In South Africa, most provinces implement a supplementation protocol based on nutritional assessment and classification of individuals rather than on disease diagnosis or treatment status.

S Afr Med J 2018;108(1):16-18. DOI:10.7196/SAMJ.2018.v108i1.12839

There is a complex relationship between tuberculosis and nutrition.[1] The immunodeficiency caused by undernutrition increases the risk of acquiring tuberculosis.[2] Alternatively, tuberculosis may cause undernutrition through increased metabolic demands and decreased appetite. The resulting nutritional deficiencies may worsen the disease or delay recovery by depressing immune function.[3,4] A key guiding principle of the World Health Organization guidelines on nutritional care and support for patients with tuberculosis[5] is that â&#x20AC;&#x2DC;an adequate diet, containing all essential macro- and micronutrients, is necessary for the well-being and health of all people, including those with TB infection or TB diseaseâ&#x20AC;&#x2122;. However, owing to limited available evidence there is still no evidence-based nutritional guidance specific to adults and children who are being treated for active tuberculosis.

We summarise the evidence from an updated Cochrane review assessing the effects of oral nutritional supplements on all-cause death and cure at 6 and 12 months in patients receiving treatment for active tuberculosis.[1]

Methods

The review authors conducted a comprehensive search of eight databases up to February 2016, without language or date restrictions.

All randomised controlled trials comparing any oral nutritional supplement, given for at least 4 weeks, with no nutritional intervention, placebo or dietary advice only to patients receiving

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treatment for active tuberculosis were included. The review authors followed standard Cochrane methods for independent screening and eligibility assessment, data extraction, risk of bias assessment and data analysis. The quality of the evidence was assessed using the Grading of Recommendation Assessment, Development and Evaluation (GRADE) approach.[1]

Results

Of the 35 eligible trials (N=8 283 participants), four were conducted in children (n=739) and 11 specifically presented disaggregated outcome data for HIV-positive and HIV-negative participants. Most of the trials were conducted in Africa and Asia.

Macronutrient supplementation

Seven trials investigated the effect of providing free food or highenergy nutritional supplements. The trials were too small to reliably demonstrate or exclude clinically important benefits on mortality (risk ratio (RR) 0.34, 95% confidence interval (CI) 0.10 - 1.20; four trials, 567 participants, very low-quality evidence), cure (RR 0.91, 95% CI 0.59 - 1.41; one trial, 102 participants, very low-quality evidence), or treatment completion (data not pooled; two trials, 365 participants, very low-quality evidence). Providing free food or high-energy nutritional supplements probably produces modest weight gain during treatment for active tuberculosis, although this

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was not consistent across all included trials (data not pooled; five trials, 883 participants, mean weight gain 0.78 - 2.6 kg, moderatequality evidence). There is some evidence that quality of life may be improved, but the trials were too small to have much confidence in the result (data not pooled; two trials, 134 participants, low-quality evidence) (Table 1).[1]

Multi-micronutrient supplementation

Six trials assessed multi-micronutrient supplementation in doses up to 10 times the recommended dietary allowance (RDA).[6] Routine multi-micronutrient supplementation may have little or no effect on mortality in HIV-negative people with tuberculosis (RR 0.86, 95% CI 0.46 - 1.6; four trials, 1 219 participants, low-quality evidence), or HIV-positive people not taking antiretroviral therapy (RR 0.92, 95% CI 0.69 - 1.23; three trials, 1 429 participants, moderate-quality evidence). There is insufficient evidence to know whether multimicronutrient supplementation improves cure (no trials), treatment completion (RR 0.99, 95% CI 0.95 - 1.04; one trial, 302 participants, very low-quality evidence), or the proportion of people who remain sputum-positive during the first 8 weeks of antituberculosis treatment (RR 0.92, 95% CI 0.63 - 1.35; two trials, 1 020 participants, very lowquality evidence). Furthermore, multi-micronutrient supplementation may have little or no effect on weight gain during treatment (data not pooled; five trials, 2 940 participants, low-quality evidence),

and no studies have assessed the effect on quality of life. The summary of findings for multi-micronutrient supplementation is available for the outcomes death, cure rate, treatment completion, remaining sputumpositive (4 weeks), weight gain and quality of life.[1]

Single- or dual-micronutrient supplementation

Eighteen trials assessed single- or dual-micronutrient supplementation. Low vitamin A levels are common in tuberculosis, and plasma levels of vitamin A appear to increase following initiation of antituberculosis treatment regardless of supplementation. There is no evidence that vitamin A supplementation in doses up to three times the RDA has a beneficial effect on tuberculosis treatment outcomes (i.e. death (RR 0.97, 95% CI 0.84 - 1.12; eight trials, 3 308 participants), sputum smear- or culture-positive after 4 weeks (RR 0.70, 95% CI 0.33 - 1.48; one trial, 148 participants)) or nutritional recovery (body mass index: RR 0.3, 95% CI –0.44 - 1.04; one trial, 148 participants). In contrast, supplementation probably improves plasma levels of zinc, vitamin D, vitamin E and selenium, but this has not been shown to have clinically important benefits.

Of note, despite multiple studies of vitamin D supplementation in different doses, statistically significant benefits on sputum conversion have not been demonstrated (number of participants who were sputum smear- or culture-positive after 4 weeks: RR 0.87, 95% CI 0.74 - 1.03; five trials, 929 participants).[1]

Table 1. Summary of findings: Food provision (calorie supplementation as food or energy-dense supplements) compared with standard care (nutritional advice or no intervention) for adults and children with active tuberculosis* Number of participants (trials)

Quality of the evidence (GRADE)

Outcomes

Standard care

Increased calorie intake

Death (at 6 months) (95% CI)

3 per 100

1 per 100 (0 - 4)

RR 0.34 (0.10 - 1.20)

567 (4 trials)

Very low†‡§

Cured (at 6 months) (95% CI)

48 per 100

44 per 100 (28 - 68)

RR 0.91 (0.59 - 1.41)

102 (1 trial)

Very lowद

Treatment completion (at 6 months) (95% CI)

79 per 100

85 per 100 (70 - 100)

Not pooled

365 (2 trials)

Very low§||**

Sputum negative (at 8 weeks) (95% CI)

76 per 100

82 per 100 (65 - 100)

RR 1.08 (0.86 - 1.37)

222 (3 trials)

Very low§||**

Mean weight gain (at 8 weeks) (95% CI)

-

-

MD 0.78 (–0.05 - 1.6)

883 (5 trials)

Moderate††‡‡

Quality of life (change in quality of life score), mean (SD)

At 6 weeks: 13.33 (24.76)

14.47 (25.43)

Not pooled

134 (2 trials)

Low§§¶¶

At 24 weeks: 18.75 (27.38)

8.33 (22.49)

Relative effect

CI = confidence interval; SD = standard deviation; RR = risk ratio; MD = mean difference; GRADE: Grading of Recommendations Assessment, Development and Evaluation.

GRADE Working Group grades of evidence: High quality: further research is very unlikely to change our confidence in the estimate of effect.

Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.

Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.

Very low quality: we are very uncertain about the estimate. *This technical summary is an adapted version of a Cochrane Review Summary of Findings table previously published[1] in the Cochrane Database of Systematic Reviews 2016, Issue 6, https:// doi.org/10.1002/14651858.CD006086.pub4 (see www.cochranelibrary.com for information). Cochrane reviews are regularly updated as new evidence emerges and in response to feedback, and the Cochrane Database of Systematic Reviews should be consulted for the most recent version of the review. † Three trials reported some deaths during the 6 months of treatment (Jahnavi 2010; Jeremiah 2014; Sudarsanam 2010), and one reported that no deaths occurred (Martins 2009). The trials were conducted in Tanzania, Timor-Leste, and India in participants with signs of undernutrition. Martins 2009 gave a daily hot meal, Sudarsanam 2010 gave monthly ration packs, Jahnavi 2010 gave daily locally appropriate supplements, and Jeremiah 2014 gave high-energy multivitamin-enriched biscuits. ‡ Downgraded by 1 for indirectness: trials are only available from limited settings. Food supplementation would plausibly have its biggest effect in highly food-insecure or emergency settings, which are not reflected in these trials. § Downgraded by 2 for imprecision: the trials and meta-analysis are significantly underpowered to either detect or exclude an effect if it exists. ¶ Data on successful cure at 6 months are only available from Sudarsanam 2010, which randomised tuberculosis patients in India to monthly ration packs or advice only. || Two trials report on tuberculosis treatment completion at 6 months (Jahnavi 2010; Martins 2009). One trial was conducted in India and one in Timor-Leste in participants with signs of undernutrition. Both trials gave daily locally appropriate supplements. **Downgraded by 1 for inconsistency. Jahnavi 2010 found a statistically significant benefit, while the larger trial, Martins 2009, did not. †† Five studies reported measures of weight gain but at different time points, which prevented meta-analysis. The relative effect was derived from three trials (Jeremiah 2014; Martins 2009 and Praygod 2011b) that provided change and/or actual mean weight data at 8 weeks. ‡‡ Downgraded by 1 for inconsistency. Praygod 2011b included only HIV-positive patients, and although the trend was towards a benefit, this did not reach statistical significance. Jeremiah 2014 noted a greater increase in mean weight gain in the supplemented group compared with the non-supplemented group after 8 weeks; however, the difference was not appreciable (1.09 kg, p<0.6, authors’ own figures). The three other trials all demonstrated clinically important benefits. §§ Downgraded by 1 for indirectness. Only two small trials, one from Singapore (Paton 2004) and one from India (Jahnavi 2010), report quality-of-life scores. The results cannot be generalised to other populations or settings with any certainty. ¶¶ Downgraded by 1 for imprecision. The presented data appear highly skewed and could not be pooled.

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Conclusion

The review authors concluded that based on the current research they do not know whether routinely providing free food or energy supplements results in better antituberculosis treatment outcomes (decreased tuberculosis-related mortality, increased cure rate, increased tuberculosis treatment completion rate); however, limited evidence suggests that it probably improves weight gain in some settings. There is also no reliable evidence that routine supplementation with multi-micronutrients or specific individual micronutrients above recommended daily amounts has clinical benefits. Of note for future research, according to the review authors’ calculations, none of the included trials or meta-analyses of trials were sufficiently powered to detect clinically important effects on the outcomes of interest.[1]

This evidence in the South African context

Tuberculosis is the leading cause of underlying natural deaths in South Africa (SA), even through the proportions of natural deaths attributed to tuberculosis have declined over time (8.8% in 2013, 8.3% in 2014, 7.2% in 2015).[7] The 2016 Global Tuberculosis Report estimated that SA had the sixth-greatest number of incident cases and third-greatest incidence in relation to population.[8] The incidence of multidrug-resistant (MDR) and extensively drug-resistant tuberculosis is increasing, and SA is deemed at risk of having a MDR tuberculosis-dominated tuberculosis pandemic.[9] According to the 2015/2016 District Health Barometer,[10] the incidence of tuberculosis in SA has decreased over the past 5 years, with the most notable decline in KwaZulu-Natal Province. The Eastern Cape, KwaZulu-Natal and Western Cape have the highest incidence of tuberculosis, while Mpumalanga, Gauteng and Limpopo provinces rank the lowest. Districts with the highest tuberculosis incidence were Sarah Baartman (Eastern Cape), Pixley ka Seme (Northern Cape) and Nelson Mandela Bay (Eastern Cape).[10] While the national guiding document on nutritional supplementation is being finalised, most provinces implement a supplementation protocol based on the nutritional assessment and nutritional classification of individuals rather than on disease diagnosis or treatment status. Nutritional supplementation is discontinued when nutritional status goals are met. Macronutrient supplementation practices often depend on budget and human resource availability, and mostly involve providing undernourished individuals with varying quantities (range 2 - 7 kg per month) and combinations of enriched maize porridge, enriched energy drinks and mageu (lactic acid-fermented maize-based drink). Eligibility criteria for nutritional supplementation differ between provinces and according to age, mostly referring to a body mass index <18.5 kg/m2 in adults.

Two recent studies in adult tuberculosis patients in Delft in the Western Cape[11] and Standerton in Mpumalanga (J Wessels, ‘Nutritional status of patients with tuberculosis and TB/HIV co-infection at Standerton TB Specialised Hospital, Mpumalanga’, unpublished data) show that newly admitted patients with active tuberculosis are undernourished (body mass index <18.5 kg/m2).

Considering the findings of these studies and the Cochrane review, the current national nutritional supplementation practices, which focus on addressing undernutrition in general rather than diseasespecific nutritional requirements, would appear to be appropriate.

One exception may be pregnant women with active tuberculosis. In pregnant women, tuberculosis is associated with high mortality rates and poor treatment outcomes, and as such these women may require additional nutritional support.

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In SA, the burden of tuberculosis disproportionately affects people who are chronically impoverished, hungry and malnourished, who have an increased risk not only of developing tuberculosis but also of poor tuberculosis treatment outcomes.[12,13] National data show that almost a third (28.3%) of all adults are at risk of food insecurity and just over a quarter of all adults (26%) are food insecure.[14] Approximately 70% of patients (n=100) admitted to a specialist tuberculosis hospital in Mpumalanga were from food-insecure households (J Wessels, unpublished data). Patients with tuberculosis also incur substantial direct (e.g. transport to and from the clinic for consultation and treatment) and indirect (e.g. time and income loss due to absence from work) costs related to their condition,[15] further exacerbating the social inequity. Currently, only 5% of all tuberculosis patients access the disability grant provided through the South African Social Security Agency.[15] Improving access to the disability grant, as well as a possible expansion thereof to tuberculosis patients contingent on treatment adherence or other relevant improved health behaviours associated with tuberculosis risk (e.g. stopping smoking),[16] along with effective implementation of nutritional supplementation when indicated, deserves due attention in the fight to improve the concomitant and intergenerational burden of poor nutrition and tuberculosis in SA. Acknowledgements. S Nagpal, T D Sudarsanam and D Sinclair, co-authors of the Cochrane review, are acknowledged for all their input into the review.

Author contributions. LG summarised the evidence from the Cochrane Review with the assistance of SD and CEN. SMvdM and JW drafted the section on the evidence in the SA context.

Funding. Partly supported by the Effective Health Care Research Consortium, which is funded by UK aid from the UK Government for the benefit of developing countries (grant 5242). The views expressed in this publication do not necessarily reflect UK government policy.

Conflicts of interest. None.

1. Grobler L, Nagpal S, Sudarsanam TD, Sinclair D. Nutritional supplements for people being treated for active tuberculosis. Cochrane Database Syst Rev 2016, Issue 6. Art. No.: CD006086. https://doi. org/10.1002/14651858.CD006086.pub4 2. Katona P, Katona-Apte J. The interaction between nutrition and infection. Clin Infect Dis 2008;46(10):1582-1588. https://doi.org/10.1086/587658 3. Cegielski JP, McMurray DN. The relationship between malnutrition and tuberculosis, evidence from studies in humans and experimental animals. Int J Tuberc Lung Dis 2004;8(3):286-298. http://www. ingentaconnect.com/content/iuatld/ijtld/2004/00000008/00000003/art00004 (accessed 1 December 2017).

4. Macallan DC. Malnutrition in tuberculosis. Diagn Microbiol Infect Dis 1999;34(2):153-157. https:// doi.org/10.1016/S0732-8893(99)00007-3 5. World Health Organization. Guideline: Nutritional Care and Support for Patients with Tuberculosis.

Geneva: WHO, 2013. http://www.who.int/nutrition/publications/guidelines/nutcare_support_ patients_with_tb/en/ (accessed 19 July 2017).

6. Institute of Medicine, The National Academies of Science, Engineering and Medicine, Health and Medicine Division. Dietary reference intakes table and application. http://www.nationalacademies. org/hmd/Activities/Nutrition/SummaryDRIs/DRI-Tables.aspx (accessed 16 September 2016).

7. Statistics South Africa. Mortality and Causes of Death in South Africa, 2015: Findings from Death Notification. Pretoria: Stats SA, 2017. http://www.statssa.gov.za/?page_ id=1854&PPN=P0309.3&SCH=6987 (accessed 17 July 2017).

8. World Health Organization. Global Tuberculosis Report 2016. Geneva: WHO, 2016. http://www.who. int/tb/publications/global_report/en/ (accessed 19 July 2017).

9. Nieburg P, Angelo S. Tuberculosis in the Age of Drug Resistance and HIV – Lessons from South Africa’s Experience. A Report of the CSIS Global Health Policy Center, September 2015. Washington, DC: Centre for Strategic and International Studies, 2015.

10. Massyn N, Peer N, English R, Padarath A, Barron P, Day C, eds. District Health Barometer 2015/16.

Durban: Health Systems Trust, 2016.

11. Lombardo CC, Swart R, Visser ME. The nutritional status of patients with tuberculosis in comparison with tuberculosis-free contacts in Delft, Western Cape. S Afr J Clin Nutr 2012;25(4):180-185. http:// www.sajcn.co.za/index.php/SAJCN/article/view/594 (accessed 1 December 2017).

12. South African National Tuberculosis Association (SANTA). Tuberculosis. http://www.santa.org.za/tbincidence-and prevalence.html (accessed 1 September 2017).

13. Chee CB, Sester M, Zhang W, Lange C. Diagnosis and treatment of latent infection with Mycobacterium tuberculosis. Respirology 2013;18(2):205-216. https://doi.org/10.1111/resp.12002 14. Shisana O, Labadarios D, Rehle T, et al. South African National Health and Nutrition Examination Survey (SANHANES-1): 2014 edition. Cape Town: HSRC Press, 2014.

15. Foster N, Vassall A, Cleary S, Cunnama L, Churchyard G, Sinanovic E. The economic burden of TB diagnosis and treatment in South Africa. Soc Sci Med 2014;130(April):42-50. https://doi.org/10.1016/j. socscimed.2015.01.046 16. Hargreaves JR, Boccia D, Evans CA, Adato, M, Petticrew M, Porter JDH. The social determinants of tuberculosis: From evidence to action. Am J Public Health 2011;11(4):654-662. https://doi. org/10.2105/AJPH.2010.199505

Accepted 7 September 2017.

January 2018, Print edition

This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

IN PRACTICE

MEDICINE AND THE LAW

‘Covering doctors’ standing in for unavailable colleagues: What is the legal position?

D J McQuoid-Mason, BComm, LLB, LLM, PhD Centre for Socio-Legal Studies, University of KwaZulu-Natal, Durban Corresponding author: D J McQuoid-Mason (mcquoidm@ukzn.ac.za)

Covering doctors are those who stand in for colleagues when the latter are unable to deal with their patients. Covering doctors who begin to issue telephonic instructions to nurses or other healthcare practitioners regarding the treatment of the patients they are covering are in the same position as any other doctors treating patients. They cannot argue that the patients they are covering only become their patients once an emergency or crisis occurs or when they see the patients for the first time, and that prior to that their function is merely to monitor the patient’s progress. They also cannot rely on telephone instructions for long periods of time when the patient’s health may be in danger, without seeing the patient. However, if covering doctors are found to be negligent they can still escape liability if the plaintiff cannot prove a causal link between their negligence and the harm that resulted ‘beyond a reasonable doubt’.

S Afr Med J 2018;108(1):19-21. DOI:10.7196/SAMJ.2018.v108i1.12749

A recent court case involving the duties of covering doctors who issue telephonic instructions to nurses, while standing in for colleagues who are unable to deal with their patients, involved the following facts:[1] A covering doctor is asked to look after a pregnant patient who is about to give birth to her first child, because her obstetriciangynaecologist is not available. He is contacted telephonically by the midwife on duty and given information concerning the patient’s condition and progress. There are some early indications that the birth may not be straightforward, but these do not manifest again until a few hours later. The covering doctor continues to receive telephonic information from the nurses and issues instructions to them without seeing the patient. The nurses negligently fail to inform the doctor of two further complications experienced by the patient. When he is informed that the patient is fully dilated the covering doctor arrives at the hospital, 11.5 hours after he first issued telephonic instructions to the nursing staff. He then discovers that the baby is in distress and needs to be delivered urgently. The nurses negligently cause further delays in the birth of the child. Eventually, the baby is born, but had been deprived of oxygen during labour and is later found to suffer from cerebral palsy.

The hospital accepts liability for the negligence of its nurses towards the patient and the child, but seeks a contribution towards the damages from the covering doctor as a joint wrongdoer. The covering doctor denies liability on the basis that he owed the patient no duty of care until he arrived at the hospital. Until then there was no doctor-patient relationship between them. He also argues that he was merely covering for the patient’s obstetrician in the event of an emergency or imminent delivery. He further argues that he did not intervene earlier because he did not wish to interfere with the relationship between the patient and her obstetrician, as this would cause her anxiety. However, he concedes that if the patient had been his from the beginning he would have visited her much earlier to check her condition. Finally, the covering doctor argues that even if he was negligent, there was no causal link between

22

his negligence and the resulting harm to the baby. The court rejects the covering doctor’s arguments that the doctor-patient relationship only came into effect when he arrived at the hospital.

It also rejects the contention that he was only obliged to cover for an emergency or imminent delivery. The court finds that he had not exercised the requisite skill and care expected of a covering doctor in his position. As a result, he is guilty of negligence.

However, the court finds that the hospital did not establish ‘on a balance of probabilities’ that the covering doctor’s negligence caused the harm suffered by the baby, and the case against him was dismissed.[1] This case (the S case) raises the following questions: (i) When does a person become a patient? (ii) What are the duties of covering doctors? (iii) When can doctors use telephonic instructions without seeing a patient? (iv) What information has to be placed before the court to establish a causal link between a doctor’s negligence and the harm to the patient?

When does a person become a patient?

It is well established that usually a person becomes a patient either through a contractual arrangement[2] or as a result of the law of delict imposing a duty on doctors not to treat their patients negligently.[1] In terms of contract, a doctor ‘undertakes to treat a patient with the required skill and care, and a patient undertakes to pay their fees’.[1] Under the law of delict, once a doctor begins to provide care to a person or instructs other healthcare personnel on how to treat such a person, the doctor is regarded as having entered in a doctor-patient relationship through mere operation of the law.[2] In such instances, the law imposes a duty on doctors to treat patients with the same degree of skill and care as a reasonably competent practitioner in that field of practice – independent of any contractual relationship.[2] Failure to exercise such skill and care amounts to negligence on the part of the doctor. As indicated, such a duty also exists when there is a contract between the doctor and the patient.

January 2018, Print edition

IN PRACTICE

The law of delict imposes such a duty on doctors because it is not always possible for patients to enter into contracts with their doctors, and doctors are still required to treat such patients properly. For instance, where patients are unconscious, doctors are required to treat such patients with the necessary skill and care once they assume responsibility for treating them.[1] Doctors who fail to exercise the requisite skill and care can be sued either in contract or in delict because they have a contractual obligation not to be negligent, but also ‘a legal duty, independent of the contract, not to be negligent’.[1] A person therefore becomes a patient when a doctor agrees to treat them or when a doctor begins treating them – either personally or by issuing instructions to healthcare providers concerning their treatment. The court in the S case therefore concluded that the covering doctor ‘owed the patient a legal duty as a specialist obstetrician from the time that he was notified of her admission and started to manage her treatment, and he was negligent in not examining her earlier and verifying for himself that everything was in order’.[1]

What are the duties of covering doctors?

Covering doctors are those who stand in for colleagues when the latter are unable to deal with their patients, and have the same duties as ordinary doctors.[1] Once covering doctors begin to issue telephonic instructions to nurses or other healthcare practitioners regarding the treatment of the patients they are covering, they are in the same position as any other doctors treating patients.[1] They cannot argue that the patients they are covering only become their patients once an emergency or crisis occurs or when they see the patients for the first time. Covering doctors also cannot maintain that prior to such emergency or crisis their function is merely to monitor the patient’s progress – as was alleged in the S case. This is especially so when the covering doctor knows, or should know, that at the time the original treating doctor is unable to manage the patient.[1] In the S case the court pointed out that ‘[t]he process of labour is inherently dangerous and calls for expert monitoring and management of both mother and foetus’. It rejected ‘the implication’ that ‘during the process of labour there was no obstetrician who had the responsibility of managing the patient and her unborn child’, and that the covering doctor ‘was not obliged or willing to do anything until an emergency developed or the delivery was imminent’.[1] The court also rejected the argument that although the covering doctor would normally go and see his patient within 3 or 4 hours of admission, he refrained from doing so in order not to interfere with the original treating doctor’s relationship with his patient as it might ‘cause anxiety on her part’. It also rejected the doctor’s contention that he did not interfere because ‘he did not want there to be a discrepancy between his management of the patient’ and that of the original treating doctor.[1] The court pointed out that ‘no reasonable obstetrician will leave the patient entirely in the hands of the nursing staff until the baby is about to be born’, and held that the covering doctor was negligent in this respect.[1]

When can doctors use telephonic instructions without seeing a patient?

It has been suggested elsewhere that it may not be appropriate to issue telephonic instructions where the patient is not previously known to the doctor or when the assessment may be helped by examination of the patient.[3] Generally, doctors are expected to examine their patients before issuing telephonic instructions to

23

nurses. In emergencies, however, or when they are aware of the health status of their patients, doctors may be justified in issuing telephonic instructions to nurses without examining the patient.[3] In the S case, the covering doctor issued telephonic instructions to the nursing staff without seeing the patient for over 11 hours.

Expert witnesses stated that as it was a first pregnancy the covering doctor should have gone to the hospital ‘within an hour or so after this call and verify for himself that everything was in order’. It was also necessary for him ‘to satisfy himself that the information given to him by the nursing staff was correct’. An ‘early visit to see the patient would have alerted [the covering doctor] to the high head, which made her a high risk patient which required a frequent and vigilant observation’. [1] The court stated that ‘an obstetrician who has not seen a patient who was admitted eight and a half hours earlier, cannot sit at home and judge the situation simply on what the nursing staff reports telephonically about the CTG [cardiotocograph] readings’. The covering doctor accepted this and conceded that ‘if the patient had been his he would have gone to check for himself ’. He did not do so because he regarded the patient as the original treating doctor’s patient.[1] As a result, the covering doctor’s conduct ‘was a serious lapse which fell short of the degree of care and expertise that was expected of him as a specialist obstetrician’, and he was found liable for negligence.[1] Doctors are expected to examine their patients before issuing telephonic instructions to nurses – except in emergencies or when they know the patient’s health history.[3] In such situations the court will decide whether the doctor concerned acted reasonably. The test used by the court is whether the doctor exercised the same degree of skill and care as a reasonably competent practitioner in their branch of the profession.[3] In the S case, the court found that the covering doctor’s conduct ‘fell short of the degree of care and expertise that was expected of him as a specialist obstetrician’.[1]

What information has to be placed before the court to establish a causal link between a doctor’s negligence and the harm to the patient?

In the S case, the court was faced with a situation where the expert witnesses could not say whether the baby would have escaped birth damage had it been delivered 2 hours earlier – although in a joint minute they stated that they thought that the damage may have occurred an hour or shortly before the covering doctor arrived to visit the patient. However, no reasons were given for their conclusion regarding the timing. One of the witnesses conceded that ‘it is almost impossible to estimate how long it takes’ because it ‘depends on the degree of hypoxia’.[1] The judge pointed out that ‘a court cannot simply accept the say-so of an expert who expresses an opinion on a matter within his field of expertise’ and ‘will have regard to whether the opinion appears to be reasonable and logical and what the reasons for it are’.[4] ‘In this case the opinion expressed in the joint minute … was not supported by reasons and appears to be no more than an estimate’.[1] Therefore the plaintiffs had not proved ‘on a balance of probabilities’ that if the covering doctor had gone to see the patient when a reasonable obstetrician would have, the baby would not have suffered from cerebral palsy.[1]

Conclusion

The S case discusses for the first time what is expected of a covering doctor in terms of managing a patient for another doctor, and leads to the following conclusions:

January 2018, Print edition

IN PRACTICE

• Covering doctors should treat the patient they are covering in the same manner as they would treat their own patient.

• Covering doctors become legally responsible for such a patient from the moment they agree to manage the patient’s treatment.

• Covering doctors cannot argue that the patient they are covering only becomes their patient when they see the patient for the first time.

• Covering doctors cannot argue that their function is merely to monitor the patient’s progress and that the person only becomes their patient once an emergency or crisis occurs.

• Covering doctors cannot judge the patient’s condition solely on what the nursing staff report telephonically.

• Even if the court finds that a covering doctor’s conduct was wrongful and negligent, the doctor will only be liable for damages if the plaintiff proves ‘on a balance of probabilities’ that the doctor’s act or omission caused the harm that resulted.

Acknowledgements. None.

Author contributions. Sole author.

Funding. None.

Conflicts of interest. None.

1. S v Life Healthcare Group (Pty) Ltd (10227/2014) [2017] ZAKZDHC 12 (20 March 2017). http://www. saflii.org/za/cases/ZAKDHC/2017/12.html (accessed 12 July 2017).

2. Correira v Berwind 1986 (4) SA 60 (ZH).

3. McQuoid-Mason D. When may doctors give nurses telephonic instructions? S Afr Med J 2016;106(8):787-788. https://doi.org/10.7196/SAMJ.2016.v106i8.10830 4. See also Michael v Linksfield Park Clinic (Pty) Ltd 2001 (3) SA 1188 (SCA).

Accepted 25 August 2017.

CLINICAL UPDATE This open-access article is distributed under CC-BY-NC 4.0.

A cool ECG S Lahri, MB ChB, FCEM (SA)

Khayelitsha Hospital, Cape Town, South Africa Corresponding author: S Lahri (slahri7@gmail.com)

The electrocardiographic changes of hypothermia are discussed in this case of a man who was brought to an emergency centre with altered mental status. The main ECG signs are a shivering artefact baseline, J waves, and PR-, QRS- and QT-interval prolongation.

S Afr Med J 2018;108(1):22. DOI:10.7196/SAMJ.2018.v108i1.12795

A 35-year-old man was brought to an emergency centre by emergency medical services after being ‘found down’ at the side of the road in the middle of the night. He was unable to provide a history at the time and was confused. His blood glucose level was 6 mmol/L and his blood pressure 90/60 mmHg. His core body temperature was measured at 28oC. His electrocardiograph is shown in Fig. 1.

The ECG shows a bradycardia with shivering artefact and markedly large J (Osborn) waves. Pathophysiologically, J (Osborn) waves are thought to be caused by differences in action potential characteristics between the epicardial and endocardial layers of the heart.[1] They can also be observed in conditions such as benign early repolarisation or hypercalcaemia, in patients with a pericardial effusion of acute onset, and in patients with other intracranial pathology not limited to injury, such as a subarachnoid haemorrhage. The shivering artefact is not specific to hypothermia and may be seen in other patients who may have a tremor.

Other electrocardiographic manifestations of hypothermia include PR-, QRS- and QT-interval prolongation, as well as atrial and ventricular dysrhythmias. The ECG in hypothermia may also mimic a myocardial infarction and conceal the typical ECG findings in hyperkalaemia.

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Fig. 1. Electrocardiograph showing a bradycardia with shivering artefact and markedly large J (Osborn) waves.

Acknowledgements. None.

Author contributions. Sole author.

Funding. None.

Conflicts of interest. None.

1. Antzelevitch C, Yan GX, Ackerman MJ, et al. J‑wave syndromes expert consensus conference report: Emerging concepts and gaps in knowledge. J Arrhythm 2016;32(5):315-339. https://doi. org/10.1016%2Fj.joa.2016.07.002

Accepted 12 September 2017.

January 2018, Print edition

This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

RESEARCH

South African clinical practice guidelines: A landscape analysis M Wilkinson,1 BPharm, MPH; T Wilkinson,1 BPharm, MSc (Health Economics); T Kredo,2 MB ChB, MMed (Pharm), Dip HIV Man; K MacQuilkan,1 MPH; C Mudara,1 BSc Hons; A Winch,1 BSc Hons, MSc (Health Economics); Y Pillay,3 PhD; K J Hofman,1 MB BCh, FAAP PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa Cochrane South Africa, South African Medical Research Council, Cape Town, South Africa 3 National Department of Health, Pretoria, South Africa 1 2

Corresponding author: K J Hofman (karen.hofman@wits.ac.za) Background. South Africa (SA) is in the process of implementing National Health Insurance (NHI), which will require co-ordination of health provision across sectors and levels of care. Clinical practice guidelines (CPGs) are tools for standardising and implementing care, and are intended to influence clinical decision-making with consequences for patient outcomes, health system costs and resource use. Under NHI, CPGs will be used to guide the provision of healthcare for South Africans. It is therefore important to explore the current landscape of CPG developers and development.

Objective. To identify and describe all CPGs available in the public domain produced by SA developers for the SA context.

Methods. We conducted a cross-sectional evaluation using a two-part search process: an iterative, electronic search of grey literature and relevant websites (161 websites searched), and a systematic search for peer-reviewed literature (PubMed) after publication year 2000. CPGs were identified, and data were extracted and categorised by two independent reviewers. Any discrepancies were referred to a third reviewer.

Data extracted included a description of the developer, condition, and reporting of items associated with CPG quality.

Results. A search conducted in May 2017 identified 285 CPGs published after January 2000. Of those, 171 had been developed in the past 5 years. Developers included the national and provincial departments of health (DoH), professional societies and associations, ad hoc collaborations of clinicians, and the Council for Medical Schemes. Topics varied by developer; DoH CPGs focused on high-burden conditions (HIV/AIDS, tuberculosis and malaria), and other developers focused on non-communicable diseases. A conflict of interest statement was included in 23% of CPGs developed by societies or clinicians, compared with 4% of DoH CPGs. Conclusion. Accessing CPGs was challenging and required extensive searching. SA has many contributors to CPG development from the public and private sectors and across disciplines, but there is no formal co-ordination or prioritisation of topics for CPG development.

Different versions of the CPGs were identified and key quality items were poorly reported, potentially affecting the usability and credibility of those available. There was substantial variation in CPG comprehensiveness and methodological approach. Establishing a national CPG co-ordinating unit responsible for developing standards for CPG development along with clinical quality standards, and supporting highquality CPG development, is one essential step for moving forward with NHI. S Afr Med J 2018;108(1):23-27. DOI:10.7196/SAMJ.2018.v108i1.12825

Decisions made by healthcare professionals on the prevention and management of ill health are at the core of an effective, efficient and trusted health system. Clinical practice guidelines (CPGs) can have a substantial influence on clinical decision-making, with consequences for health outcomes, patients’ access to care, health system costs and resource use.

The white paper on National Health Insurance (NHI) policy for South Africa (SA)[1] released in June 2017 suggests that detailed treatment guidelines, based on the best available clinical and costeffectiveness evidence, will be used to guide the delivery of health services under NHI. Under NHI, standard treatment guidelines (STGs) developed by the National Department of Health (NDoH) for primary, secondary, tertiary and quaternary levels of care will play an integral role in determining access to and quality of care, and additional treatment guidelines will be used or developed where gaps in the therapeutic areas covered by the STGs are identified. In addition, the NHI policy states that ‘efforts will be put into place to ensure that the general public is provided with the relevant information to support access and ensure empowerment regarding these guidelines’.[1]

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However, no central, accessible database of CPGs developed in SA currently exists.[2] The CPG mapping project described in this article aimed to address this gap in knowledge of up-to-date guidelines, and to assist the NDoH by: (i) improving the current understanding of the CPG landscape in SA; and (ii) providing a starting point for a co-ordinated CPG review and development programme under NHI. The primary objective of this project was to identify and collate all publicly available CPGs and, where available, to provide the details of the developers/commissioners of such guidance.

For the purpose of this research, and the intended NHI-focused requirements of guideline production in SA, we defined CPGs in their broadest sense as documentation that advises on the clinical management (including screening, prevention, diagnosis, treatment, rehabilitation and palliation) of individuals in a particular setting for a particular disease area/condition. The use of a more restrictive definition of CPGs, for example the Institute of Medicine’s 2011 definition that includes a requirement that CPG statements/ recommendations ‘are informed by a systematic review of evidence and an assessment of the benefits and harms of alternative care options’,[3] was not considered practical or appropriate, as the

January 2018, Print edition

RESEARCH

We conducted a cross-sectional evaluation of publicly available CPGs through an iterative, electronic search of grey literature and relevant websites, as well as a systematic search for peer-reviewed literature.

Documentation relevant to the clinical management of individuals in SA (see full definition above) produced and published after 1 January 2000 in English was included in the CPG database. Only one version or presentation of any CPG was included, and non-clinical guidelines describing ethical, legal, organisational or infrastructure factors for healthcare were excluded. Continuing medical or professional education articles and academic textbooks were also excluded.

The electronic search of grey literature and relevant websites (national and provincial departments of health, professional societies, associations, universities) was conducted between 1 September 2016 and 15 November 2016, and repeated between 22 and 25 May 2017. The list of society and association websites searched was informed by a separate Society, Association and Council Mapping Project,[5] as well as the list provided on the Health Professions Council of South Africa’s website (http://www.hpcsa. co.za/Links). In the initial search, terms including ‘clinical guideline’, ‘treatment protocol’ and ‘recommendations’ were used to identify websites and grey-literature sources. This was followed by a pragmatic, within-site strategy to ensure that the search was comprehensive and that sources were fully examined.

The systematic search for peer-reviewed literature was conducted in PubMed and the South African Medical Journal (SAMJ) on 18 October 2016, and updated by the first reviewer and repeated by the second reviewer on 12 May 2017. Articles published between 1 January 2000 and 12 May 2017 were identified using search terms that included ‘South Africa’ and variations of the following keywords: guideline; clinical management; treatment; protocol; recommend; algorithm; clinical practice guideline; decision support;

Results

In total, 285 CPGs published online after the year 2000 were retrieved. Fig. 2 provides an overview of the CPGs developed and published between January 2000 and May 2017 in SA and the broad therapeutic areas they relate to. Most CPGs provide guidance on non-communicable diseases (NCDs) (46%, 130/285), maternal, neonatal and child health (MNCH) (21%, 59/285) and HIV/AIDS, tuberculosis (TB) or malaria (12%, 35/285). We found that 171/285 CPGs

Identification

Methods

Records identified through: Database searching, n=1 475 PubMed, n=234 SAMJ, n=1 241

Screening

To identify and describe all CPGs available in the public domain, produced by SA developers for the SA context.

Records screened (title/abstract), n=1 475

Eligibility

Objective

managed care; diagnoses; preventive; public health; and health service. Two reviewers independently reviewed the abstracts against the prespecified inclusion and exclusion criteria, with any disagreement discussed and referred to a third reviewer if not resolved. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart for the literature search is presented in Fig. 1.

Two independent reviewers extracted and categorised relevant information from the CPGs, with any disagreement discussed and referred to a third reviewer if not resolved.

Information extracted included a description of the developer, condition and reporting of items associated with quality CPGs (e.g. declarations of conflicts of interest, funding sources, references or evidence base, and stakeholder involvement).

Full-text articles assessed for eligibility, n=58

Included

CPG landscape in SA is fragmented and not currently standardised, with limited technical skills available.[4] As a result, the CPGs included in the database vary considerably in terms of their development methods, quality and comprehensiveness.

Database search: Articles included, n=58

(60%) were developed after 1 January 2012.

The apparent increase in CPG development since 2000 (Fig. 2) could in part be explained by the fact that only the latest version of any CPG was included in the database.

CPGs were categorised based on their scope as: • Covering multiple conditions and populations. Short guidelines/algorithms covering multiple unrelated conditions or interventions.

• Detailed. Guidelines that include the following information regarding the condition or intervention: general information, symptoms and presentation of disease, diagnosis, and management/treatment recommendations.

• Position statement. Short (usually 1 - 3 pages) recommendations or statements where the content is mainly based on the collective views of the organisation and not necessarily supported by analysis or synthesis of local evidence.

• Poster/algorithm. Algorithm or poster on the management of a particular condition or use of an intervention.

We identified five groups of CPG developers: (i) the NDoH; (ii) provincial departments of health; (iii) societies or associations; (iv) collaborations of clinicians and academics; and (v) the Council for Medical Schemes (CMS).

Eligible documents identified through search of 161 websites, n=227

Records excluded, n=1 417

Fig. 1. PRISMA flow diagram of clinical practice guidelines (May 2017).

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January 2018, Print edition

Website search: Documents included, n=227

RESEARCH

CPG developer types and categorisation are shown in Table 1. CPGs in each category vary in development methodology, length, target audience and scope (guidance on an individual intervention v. management of a condition).

Department of Health CPGs

Nine NDoH CPGs ‘covering multiple conditions and populations’ were identified: (i) three STGs for SA (primary care level, and hospital level for adults and children); (ii) Tertiary and Quaternary Level Essential Medicines Recommendations, 2016; (iii) Integrated Management of Childhood Illness (IMCI), 2014; (iv) Adult Primary Care guide, 2016/2017; (v) Newborn Care Charts, 2014 (these were developed by the Limpopo Initiative for Newborn Care, a joint initiative of the Department of Paediatrics and Child Health at the University of Limpopo and the Limpopo Department of Health, but have been categorised as an NDoH guideline owing to their national implementation and use); (vi) Guidelines for Neonatal Care, 2008; and (vii) the STG for common mental

health conditions. Outdated versions (when newer versions of the CPGs are available) of the STGs, the IMCI and the Adult Primary Care guide (previously named Primary Care 101) were found on multiple websites, including those of the NDoH, universities, provincial DoHs and professional societies and associations.

Most of the ‘detailed’ NDoH guidelines (n=45) were for HIV/AIDS, TB or malaria (28%, 15/45), followed by CPGs for MNCH (20%, 9/45), NCDs (20%, 9/45) and communicable diseases and infections (19%, 8/45). Some of the NDoH CPGs were adaptations of World Health Organization (WHO) guidelines, and many were developed in collaboration with, or with financial or technical support from, international development aid agencies such as the United Nations Children’s Fund (UNICEF), United States Agency for International Development (USAID), United Nations Population Fund (UNFPA) and Joint United Nations Programme on HIV/AIDS (UNAIDS).

Only three of the ‘detailed’ CPGs by provincial DoHs were produced in the past

50

CPGs, n

40 30 20 10 0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Year Communicable disease and infections MNCH Trauma and emergency*

HIV/AIDS, TB and malaria Multiple (adults)†

Lifestyle NCD

Fig. 2. CPGs produced in SA between January 2000 and May 2017 by broad therapeutic area (N=285).

(CPGs = clinical practice guidelines; SA = South Africa; TB = tuberculosis; MNCH = maternal, neonatal, and child health; NCD = non-communicable disease. *One CPG on the use of blood products in SA has been included under the ‘Trauma and emergency’ field; however, this document includes guidance covering more than one broad therapeutic area for both adults and children. †The ‘Multiple (adults)’ field includes four documents that consist of a package of adult-focused CPGs covering more than one broad therapeutic area. Paediatric CPGs covering more than one broad therapeutic area are included under the MNCH field.)

5 years. Two of these were developed by the KwaZulu-Natal DoH for preventing and managing malnutrition, and one by the Western Cape DoH on antimicrobial management. The KwaZulu-Natal DoH also produced protocols for management of mental health conditions, and two paediatric CPGs ‘covering multiple conditions and populations’ in 2007.

Society or association CPGs

A total of 156 CPGs developed by 63 societies or associations were identified, with the majority of organisations (54%, 34/63) producing or contributing to more than one CPG. Some of the CPGs were adaptations of guidelines developed by professional societies outside SA. The majority of the CPGs were ‘detailed’ (67%, 104/156) and were mostly produced after 1 January 2012 (62%, 96/156). Sixty percent (94/156) of the CPGs advised on the management of NCDs, with many referring to musculoskeletal (14/94), cardiovascular (13/94) and gastrointestinal (12/94) conditions.

None of the position statements identified (n=41) were published in a peerreviewed journal, and they were mainly developed by five societies: the South African Spine Society (n=12), the South African Vitreoretinal Society (n=6), the South African Gastroenterology Society (n=4), the South African Society of Cardiovascular Intervention (n=4) and the South African Society of Obstetricians and Gynaecologists (n=4).

Ten poster/algorithm guidelines were included in the CPG database, of which nine were produced by the Resuscitation Council of South Africa.

CPGs produced by clinicians and academics

Thirty-seven CPGs containing no formal statement linking their development to the DoH or a specific society or association were included as clinician/academic-produced CPGs. The majority of the CPGs were for MNCH (40%, 15/37), followed by NCDs

Table 1. Overview of clinical practice guidelines in South Africa by developer type

Multiple conditions and populations Detailed Position statement Poster/algorithm Total

National Department of Health, n 9 45 2 3 59

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Provincial department of health, n 3 10 1 4 18

Society/ association, n 1 104 41 10 156

January 2018, Print edition

Clinicians/ academics, n 0 37 0 0 37

Council for Medical Schemes, n 1 14 0 0 15

Total, N 14 210 44 17 285

RESEARCH

Table 2. Summary of findings: Items associated with good-quality CPGs

Funding statement

Conflict of interest statements, % References available, % Description of stakeholder consultation process, %

National Provincial Department of department of Health (n=59) health (n=18) Funding source not stated* (81%) or unclear† (3%) n=1 stated None stated pharmaceutical pharmaceutical industry industry involvement involvement

0 54 32

17 28 28

Societies / associations (n=156) Funding source not stated* (73%) or unclear† (2%) 22% declared pharmaceutical industry involvement 21 74 26

Clinicians and academics (n=37) Funding not stated* (59%) or unclear† (5%) 32% declared pharmaceutical industry involvement

Council for Medical Schemes (n=15) Not stated (100%)

30 100 30

0 93 0

CPG = clinical practice guideline. *A CPG funding source was categorised as ‘not stated’ if there was no explicit statement in that regard. There were cases where the involvement of international partners or the pharmaceutical industry in CPG development was stated, but the nature of their involvement (human resources or financial) was not declared. † A CPG funding source was categorised as ‘unclear’ if the funding source was not stated, but a commercial advertisement or logo of a pharmaceutical company appeared in the CPG.

(32%, 12/37), other communicable diseases and infections (14%, 5/37) and HIV/AIDS, TB and malaria (8%, 3/37).

Most (33/37) of the CPGs were published in the SAMJ, with the rest available on journal and university websites: African Journals Online (AJOL) (n=1), the Journal of Endocrinology, Metabolism and Diabetes of South Africa (JEMDSA) (n=1), the University of KwaZuluNatal (n=1) and the University of Cape Town (n=1).

Council for Medical Schemes CPGs

Fifteen CPGs developed by the CMS were identified. These consist of one CPG ‘covering multiple conditions and populations’, which contains the algorithms specifying the minimum standards required (under Prescribed Minimum Benefits (PMB)) in the management of the 25 chronic conditions on the Chronic Diseases List, and 14 ‘detailed’ Diagnosis Treatment Pair CPGs published on the CMS website as a result of the PMB Definition Project.[6] The Diagnosis Treatment Pair CPGs all relate to cancer, cardiovascular disease and organ transplants.

Key quality criteria of included CPGs

Sixteen percent (47/285) of CPGs contained a statement regarding the authors’ conflicts of interest, and 23% (65/285) explicitly declared the funding source. The methods for stakeholder consultation as part of the CPG development process were described in 26% (75/285) of CPGs, and 71% (203/285) included references. A brief summary of the findings by developer type is presented in Table 2.

Seventeen of the 59 NDoH CPGs (29%) stated the involvement of international development partners (e.g. WHO, UNICEF, USAID) in the CPG development process. These CPGs had a strong focus on MNCH (n=8) and the management of HIV/AIDS, TB and malaria (n=6). Pharmaceutical industry involvement was declared or assumed (based on pharmaceutical industry advertisements directly within the CPG) in the development of 54 CPGs, of which two-thirds (36/54) were focused on NCDs.

Discussion

CPGs developed in SA vary considerably in terms of their topics, scope, development methods, funding streams and accessibility.

This variability is not surprising considering the number and diversity of CPG developers, and the lack of formal co-ordination or standardisation between them with regard to CPG topic selection and prioritisation, development methodology and reporting principles.

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The individual topic selection/prioritisation process followed by the developers was generally not reported, and therapeutic topics vary considerably. The majority of DoH CPGs were focused on high-burden conditions such as HIV/AIDS, TB and malaria, while CPGs from other developers were more likely to provide guidance on NCDs. One possible explanation for this variation in CPG topics is the difference in the type of conditions treated by public and private healthcare providers, and as a result the types of CPGs they need or are likely to access. The effect of the aims and objectives of funding organisations (e.g. pharmaceutical industry, international development partners) on CPG topic selection was not considered as part of this mapping project, but may warrant future research to ensure that CPG topics are prioritised and selected based on the needs of the population and the healthcare community.

CPGs identified in the public domain were often out of date (with more up-to-date versions available elsewhere) and key quality items we extracted were poorly reported, potentially impacting on the usability and credibility of those available.

Accessing CPGs was challenging, as no central database of CPGs currently exists. CPGs can be submitted to the SAMJ for publication, but no formal ‘clinical guidelines’ were published in the period between the introduction of the AGREE II assessment to the SAMJ critical appraisal process for clinical guidelines in 2014[7] and May 2017. The systematic search for CPGs in the SAMJ retrieved 87 Continuing Medical Education (CME) articles published between 2014 and May 2017 that contained the features of a CPG. However, these articles were not subject to a peer review process prior to publication[8] and were not included in the CPG database. Some societies, associations, departmental organisations and universities publish CPGs on their websites, but in many cases the CPGs were out of date. The Ideal Clinic programme website consistently contained up-to-date versions of most of the core DoH guidelines (https:// www.idealclinic.org.za). The Ideal Clinic programme is an NDoH initiative, started in 2013, with a strong focus on the use of guidelines to support its aim of ‘systematically improving the quality of care provided in Primary Health Care facilities’.[9]

Strengths and limitations of the literature search

A systematic approach to identifying CPGs produced in SA and extracting the relevant data was followed. Detailed inclusion and exclusion criteria were established, based on a clear scope for the literature search. Dual review and data extraction of CPGs, as well

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as a search of grey literature, were conducted to minimise potential selection bias.

Despite the comprehensive search, given the difficulty with identifying CPGs, it is probable that CPGs are missing. Non-Englishlanguage CPGs were excluded, so guidance produced in any of the other official languages in SA will not have been retrieved, and guidelines that were not dated may potentially have been missed.

Key criteria regarding funding and conflicts of interest were extracted, but a robust quality assessment of CPGs was not conducted.

Two prior studies have evaluated the quality of a sample of CPGs in SA using the AGREE II checklist, and consistently found the reporting on several aspects of the methods for CPG development to be of low to moderate quality.[2,10] Further quality appraisal on the full set of CPGs may not provide additional insight.

Conclusions

SA has a diverse CPG-developing community, but the challenges faced by clinicians in accessing up-to-date CPGs and the lack of co-ordination between developers may limit the impact of CPG developers’ efforts to guide and improve the delivery of high-quality patient care.

Developing and maintaining an accessible, up-to-date CPG repository is a practical and useful first step towards improving the availability of CPGs in SA. The 285 CPGs identified through this mapping project provide a starting point for such a repository. In addition to a point of access for clinicians, this CPG database can also be used to inform the planning and determination of service benefits under NHI, and provide information for a clinical guidance gap analysis to identify topic areas where future CPG development will be most beneficial. Useful lessons can be learnt from information technology organisations such as the Open Medicines Project and Essential Medical Guidance (EMGuidance), which are already working collaboratively, developing and maintaining smartphone applications that provide access to the most up-to-date versions of NDoH CPGs (STGs, Tertiary and Quaternary Level Essential Medicines Recommendations, TB and HIV)[11] and some CPGs produced by other SA developers.[12] Stakeholder involvement is a crucial component that needs to be incorporated in all stages of the CPG development process. The South African Medical Association (SAMA) is currently ‘engaging its medical practitioner members to contribute substantively to the development of guidelines, sharing their experience and expertise in the process’. [13] This could potentially improve the credibility and acceptability of CPGs by healthcare professionals across both the private and public sectors, and ultimately result in meaningful changes in clinical practice. Clinical quality standards are useful tools that can be used to further aid and enhance CPG implementation, and evaluate their clinical impact under NHI. Patient involvement in the CPG development process should also be considered, to ensure that patients are involved and empowered in decisions affecting their health.

In addition, the findings from this CPG mapping project and the South African Guidelines Excellence (SAGE) project[4] demonstrate the need for a national, co-ordinating CPG unit that will enable a standardised, co-ordinated and evidence-based approach to CPG

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development. A national co-ordinating body will be essential if CPGs are to inform patient care under NHI, with a likely impact on quality of care. Ideally it will be responsible for developing and upholding key components of CPG production, which includes robust processes for topic selection and prioritisation, development, publication/ implementation and review.

A full list of the CPGs identified is available on the PRICELESS SA website (www.priceless.ac.za).

Acknowledgements. None.

Author contributions. MW led and co-ordinated the CPG mapping project and prepared the first draft of the manuscript. YP and KJH formulated the research concept, determined its scope and advised on its design and presentation. TW and TK provided technical and methodological input to the research methods, data analysis and presentation of the findings.

MW, KM, CM and AW contributed to the CPG review, selection and data extraction processes. All the authors reviewed the first draft of the manuscript and approved the final version to be published.

Funding. This research at PRICELESS SA was supported by the International Decision Support Initiative (IDSI) (http://www.idsihealth. org/) and funded by the Bill and Melinda Gates Foundation (IDSI 2 Contract: NICE 1082). TK’s contribution was funded through the Flagships Awards Project by the South African Medical Research Council (SAMRC-RFA-IFSP-01-2013/ SAGE).

Conflicts of interest. None of the authors declares any conflicts of interest. TK conducts reviews that inform national and international guidelines, co-ordinates and facilitates training on CPG development and implementation, and is principal investigator on the SAGE project.

1. National Department of Health, South Africa. National Health Act, 2003 (Act No. 61 of 2003). National Health Insurance Policy: Towards universal health coverage. Government Gazette No. 40955, 2017.

2. Kredo T, Gerritsen A, van Heerden J, Conway S, Siegfried N. Clinical practice guidelines within the Southern African Development Community: A descriptive study of the quality of guideline development and concordance with best evidence for five priority diseases. Health Res Policy Syst 2012;10:1. https://doi.org/10.1186/1478-4505-10-1 3. Graham R, Mancher M, Wolman D, Greenfield S, Steinberg E. Clinical Practice Guidelines We Can Trust. Washington, DC: Institute of Medicine Committee on Standards for Developing Trustworthy Clinical Practice Guidelines/National Academies Press, 2011:15.

4. South African Guidelines Excellence Project. SAGE Summit Report. Cape Town: SAGE, 2016. http:// www.mrc.ac.za/cochrane/SAGESummitReport.pdf (accessed 18 July 2017).

5. PRICELESS SA, University of Witwatersrand. Societies and Associations Mapping Project.

Johannesburg: PRICELESS SA, 2016.

6. Council for Medical Schemes. Terms of Reference: Prescribed Minimum Benefit (PMB) Definition Project. Pretoria: CMS, 2010. http://www.medicalschemes.com/files/PMB%20Definition%20Project/ PMBDefProject_TOR.pdf (accessed 18 July 2017).

7. Wiseman R, Cohen K, Gray A, et al. AGREE to disagree: Critical appraisal and the publication of practice guidelines. S Afr Med J 2014;104(5):345-346. https://doi.org/10.7196/SAMJ.8215 8. South African Medical Journal. Policies: Peer review process. http://samj.org.za/index.php/samj/ about/editorialPolicies#peerReviewProcess (accessed 18 July 2017).

9. Ideal Clinic South Africa. Home page: What is an ideal clinic? https://www.idealclinic.org.za (accessed 18 July 2017).

10. Machingaidze S, Zani B, Abrams A, et al. Series: Clinical Epidemiology in South Africa. Paper 2: Quality and reporting standards of South African primary care clinical practice guidelines. J Clin Epidemiol 2017;83:31-36. https://doi.org/10.1016/j.jclinepi.2016.09.015 11. Open Medicine Project. Primary Health Care app launch with the South African National Dept of Health. 2015. http://openmedicineproject.org/2015/11/primary-health-care-app-launch-with-thesouth-african-national-dept-of-health/ (accessed 7 June 2017).

12. Essential Medical Guidance. EM Guidance. https://emguidance.com (accessed 7 June 2017).

13. McGee S. Involving Medical Doctors in Clinical Practice Guideline Development. Cape Town: SAGE Matters, 2017:4. http://www.mrc.ac.za/cochrane/sage/June2017.pdf (accessed 18 July 2017).

Accepted 20 September 2017.

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This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

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Opportunities to optimise colistin stewardship in hospitalised patients in South Africa: Results of a multisite utilisation audit A P Messina,1,2 BPharm; A J Brink,3,4 MB BCh, MMed (Clin Micro); G A Richards,5 MB BCh, PhD, FCP (SA), FRCP; S van Vuuren,1 PhD Department of Pharmacy and Pharmacology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa Department of Pharmacy, Netcare Hospitals, Johannesburg, South Africa 3 Department of Clinical Microbiology, Ampath National Laboratory Services, Milpark Hospital, Johannesburg, South Africa 4 Division of Infectious Diseases and HIV Medicine, Department of Medicine, Faculty of Health Sciences, University of Cape Town, South Africa 5 Division of Critical Care, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, and Charlotte Maxeke Johannesburg Academic Hospital, Johannesburg, South Africa 1 2

Corresponding author: S van Vuuren (sandy.vanvuuren@wits.ac.za) Background. Colistin is an old antibiotic that has been reintroduced as salvage therapy in hospitalised patients because it is frequently the only agent active against Gram-negative bacteria. Various guidelines for colistin administration have led to confusion in establishing the appropriate dose, which has potential for adverse consequences including treatment failure or toxicity. The emergence and spread of colistin resistance has been documented in South Africa (SA), but no local information exists on how and why colistin is used in hospitals, and similarly, compliance with current dosing guidelines is unknown.

Objectives. To evaluate the current utilisation of colistin in SA hospitals, in order to identify stewardship opportunities that could enhance the appropriate use of this antibiotic.

Methods. Electronic patient records of adult patients on intravenous (IV) colistin therapy for >72 hours in four private hospitals were retrospectively audited over a 10-month period (1 September 2015 - 30 June 2016). The following data were recorded: patient demographics, culture and susceptibility profiles, diagnosis, and indication for use. Compliance with six colistin process measures was audited: obtaining a culture prior to initiation, administration of a loading dose, administration of the correct loading dose, adjustments to maintenance dose according to renal function, whether colistin was administered in combination with another antibiotic, and whether de-escalation following culture and sensitivity results occurred. Outcome measures included effects on renal function, overall hospital mortality, intensive care unit length of stay (LoS), and hospital LoS. Results. Records of 199 patients on IV colistin were reviewed. There was 99.0% compliance with obtaining a culture prior to antibiotic therapy, 93.5% compliance with prescription of a loading dose, and 98.5% compliance regarding prescription of colistin in combination with another agent. However, overall composite compliance with the six colistin stewardship process measures was 82.0%. Non-compliance related to inappropriate loading and maintenance doses, lack of adjustment according to renal function and lack of de-escalation following culture sensitivity was evident. Significantly shorter durations of treatment were noted in patients who received higher loading doses (p=0.040) and in those who received maintenance doses of 4.5 MU twice daily v. 3 MU three times daily (p=0.0027). In addition, compared with patients who survived, more patients who died received the 3 MU three times daily maintenance dose (p=0.0037; phi coefficient 0.26).

Conclusions. The study identified multiple stewardship opportunities to optimise colistin therapy in hospitalised patients. Urgent implementation of a stewardship bundle to improve colistin utilisation is warranted.

S Afr Med J 2018;108(1):28-32. DOI:10.7196/SAMJ.2018.v108i1.12561

The emergence of life-threatening multidrug-resistant (MDR) bacteria has been widely documented as a global threat to society, because effective antibiotics to treat bacterial infections are rapidly diminishing.[1] A global review of antibiotic consumption revealed that antibiotic utilisation increased by 36% over a 10-year period (2000 - 2010), with the most notable escalation reflected in the carbapenem and polymyxin classes.[2] This trend correlates with the mounting rates of MDR and extensively drug-resistant (XDR) Gramnegative pathogens, which include the carbapenemase-producing Enterobacteriaceae (CPE), which often require the use of older, more toxic drugs such as colistin as last-resort salvage therapy for critically ill patients in hospital settings.[3] Colistin, also known as polymyxin E, is a nephrotoxic and neurotoxic, concentration-dependent bactericidal antibiotic. It became

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accessible for use in the late 1950s, but its use diminished over time as newer, less toxic agents such as the aminoglycosides became available.[4-5] Unfortunately, the current dosing guidelines for colistin, with regard to both administration and dose, are outdated, inaccurate and confusing, as the package insert information has not been revised since its initial launch.[6] This compromises the management of patients with serious Gram-negative infections and potentially increases resistance.[7] Recommendations also differ between the European and American literature, depending on whether the metric system has been adopted or not. Either international units or milligrams of the sodium salt colistimethate (the inactive prodrug) may be used, and to confuse matters further, colistin base activity (CBA) in milligrams may also be used to define the dose.[4,6] Many believe that the appropriate use of colistin is not known, as

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knowledge of its pharmacokinetics (PK) and pharmacodynamics (PD) are incomplete.[8] However, a recent large multicentre PK study involving 215 patients described a novel algorithmic approach for intravenous (IV) colistin dosing, establishing for the first time dosing recommendations based on accurate PK data.[9] Colistin in South Africa (SA) is only authorised in exceptional circumstances following application to and approval from the Medicines Control Council, as stipulated in section 21 of the Medicines and Related Substances Control Act. This process is often associated with delays in drug procurement.[10] Over- or incorrect use of antibiotics can lead to the development of resistance[11] and, while the emergence and spread of colistin resistance, including heteroresistance among CPE (OXA-48 producing Klebsiella pneumoniae) and plasmid-mediated resistance, has recently been documented in SA,[12-14] the degree of compliance with current dosing guidelines is unknown and no local information on why and how colistin is prescribed is available. Colistin hetero-resistance is defined as ‘the emergence of resistance to colistin by a subpopulation from an otherwise susceptible (MIC [minimum inhibitory concentration] of ≤2 mg/liter) population’ that may be related to exposure to suboptimal polymyxin concentrations.[14]

Objectives

The main purpose of this study was to evaluate the current utilisation of colistin in four private sector SA hospitals. We also hoped to identify opportunities to improve the appropriate use of colistin in the future, in an attempt not only to improve outcomes, but to negate or minimise the risk of development of resistance in vivo.

Methods

This multicentre retrospective record review of patients receiving IV colistin treatment was conducted in four private sector SA hospitals, comprising two each in Johannesburg and Pretoria. The necessary approvals for this study were obtained from the individual participating hospitals, and ethical clearance (ref. no. M150404) was granted by the University of the Witwatersrand Human Research Ethics Committee.

Hospital names were kept anonymous for ethical reasons.

Data were collected and captured in the electronic Bluebird system (http://www.intelms.com/) for a 10-month period (1 September 2015 - 30 June 2016). This system integrates laboratory data from the main private laboratories with dispensing data and the patient’s admission master file. This allowed for the identification of patients in each hospital to whom colistin had been dispensed, and for the monitoring of laboratory culture results, drug prescription data, hospital ward movements and overall patient outcomes. The study included adult patients aged >18 years who were prescribed IV colistin for at least 72 hours. Paediatric and neonatal patients and those who received colistin treatment via an alternative route of administration were excluded. Following review of patient records from the Bluebird system, findings were entered onto a spreadsheet using Microsoft Excel version 14 (Microsoft, USA) for statistical analysis and qualitative interpretation.

The following patient information was collected: age, gender, weight (kg), hospital ward location, admission diagnosis, serum creatinine level and estimated glomerular filtration rate (eGFR). The indications for colistin therapy were recorded as follows: empirical therapy (if no evidence of an MDR or XDR Gram-negative organism was found prior to or during the course of treatment), directed therapy (infection with an MDR or XDR organism of known sensitivity) or salvage therapy (failure of an alternative treatment where colistin was used as escalation therapy).

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Process and outcome measures

Audit of colistin process measures included the following: obtaining a culture prior to colistin initiation, prescription of a loading dose, prescription of correct loading and maintenance doses, and adjustments of maintenance doses according to renal function as stipulated by two SA guidelines,[10,15] administration of colistin in combination with another antibiotic, duration of therapy (calculated as number of treatment days), and de-escalation following culture and sensitivity results. First or repeat courses were also documented, and the type of culture specimens, the organisms cultured and the sensitivity profiles were matched to the prescription data. Outcome measures included were effect on renal function, overall hospital mortality, intensive care unit (ICU) length of stay (LoS) and hospital LoS.

Statistical analysis

The relationship between the duration of therapy and other study variables was assessed by the t-test, or one-way analysis of variance (ANOVA) for more than two categories. Where the data did not meet the assumptions of these tests, a non-parametric alternative, the Wilcoxon rank-sum test (or the Kruskal-Wallis test for more than two categories), was used. The χ2 test was used to assess the relationships between patient outcomes and other study variables. Fisher’s exact test was used for 2 × 2 tables or where the requirements for the χ2 test could not be met. Data analysis was carried out using SAS version 9.4 for Windows (SAS Institute, USA). The 5% significance level was used.

Results

A total of 212 patients received IV colistin during the study period.

Of these 13 did so for <72 hours and were therefore excluded.

Table 1 describes the demographics and characteristics of the patients included in the study. The mean age of the patients was 50.9 years (standard deviation (SD) 16.9), range 19 - 93). The most common admission diagnosis was haematological malignancy (37.2%, n=74) followed by trauma (12.1%, n=24) and then bloodstream infection (7.5%, n=15). Laboratory culture identification was undertaken from 197 patients. Blood cultures were the most frequent (54.3%, n=107), Table 1. Demographics and characteristics of the patients studied (N=199) Patients, n (%) Number of patients per hospital Hospital 1 56 (28.1) Hospital 2 22 (11.1) Hospital 3 17 (8.5) Hospital 4 104 (52.3) Distribution of patients according to hospital location General wards 40 (20.1) ICUs 159 (79.9) Gender Male 113 (56.8) Female 86 (43.2) Course of colistin therapy First course 163 (81.9) Repeat course 36 (18.1) Indication for colistin therapy Empirical therapy 63 (31.1) Directed therapy 121 (60.8) Salvage therapy 15 (7.5) ICUs = intensive care units.

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Process measures

As demonstrated in Table 2, there was considerable variability in both the prescribed loading and maintenance doses, as well as in frequency of administration. Non-compliance with SA dosing adjustment recommendations according to renal function is depicted in Table 3, and the audit of compliance with all the colistin process measures is summarised in Table 4.

who received maintenance doses of 4.5 MU IV 12-hourly v. 3 MU IV 8-hourly also had shorter durations of therapy, 8 days v. 12 days, respectively (p=0.0027). The duration of therapy for patients with P. aeruginosa infection (median 12 days, IQR 8 - 23) was significantly longer than for those without (median 9 days, IQR 6 - 15) (p=0.044).

No significant differences were found in the median duration of therapy for patients in the ICU v. the general wards (p=0.41) or between those with positive blood culture samples v. other specimen types (p=0.39). In addition, no difference was noted regarding treatment duration and overall patient outcome (p=0.20).

25 Median duration of treatment (d)

followed by urine (14.7%, n=29), sputum (8.6%, n=17) and tracheal aspirates (8.1%, n=16). The most prevalent organisms necessitating the use of colistin were K. pneumoniae (39.2%, n=78), Pseudomonas aeruginosa (20.1%, n=40) and Acinetobacter baumannii (9.0%, n=18).

Of these, 77.9% (n=106) were resistant to the carbapenems. The most commonly co-administered antibiotics were meropenem (60.7%, n=119) and tigecycline (28.6%, n=56). In 63.8% (n=125), 32.1% (n=63) and 4.1% (n=8) of patients, one, two and three Gram-negative antimicrobial agents, respectively, were prescribed in addition to colistin. The median duration of colistin therapy was 9 days (interquartile range (IQR) 6 - 16, range 3 - 63). Most patients (57.8%, n=115) received a course of therapy of ≤10 days, 13.6% (n=27) a course of 11 - 14 days and 28.6% (n=57) a course of ≥15 days.

20 15 10 5 0 4-6

8-9

11 - 12

Loading dose (MU)

Outcome measures

Durations of treatment were found to be significantly shorter in patients who received higher loading doses (p=0.040) (Fig. 1). Those

Fig. 1. Associations between colistin loading dose and median duration of treatment. The error bars denote the interquartile range.

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Table 2. Prescribed LDs and MDs and frequency of administration of colistin in 90 the study patients (N=199) Patients (N=186), n (%) 3 (1.6) 10 (5.4) 5 (2.7) 45 (24.2) 1 (0.5) 122 (65.6)

MD 1 MU 1.5 MU 2 MU 2.5 MU 3 MU 4.5 MU

LD = loading dose; MD = maintenance dose.

Patients (N=199), 80 n (%) 70 3 (1.5) 60 11 (5.5) 50 40 17 (8.5) 30 2 (1.0) 65 (32.7) 20 10 101 (50.8)

Frequency of administration 6-hourly 8-hourly 12-hourly

Patients in each group, %

LD 4 MU 6 MU 8 MU 9 MU 11 MU 12 MU

0

Died 1 - 1.5 MU

Discharged 2 - 2.5 MU

Table 3. Compliance with recommended adjustments of colistin dosage according to renal function South African Society of Clinical Pharmacy guideline[15] Normal renal function CrCl 40 - 60 mL/min CrCl 10 - 40 mL/min CrCl <10 mL/min Compliance with recommended dosing guidelines for study patients (N=199), n (%) Unknown* Compliant Non-compliant Visser Kift et al. guideline[10] Critically ill or severe sepsis eGFR >60 mL/min eGFR 30 - 60 mL/min eGFR 10 - 30 mL/min eGFR <10 mL/min Compliance with recommended dosing guidelines for study patients (N=199), n (%) Unknown* Compliant Non-compliant

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3 MU

4.5 MU

Loading dose 12 MU, then 3 MU 8-hourly or 4.5 MU 12-hourly 2 MU 12-hourly 2 MU 24-hourly 1.5 MU 36-hourly 58 (29.2) 68 (34.2) 73 (36.7) Loading dose 9 - 12 MU 4.5 MU 12-hourly 3 MU 12-hourly 2 MU 12-hourly 1 MU 12-hourly 3 (1.5) 80 (40.2) 116 (58.3)

CrCl = creatinine clearance; eGFR = estimated glomerular filtration rate. *Contributions to unknown compliance are a result of data not documented on records for variables including weight and eGFR.

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Patients (N=100), n (%) 1 (0.5) 76 (38.2) 122 (61.3)

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Table 4. Compliance with colistin stewardship process measures Median duration of treatment (d)

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20 Process measures Obtaining an appropriate culture prior to commencement of colistin therapy 15 Prescription of a loading dose Prescription of an appropriate loading dose 10 Prescription of appropriate maintenance dosing, including adjustment according to renal insufficiency

Prescription of colistin in combination with another Gram-negative antibiotic De-escalation of colistin therapy

5 0 4-6

*According to the South African Society of Clinical Pharmacy guideline.[15] According to Visser Kift et al.[10]

8-9

To our knowledge this is the first study that has evaluated the current utilisation of colistin across multiple SA hospitals and involving a large sample of patients. As a result, numerous opportunities for improved stewardship were identified. Recent recommendations in response to the emergence and spread of plasmid-mediated colistin resistance include preserving colistin use for definitive treatment based on susceptibility testing, use of PK/PD indicators to ensure appropriate dosing, and use of empirical therapy in selected cases only.[16] Contrary to these recommendations, our study suggests that both loading and maintenance dosing of colistin is variable and inconsistent, with adherence to available local dosing guidelines at best 48.2%. This reveals the extent of uncertainty associated with colistin utilisation in SA hospitals and the very urgent need for education so that our last-resort Gram-negative antibiotic can be preserved for as long as possible. The administration of a colistin loading dose is widely considered to be best practice, as it facilitates the rapid achievement of optimal bactericidal concentrations.[17,18] Although compliance with the recommendation for a loading dose was high (93.5%), the actual loading doses ranged from 4 MU to 12 MU. This demonstrates a lack of understanding regarding the need for appropriate loading doses, which should be in the region of 9 - 12 MU regardless of renal function.[9,19] The findings of our study further emphasise the importance of ensuring optimal dosing as, although Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were not available so that patients could be appropriately

100 90 Patients in each group, %

The effects on renal function in patients who received IV colistin therapy were insignificant. There was no change in median creatinine level after receiving colistin (73 µmol/L, IQR 53 - 110, range 21 - 601 before; 73 µmol/L, IQR 51 - 128, range 20 - 645 after). Similarly, the mean eGFR was 79 mL/min (SD 37, range 8 - 150) before treatment and 79 mL/min (SD 38, range 7 - 150) after treatment. Prior to the commencement of colistin, 5.6% of patients (n=11) were considered to have kidney failure, 7.1% (n=14) to have severe kidney injury, and 66.8% (n=131) to have normal kidney function according to the Kidney Disease Improving Global Outcomes (KDIGO) classification.

The median ICU LoS was 31 days (IQR 15 - 52, range 0 - 152) and the median hospital LoS was 46 days (IQR 25 - 83, range 3 227). The majority of the patients (70.4%, n=140) were discharged, indicating a 29.6% in-hospital mortality rate (n=59). This study found no significant association between patient outcomes and a particular organism, the presence or absence of a bloodstream infection, duration of therapy or loading dose. However, a significant association was found between outcome and the maintenance dose prescribed (p=0.0037; phi coefficient 0.26). Patients who died had received lower prescribed maintenance doses per interval than those who survived (Fig. 2).

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11 - 12

Loading dose (MU)

†

Discussion

Compliance rate (N=199), % (n) 99.0 (197) 93.5 (186) 90.3 (168) 48.2 (68/141)* 40.8 (80/196)† 98.5 (196) 69.9 (58/83)

80 70 60 50 40 30 20 10 0

Died 1 - 1.5 MU

Discharged 2 - 2.5 MU

3 MU

4.5 MU

Fig. 2. Associations between colistin maintenance doses and patient outcome.

matched, higher loading doses appeared to be associated with shorter duration of treatment. Interestingly, there also appeared to be an association with the manner in which the maintenance doses were administered. Although most patients received 9 MU/day, those who received doses of 4.5 MU twice daily also had a shorter duration of therapy and more favourable overall outcomes, which may be due to the concentration-dependent nature of the drug. This is in keeping with the concept that administration of antibiotics according to PK principles and rapid achievement of therapeutic concentrations would result in improved clinical cure.[17,20-21] Combination therapy was prescribed to all but three patients in our study. This practice, including duplicate and sometimes triplicate therapy, is recommended by local guidelines for the treatment of CPE, suggesting that combinations may improve efficacy and minimise the risk of selection of resistant organisms. Studies that have supported combination therapy for CPE have relatively low sample sizes, and concerns remain regarding the increased environmental burden of multiple antibiotic exposure, which may actually increase colonisation rates with resistant organisms and increase the risk of Clostridium difficile infection.[22] One recent study could not demonstrate whether it was combination therapy alone rather than higher dosing that contributed to better patient outcomes, albeit in a small patient study population (N=28).[17] Randomised clinical trials are underway to help establish whether patient outcomes are actually improved with combinations compared with appropriately dosed and administered colistin monotherapy.[17,22] Until these results are available, combination therapy is currently the recommended best practice.

Of concern is the large proportion of patients in our study (31.1%) who received empirical colistin therapy. This could be due to the expectation of increased MDR and XDR infections in the large population of severely immunocompromised haematology patients

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included in the study, for whom colistin may well be appropriate. For 69.9% (n=58) of the eligible patients, therapy was de-escalated to a narrower-spectrum antibiotic following the availability of sensitivity results. Although this is a somewhat low figure, it is in line with other studies indicating that de-escalation is not always possible for many reasons, including the limited number of effective antibiotics available to treat MDR infections, the limited understanding of how to de-escalate, and the fact that the practice has still not been widely accepted in critically ill patients.[23] Colistin-related nephrotoxicity remains an important concern and has been found to be influenced by elevated plasma drug concentrations (>2.5 mg/L) and longer duration of therapy.[24] Similar insignificant effects as in our analysis of renal function have been demonstrated.[17] Another study found that up to 43% of patients were at risk of or had acute kidney injury or renal failure according to the Risk, Injury, Failure, Loss and End-stage kidney disease (RIFLE) criteria after IV colistin therapy; however, this toxicity was reversed following discontinuation of treatment.[25] Recent results from the multicentre PK colistin study demonstrated that there was huge interpatient variability in the clearance of colistin (even at similar creatinine clearances), which is probably due to differences between individuals in conversion rates of the inactive prodrug to its active form.[9] This adds to the complexity of providing optimal dosing, given the very narrow therapeutic window of the drug.

Study limitations

Limitations of this study include its retrospective nature and the need to collect data from electronic prescription records, which may not always record parameters such as renal replacement therapy.

Furthermore, the high number of patients who did not have their weight recorded made it difficult to calculate creatinine clearances using the Cockcroft-Gault equation. Compliance with the South African Society of Clinical Pharmacy dosing guidelines based on creatinine clearance may therefore be skewed. Although not an objective of the study, illness severity scores such as the APACHE II score were not recorded and patient risk in relation to mortality or outcome could therefore not be corrected. The median duration of colistin therapy in this study was 9 days. In these scenarios, treatment courses are typically determined at the discretion of the prescribing clinician, and this commonly depends on the clinical response to therapy and/or evidence of microbiological cure. As such, duration of therapy could not be used as a process indicator owing to the limited guidance available on what an appropriate duration should be. In addition, the dosing duration may have been a function of prescriber education rather than an indication that higher loading doses were associated with a more rapid clinical response. Finally, data on side-effects of colistin other than nephrotoxicity were not actively investigated.

Conclusions

This study showed that multiple stewardship opportunities for improvement exist, including administration of appropriate colistin loading and maintenance doses, optimising maintenance doses according to renal function, prioritising culture-driven prescribing where possible, and monitoring of combination therapy, de-escalation practices and duration of treatment to preserve colistin efficacy for the foreseeable future. The introduction of colistin therapeutic drug monitoring would be extremely useful to individualise dosing, given the variability of PK and PD parameters in critically ill patients. As an immediate solution, however, the design of a colistin antimicrobial stewardship bundle to increase composite compliance could have a significant impact and is strongly recommended.

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Acknowledgements. We acknowledge the invaluable contributions of the pharmacists at the participating hospitals for their day-to-day management of patients on colistin, and the hospitals and hospital group for participating in the study. We would also like to acknowledge Dr Petra Gaylard from DMSA (Data Management and Statistical Analysis) for her valuable insight and input relating to the statistics and data analysis.

Author contributions. APM, AJB and SvV designed the study. APM conducted the study and collected the data. AJB and SvV are cosupervisors to APM, as the study forms part of a postgraduate degree.

GAR provided expert input into the study design. All authors interpreted the data, wrote the article and approved the final version.

Funding. This study was supported by a Faculty Research Committee individual research grant from the Faculty of Health Sciences, University of the Witwatersrand.

Conflicts of interest. None.

1. O’Neill J. Review on AMR. Antimicrobial resistance: Tackling a crisis for the health and wealth of nations.

December 2014. https://amr-review.org/sites/default/files/160518_Final%20paper_with%20cover.pdf (accessed 17 November 2016).

2. Van Boeckel TP, Gandra S, Ashok A, et al. Global antibiotic consumption 2000 to 2010: An analysis of national pharmaceutical sales data. Lancet Infect Dis 2014;14(8):742-750. https://doi.org/10.1016/s14733099(14)70780-7 3. Goff DA, Kaye KS. Minocycline: An old drug for a new bug: Multi-drug resistant Acinetobacter baumanii.

Clin Infect Dis 2014;59(6):365-366. https://doi.org/10.1093/cid/ciu531 4. Biswas S, Brunel J, Dubus J, Reynaud-Gaubert M, Rolain J. Colisitin: An update on the antibiotic of the 21st century. Expert Rev Anti Infect Ther 2012;10(8):917-934. https://doi.org/10.1586/eri.12.78 5. Pike M, Saltiel E. Colistin- and polymyxin-induced nephrotoxicity: Focus on literature utilizing the RIFLE classification scheme of acute kidney injury. J Pharm Pract 2014;27(6):554-561. https://doi. org/10.1177/0897190014546116 6. Nation RL, Li J, Cars O, et al. Framework for optimisation of the clinical uses of colistin and polymyxin B: The Prato polymyxin consensus. Lancet Infect Dis 2015;15(2):225-234. https://doi.org/10.1016/s14733099(14)70850-3 7. Kassamali Z, Rotschafer JC, Jones RN, Prince RA, Danziger LH. Polymyxins: Wisdom does not always come with age. Clin Infect Dis 2013;57(6):877-883. https://doi.org/10.1093/cid/cit367 8. Ortwine JK, Kaye KS, Li J, Pogue J. Colistin: Understanding and applying recent pharmacokinetic advances. Pharmacother 2014;35(1):11-16. https://doi.org/10.1002/phar.1484 9. Nation RL, Garoznik SM, Thamlikitkul V, et al. Dosing guidance for intravenous colistin in critically ill patients. Clin Infect Dis 2017;64(5):565-571. https://doi.org/10.1093/cid/ciw839 10. Visser Kift E, Maartens G, Bamford C. Systematic review of the evidence for rational dosing of colistin. S Afr Med J 2014;104(3):183-186. https://doi.org/10.7196/SAMJ.10727 11. Drusano GL, Louie A, MacGowan A, Hope W. Suppression of emergence of resistance in pathogenic bacteria: Keeping our powder dry, Part 1. Antimicrob Agents Chemother 2016;60(3):1183-1193. https:// doi.org/10.1128/AAC.02177-15.

12. Jayol A, Poirel L, Brink AJ, Villegas M, Yilmaz M, Nordmann P. Resistance to colistin associated with a single amino acid change in protein PmrB among Klebsiella pneumoniae isolates of worldwide origin.

Antimicrob Agents Chemother 2014;58(8):4762-4766. https://doi.org/10.1128/aac.00084-14 13. Coetzee J, Corcoran C, Prentice E, et al. Emergence of plasmid-mediated colistin resistance (MCR-1) among Escherichia coli isolated from South African patients. S Afr Med J 2016;106(5):449-450. https:// doi.org/10.7196/samj.2016.v106i5.10710 14. Jayol A, Nordmann P, Brink AJ, Poirel L. Heteroresistance to colistin in Klebsiella pneumoniae associated with alterations in the PhoPQ regulatory system. Antimicrob Agents Chemother 2015;59(5):2780-2784. https://doi.org/10.1128/aac.05055-14 15. Labuschagne Q, Schellack N, Gous A, et al. Colistin: Adult and paediatric guideline for South Africa.

South Afr J Infect Dis 2016;1(1):1-5. https://doi.org/10.1080/23120053.2016.1144285 16. Al-Tawfiq JA, Laxminarayan R, Mendelson M. How should we respond to the emergence of plasmidmediated colistin resistance in humans and animals? Int J Infect Dis 2017;54:77-84. https://doi. org/10.1016/j.ijid.2016.11.415 17. Dalfino L, Puntillo F, Mosca A, et al. High-dose, extended-interval colistin administration in critically ill patients: Is this the right dosing strategy? A preliminary study. Clin Infect Dis 2012;54(12):1720-1726. https://doi.org/10.1093/cid/cis286 18. Garoznik SM, Li J, Thamlikitkul V, et al. Population pharmacokinetics of colistin methanesulfonate and formed colistin in critically ill patients from a multicenter study provide dosing suggestions for various categories of patients. Antimicrob Agents Chemother 2011;55(7):3284-3294. https://doi.org/10.1128/ aac.01733-10 19. Richards GA, Joubert IA, Brink AJ. Optimising the administration of antibiotics in critically ill patients. S Afr Med J 2015;105(5):419. https://doi.org/10.7196/SAMJ.9649 20. Vicari G, Bauer SR, Neuner EA, Lam SW. Association between colistin dose and microbiological outcomes in patients with multidrug-resistant Gram-negative bacteraemia. Clin Infect Dis 2012;56(3):398-404. https://doi.org/10.1093/cid/cis909 21. Falagas M, Rafailidis PI, Ioannidou E, et al. Colistin therapy for microbiologically documented multidrug-resistant Gram-negative bacterial infections: A retrospective cohort study of 258 patients. Int J Antimicrob Agents 2010;35(2):194-199. https://doi.org/10.1016/j.ijantimicag.2009.10.005 22. Paul M, Carmeli Y, Durante-Mangoni E, et al. Combination therapy for carbapenem-resistant Gramnegative bacteria. J Antimicrob Chemother 2014;69(9):2305-2309. https://doi.org/10.1093/jac/dku168 23. Garnacho-Montero J, Escoresca-Ortega A, Fernandes-Delgado E. Antibiotic de-escalation in the ICU: How is it best done? Curr Opin Infect Dis 2015;28(2):193-198. https://doi.org/10.1097/ qco.0000000000000141 24. Hartzell JD, Neff R, Ake J, et al. Nephrotoxicity associated with intravenous colistin (colistimethate sodium) treatment at a tertiary care medical center. Clin Infect Dis 2009;48(12):1724-1728. https://doi. org/10.1086/599225 25. Pogue JM, Lee J, Marchaim D, et al. Incidence of and risk factors for colistin-associated nephrotoxicity in a large academic health system. Clin Infect Dis 2011;53(9):879-884. https://doi.org/10.1093/cid/cir611

Accepted 11 August 2017.

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This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

RESEARCH

Self-reported alcohol use and binge drinking in South Africa: Evidence from the National Income Dynamics Study, 2014 - 2015 N G Vellios, MSocSc (Economics); C P van Walbeek, PhD (Economics) Southern Africa Labour and Development Research Unit, School of Economics, Faculty of Commerce, University of Cape Town, South Africa Corresponding author: N G Vellios (nicole.vellios@uct.ac.za) Background. Although the South African (SA) government has implemented alcohol control measures, alcohol consumption remains high.

Objectives. To quantify the prevalence of self-reported current drinking and binge drinking in SA, and to determine important covariates.

Methods. We used the 2014 - 2015 National Income Dynamics Study, a nationally representative dataset of just over 20 000 individuals aged ≥15 years. Multiple regression logit analyses were performed separately by gender for self-reported current drinkers (any amount), selfreported bingers as a proportion of drinkers, and self-reported bingers as a proportion of the total population. An individual was defined as a binge drinker if he/she reported consumption of ≥5 standard drinks on an average drinking day.

Results. Current alcohol use (any amount) in 2014 - 2015 was reported by 33.1% of the population (47.7% males, 20.2% females). Of drinkers, 43.0% reported binge drinking (48.2% males, 32.4% females). The prevalence of self-reported binge drinking as a percentage of the total population was 14.1% (22.8% males, 6.4% females). Although black African males and females were less likely than white males and females to report drinking any amount, they were more likely to report binge drinking. Coloured (mixed race) females were more likely than black African females to report drinking any amount. Males and females who professed a religious affiliation were less likely than those who did not to report drinking any alcohol. The prevalence of self-reported binge drinking was highest among males and females aged 25 - 34 years. Smoking cigarettes substantially increased the likelihood of drinking any amount and of binge drinking for both genders.

Conclusion. In SA, one in three individuals reported drinking alcohol, while one in seven reported binge drinking on an average day on which alcohol was consumed. Strong, evidence-based policies are needed to reduce the detrimental effects of alcohol use.

S Afr Med J 2018;108(1):33-39. DOI:10.7196/SAMJ.2018.v108i1.12615

Of the 48 countries in the World Health Organization (WHO) African region, South Africa (SA) had the highest per capita alcohol consumption (in terms of pure litres of alcohol) by individuals aged ≥15 years in 2010.[1] SA has a particularly harmful pattern of drinking. This indicator considers the manner and circumstances in which alcohol is consumed, rather than the prevalence of drinking.

The quantity of alcohol consumed per occasion, festive drinking, the proportion of drinking events that end in drunkenness, the proportion of drinkers who drink daily, and the prevalence of drinking outside of mealtimes and in public places are considered in compiling the pattern-of-drinking score.[2] The WHO classifies countries’ patterns of drinking on a five-point scale, where 1 indicates the least risky pattern of drinking and 5 the most risky pattern.[2] According to this scale, many Western European countries score a 1. At the other extreme, the Russian Federation and Ukraine are the only two countries that score a 5. Nine countries (SA, Belarus, Belize, Grenada, Guatemala, Kazakhstan, Moldova, Namibia and Zimbabwe) score a 4.[3] Risky drinking is associated with many social ills. In 2000, alcoholrelated homicide and violence, alcohol-related traffic accidents, alcohol-related disorders and fetal alcohol syndrome were responsible for 7.1% (95% confidence interval (CI) 6.6 - 7.5) of all deaths and 7% (95% CI 6.6 - 7.4) of disability-adjusted life-years lost in SA.[4] Alcohol harm is the fourth most important risk factor for premature death among the 17 risk factors identified by the South African National Burden of Disease Study.[5] A 2009 review of prevalence data from five national and local surveys on alcohol use in SA from the previous 12 years found no

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significant increase in alcohol use.[6] A 2011 study using 2008 data showed that 27.7% of the SA population (41.5% of males and 17.1% of females) were current drinkers.[7] Past-month binge drinking (defined as ≥4 drinks for females and ≥5 for males) was reported by 9.6% of the population (17.1% of males and 3.8% of females).[7] Given the stigma associated with alcohol use in many communities, and the well-known finding that people tend to under-report the consumption of goods and services that may be perceived as socially undesirable,[8-10] it is likely that the prevalence and intensity of drinking is under-reported in surveys. This was recently investigated in a 2017 study where five nationally representative SA surveys were used to calculate the percentage of total alcohol use that is accounted for in self-reported surveys. [11] The authors found that survey data covered between 11.8% (95% CI 9.3 - 16.2) and 19.4% (95% CI 14.9 - 24.2) of total alcohol consumption, suggesting massive under-reporting of actual alcohol consumption by respondents in surveys.[11] Even though alcohol use is under-reported in survey data, estimates of self-reported current and binge drinking can assist policy makers to monitor trends in alcohol use, especially risky drinking.

Objectives

To provide recent estimates of self-reported current drinking and binge drinking using a large nationally representative household dataset and to identify some of the important covariates of alcohol consumption. Given the substantial under-reporting of alcohol use, the numbers presented should be seen as lower limits.

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Methods

We used data from wave 4 of the 2014 - 2015 National Income Dynamics Study (NIDS).[12] NIDS is the first national cohort study in SA, focusing primarily on demographics, labour market participation, grants received, education and health. A stratified, two-stage cluster sample design was used in sampling the households included in the 2008 base wave.[13] The individuals interviewed in waves 2, 3 and 4 included both household members from the original sample and new individuals who had joined the original households. [14] Response rates in the NIDS survey were high – 81% of households were successfully interviewed in wave 4.

The NIDS contains questionnaires for households, adults (≥15 years), children and proxies. We used only the responses from the adult questionnaire of wave 4 in this study (n=22 752). Since we were less interested in changes in binge drinking than in the prevalence of binge drinking, we did not exploit the panel aspect of the data, but rather treated wave 4 as a cross-sectional dataset.

Respondents classified themselves into one of the previously defined official SA population groups. ‘African’ refers to black people originating from the African continent, ‘coloured’, a uniquely defined SA group, includes people of mixed Khoi, San, Malay, European and black African ancestry, ‘Asian’ defines descendants of individuals from East Asia and the Indian subcontinent, and ‘white’ refers to Caucasians of European ancestry.[8] Two survey questions were relevant to this study. The first was ‘How often do you drink alcohol?’ with options (i) ‘I have never drunk alcohol’, (ii) ‘I no longer drink alcohol’, (iii) ‘I drink alcohol very rarely’, (iv) ‘Less than once a week’, (v) ‘On 1 or 2 days a week’, (vi) ‘On 3 or 4 days a week’, (vii) ‘On 5 or 6 days a week’, and (viii) ‘Every day’.

A person was classified as a current drinker if he/she selected any option from (iii) through (viii). The second question was ‘On a day that you have an alcoholic drink, how many standard drinks do you usually have?’ (emphasis in original). The questionnaire defined a standard drink as ‘a small glass of wine, a 330 mL can of regular beer, a tot of spirits, or a mixed drink’. The options were (i) ‘13 or more standard drinks’, (ii) ‘9 to 12 standard drinks’, (iii) ‘7 to 8 standard drinks’, (iv) ‘5 to 6 standard drinks’, (v) ‘3 or 4 standard drinks’, and (vi) ‘1 or 2 standard drinks’. The questionnaire did not ask about the duration of a typical drinking session.

We present descriptive statistics, by demographic, socioeconomic and other indicators, of the proportion of adults (≥15 years) who indicated consumption of any alcohol and adults who reported binge drinking. In order to compare the coverage rate of alcohol consumption reported in the NIDS data with official sales, we estimated the number of drinks consumed in the 2014/2015 tax year by dividing the excise tax revenue received by the government for each of the four categories of alcohol (namely beer, sorghum beer and sorghum flour, wine and other fermented beverages, and spirits) by the appropriate specific excise tax amount for that category of alcohol.[15] We subsequently estimated odds ratios (ORs) for males and females using multiple logit regressions, for any drinkers (relative to the total population), bingers (relative to any drinkers), and bingers (relative to the total population). The choice of covariates

was based on previous studies and data availability. All results refer to self-reported consumption patterns of alcohol. Standard errors were clustered at the household level. All data were weighted and estimated using Stata/SE 14.1 (StataCorp, USA).

Results

In 2014 - 2015, 33.1% of SA adults aged ≥15 years (47.7% males, 20.2% females) reported consumption of any alcohol (Table 1). Of those who reported any alcohol consumption, 48.2% of males and 32.4% of females reported drinking ≥5 standard drinks per drinking day; 22.8% of adult males and 6.4% of adult females were therefore categorised as binge drinkers. Given under-reporting in survey data, these percentages should be seen as lower limits.

Descriptive statistics of adult (≥15 years) drinkers of any amount and binge drinkers (≥5 drinks) are shown in Table 2. Column 2 considers current drinkers as a percentage of the entire population, column 3 considers binge drinkers as a percentage of current drinkers, and column 4 considers binge drinkers as a percentage of the entire population.

Almost half of males and a fifth of females in SA reported current drinking (Table 2, column 2). Current drinking was highest among whites (54.1%) and coloureds (45.2%) and among individuals aged 25 - 34 years (42.5%). The prevalence of current drinking was higher in urban areas than in rural areas (38.1% and 24.0%, respectively).

Half of adults who were divorced/separated reported current drinking.

More than two-thirds of smokers reported current drinking. Those who were unemployed or employed reported higher prevalences of current drinking (35.9% and 41.9%, respectively) than those who were not economically active (e.g. retired or studying) (22.0%).

Although whites had the highest reported rate of current drinking (54.1%), whites had a lower rate of binge drinking among drinkers than all the other population groups (11.6%) (Table 2, column 3).

Black Africans had the lowest rate of reported drinking (29.4%), but the highest rate of binge drinking among drinkers (50.4%). Asians had a low reported drinking prevalence (28.9%) and a relatively low prevalence of binge drinking among drinkers (22.7%). Males had a high prevalence of drinking (47.7%) and a high prevalence of binge drinking among drinkers (48.2%), while females were substantially lower on both measures (20.2% and 32.4%, respectively). The correlation coefficient between the prevalence percentages in columns 2 and 3 is 0.12 (p=0.465), which suggests that the prevalence of drinking (any amount) is uncorrelated with the prevalence of binge drinking among drinkers.

Binge drinking was more prevalent among black Africans (14.6%) and coloureds (19.7%) than among Asians (6.6%) and whites (6.3%) (Table 2, column 4). Binge drinking peaked in the age range 25 - 34 years (20.9%). The prevalence of binge drinking was higher among individuals living in urban areas (16.2%) than among those living in rural areas (10.4%). There were also significant differences in prevalence by marital/partnership status, those who were living with a partner, divorced/separated or single, binging more than those who were married or were widows/widowers. The rate of binge drinking was higher among those who professed no religious affiliation

Table 1. Prevalence of self-reported drinking behaviour, 2014 - 2015[12] (weighted data) Total, % 33.1 43.0 14.1

Current drinkers (any amount) Current drinkers who binge drink* Binge drinkers* as proportion of the total population *Binge drinking defined as ≥5 standard drinks on a usual drinking day for males and females.

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Males, % 47.7 48.2 22.8

Females, % 20.2 32.4 6.4

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Table 2. Descriptive statistics of self-reported alcohol drinking and self-reported binge drinking in South Africa, 2014 - 2015[12] (weighted data)

Characteristics Column number Gender Males Females p-value* Population group Black African Coloured Asian White p-value Age (yr) 15 - 24 25 - 34 35 - 44 45 - 54 55 - 64 ≥65 p-value Rural/urban Rural Urban p-value Marital status Married Living with partner Widower/widow Divorced/separated Single p-value Religious affiliation No religious affiliation Religious affiliation p-value Smoking behaviour Non-smoker Smoker p-value Education No schooling Some primary (grades 1 - 7) Some secondary (grades 8 - 11) Completed secondary (grade 12) Some tertiary p-value Province Western Cape Eastern Cape Northern Cape Free State KwaZulu-Natal

Proportion of adult population, % 1

Alcohol consumers who Adults (≥15 yr) who drink ≥5 drinks per consume any alcohol, % drinking session, % 2 3

Adults (≥15 yr) consuming ≥5 drinks per drinking session, % 4

46.8 53.2

47.7 20.2 <0.001

48.2 32.4 <0.001

22.8 6.4 <0.001

79.0 9.1 2.8 9.2

29.4 45.2 28.9 54.1 <0.001

50.4 43.9 22.7 11.6 <0.001

14.6 19.7 6.6 6.3 <0.001

26.8 25.0 18.3 13.3 9.1 7.5

25.2 42.5 36.7 35.5 27.9 23.2 <0.001

47.9 49.4 44.2 39.0 27.6 14.6 <0.001

11.9 20.9 16.2 13.7 7.6 3.3 <0.001

35.4 64.6

24.0 38.1 <0.001

44.0 42.7 0.563

10.4 16.2 <0.001

27.8 6.9 1.0 3.3 61.0

32.9 39.7 24.5 50.4 33.8 <0.001

30.6 50.4 29.5 31.2 49.8 <0.001

10.0 19.9 7.2 15.7 16.6 <0.001

7.4 92.6

51.4 31.6 <0.001

47.9 42.4 0.082

24.4 13.3 <0.001

79.7 20.3

23.7 69.7 <0.001

36.6 51.7 <0.001

8.6 35.9 <0.001

5.4 15.3 46.1 16.6 16.6

24.9 28.7 30.3 37.6 43.0 <0.001

31.1 48.7 45.2 45.9 35.1 <0.001

7.5 13.8 13.6 17.2 15.0 <0.001

12.2 11.9 2.5 5.1 19.6

44.2 28.4 44.3 40.9 23.4

39.2 42.0 44.8 62.9 39.6

17.2 11.7 19.7 25.6 9.2 Continued ...

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Table 2. (continued) Descriptive statistics of self-reported alcohol drinking and self-reported binge drinking in South Africa, 2014 - 2015[12] (weighted data)

Characteristics North West Gauteng Mpumalanga Limpopo p-value Employment status Unemployed Not economically active† Employed p-value Total

Proportion of adult population, % 5.2 26.3 8.2 9.0

12.6 40.7 46.7 100

Adults (≥15 yr) who consume any alcohol, % 37.7 37.2 32.9 23.5 <0.001

Alcohol consumers who drink ≥5 drinks per drinking session, % 50.8 40.2 44.8 44.5 <0.001

Adults (≥15 yr) consuming ≥5 drinks per drinking session, % 19.0 14.8 14.6 10.4 <0.001

35.9 22.0 41.9 <0.001 33.1

46.4 36.8 45.1 0.002 43.0

16.6 8.0 18.8 <0.001 14.1

*The p-values test the hypothesis that the prevalence of drinking is the same between the various sub-categories. † E.g. retired or studying.

(24.4%) than among those who professed a religious affiliation (13.3%), and it was much higher among smokers (35.9%) than among non-smokers (8.6%). Individuals with no schooling had a lower rate of binge drinking than those with any level of education.

The total number of drinks reported in the 2014 - 2015 NIDS data was 4.8 billion (an average of 138 drinks per year per adult, irrespective of drinking status, and an average of 418 drinks per self-reported drinker). Specific excise tax revenue was collected from ~18.7 billion drinks (which indicates 534 drinks per adult, irrespective of drinking status) in the 2014/2015 tax year,[15] representing a coverage rate of 26%. Unrecorded consumption is estimated to account for 14% of total consumption (for the period 2009/2010).[16] Including this estimate of unrecorded consumption decreases the coverage rate to ~22%.

ORs, obtained from logit analyses, are shown in Table 3, which presents weighted regression results for males (columns 1 - 3) and females (columns 4 - 6), using different measures of alcohol consumption. Since the prevalence of drinking and binge drinking is much higher for males than for females, the regressions are estimated separately by gender. Columns 1 and 4 consider current drinking of any amount of alcohol, where y=1 if the person is a drinker and y=0 if the person is a non-drinker. Columns 2 and 5 consider binge drinking among drinkers, where y=1 if the drinker is a binge drinker and y=0 if the drinker is a non-binge drinker (non-drinkers are excluded from the analysis). Columns 3 and 6 consider binge drinking in the entire population, where y=1 if the person is a binge drinker and y=0 if the person is a non-binge drinker or a non-drinker. In the description of results, we primarily focus on drinking of any amount (columns 1 and 4) and bingers as a percentage of the total population (columns 3 and 6).

Although white males (OR 2.75; 95% CI 1.58 - 4.80) and females (OR 4.16; 2.39 - 7.25) were more likely to drink any amount of alcohol than black African males and females, white males (OR 0.33; 95% CI 0.16 - 0.69) and females (OR 0.19; 95% CI 0.07 - 0.48) were less likely to binge drink than black African males and females, respectively. Considering self-reported bingers as a percentage of self-reported drinkers (columns 2 and 5), coloured, Asian and white males and females were less likely to binge than black African males and females who drank. While there were no significant differences in bingers as a percentage of the total population (columns 3 and 6) between black Africans, coloureds and Asians, white males and females binged significantly less.

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Compared with males aged 15 - 24 years, males >24 years of age were more likely to drink any amount (column 1). Females aged 25 - 34 years were most likely to drink any amount (column 4). As a percentage of the total population, individuals aged 25 - 34 years were more likely to binge than those aged 15 - 24 years, for both males (OR 1.44; 95% CI 1.13 - 1.85) and females (OR 1.49; 95% CI 1.06 - 2.08). Binge drinking behaviour for older males did not differ significantly from that for males aged 15 - 24, but older females, especially beyond age 45, were significantly less likely to binge than females aged 15 - 24.

Compared with males who were married, males living with a partner (OR 1.58; 95% CI 1.09 - 2.27) or who were single (OR 1.74; 95% CI 1.24 - 2.43) were more likely to binge drink. Compared with females who were married, females living with a partner (OR 1.68; 95% CI 1.01 - 2.79) or who were single (OR 1.41; 95% CI 0.99 - 2.02) were more likely to binge drink, a similar result to that for males.

There was no statistical difference in male and female prevalence of any drinking according to whether there were children living in the house or not (columns 1 and 4). Having children in the house slightly increased the probability of binge drinking for males (OR 1.21; 95% CI 1.00 - 1.47), but not for females (OR 0.93; 95% CI 0.69 - 1.26).

Males who professed a religious affiliation were less likely to drink (OR 0.62; 95% CI 0.48 - 0.79) or to binge (OR 0.78; 95% CI 0.61 0.99) than males who professed no religious affiliation. The effect was similar for females, but was not significant for binge drinking.

Living in an urban area as opposed to a rural area increased the probability of binge drinking for both males (OR 1.28; 95% CI 1.04 1.56) and females (OR 1.56; 95% CI 1.15 - 2.11). Cigarette smoking was associated with a substantially greater likelihood of drinking and binge drinking for both males and females.

The impact of schooling on the likelihood of binge drinking differed substantially between males and females. The level of education did not appear to influence binge drinking among females, but did have an effect on males. Males with some tertiary education were more likely than males with no education to drink any amount, while males who had completed secondary school (OR 1.70; 95% CI 1.04 - 2.80) and had at least some tertiary education (OR 1.99; 05% CI 1.17 - 3.38) were more likely to binge than males with no schooling.

Males and females who were not economically active (e.g. retired or studying) were less likely to drink any amount (OR 0.73; 95% CI 0.56 - 0.95 for males and OR 0.58; 95% CI 0.44 - 0.78 for females)

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Table 3. Regression results (odds ratios, robust standard errors in parentheses), National Income Dynamics Study wave 4,[12] 2014 - 2015 (weighted data)

Column number Black African Coloured Asian White 15 - 24 years 25 - 34 years 35 - 44 years 45 - 54 years 55 - 64 years ≥65 years Married Living with partner Widower/widow Divorced/separated Single Any children living in house No children living in house No religious affiliation Religious affiliation Rural Urban Non-smoker Smoker No schooling Some primary (gr 1 - 7) Some secondary (gr 8 - 11) Completed secondary (gr 12) Some tertiary Unemployed Not economically active¶ Employed Per capita income (/1 000) Controls for province Constant Observations, n|| Pseudo r2

Drinkers† 1 1.00 1.09 (0.22) 1.54 (0.50) 2.75*** (0.78) 1.00 1.88*** (0.22) 1.62*** (0.24) 1.71*** (0.32) 1.88*** (0.41) 1.84** (0.50) 1.00 1.73*** (0.30) 2.00 (1.02) 2.26*** (0.63) 1.70*** (0.26) 1.00 1.09 (0.11) 1.00 0.62*** (0.08) 1.00 1.17* (0.11) 1.00 5.08*** (0.49) 1.00 0.76 (0.16) 0.93 (0.19) 1.40 (0.32) 1.80** (0.45) 1.00 0.73** (0.10) 1.04 (0.14) 1.00 (0.01) Yes 0.26*** (0.10) 9 000 0.16

Males Bingers of drinkers‡ 2 1.00 0.67* (0.14) 0.32*** (0.14) 0.16*** 0.06) 1.00 0.99 (0.15) 0.97 (0.18) 0.99 (0.23) 0.79 (0.20) 0.61 (0.21) 1.00 1.21 (0.26) 0.87 (0.61) 1.19 (0.43) 1.45** (0.27) 1.00 1.22* (0.14) 1.00 1.06 (0.15) 1.00 1.22 (0.16) 1.00 1.53*** (0.18) 1.00 1.47 (0.40) 1.35 (0.37) 1.54 (0.47) 1.69* (0.54) 1.00 0.83 (0.14) 1.11 (0.17) 1.00 (0.01) Yes 0.54 (0.24) 4 033 0.09

Bingers of total population§ 3 1.00 0.77 (0.14) 0.53 (0.21) 0.33*** (0.13) 1.00 1.44*** (0.18) 1.34* (0.21) 1.35 (0.28) 1.24 (0.28) 0.90 (0.26) 1.00 1.58** (0.29) 1.31 (0.86) 1.68 (0.57) 1.74*** (0.30) 1.00 1.21** (0.12) 1.00 0.78** (0.09) 1.00 1.28** (0.13) 1.00 3.49*** (0.34) 1.00 1.16 (0.27) 1.18 (0.27) 1.70** (0.43) 1.99** (0.54) 1.00 0.68*** (0.10) 1.08 (0.14) 1.00 (0.01) Yes 0.10*** (0.04) 8 933 0.12

Drinkers† 4 1.00 1.96*** (0.35) 0.78 (0.46) 4.16*** (1.18) 1.00 1.46*** (0.20) 1.12 (0.18) 0.90 (0.18) 0.68 (0.18) 0.94 (0.31) 1.00 1.30 (0.29) 0.37* (0.22) 1.39 (0.38) 1.51*** (0.20) 1.00 0.86 (0.11) 1.00 0.54*** (0.12) 1.00 1.37*** (0.16) 1.00 4.80*** (0.88) 1.00 0.79 (0.18) 0.68 (0.16) 0.88 (0.23) 0.99 (0.25) 1.00 0.58*** (0.09) 0.89 (0.13) 1.00 (0.00) Yes 0.33** (0.15) 11 134 0.15

Females Bingers of drinkers‡ 5 1.00 0.48*** (0.12)

Bingers of total population§ 6 1.00 0.85 (0.21)

††

††

0.08*** 0.04) 1.00 1.03 (0.21) 0.90 (0.24) 0.41*** (0.14) 0.26*** (0.12) 0.39* (0.20) 1.00 1.46 (0.47) 0.41 (0.27) 0.89 (0.47) 0.97 (0.24) 1.00 1.07 (0.20) 1.00 1.67 (0.54) 1.00 1.11 (0.20) 1.00 3.36*** (0.80) 1.00 1.37 (0.56) 1.13 (0.46) 1.35 (0.60) 1.27 (0.57) 1.00 1.05 (0.24) 1.12 (0.27) 0.99 (0.01) Yes 0.26** (0.17) 1 979 0.16

0.19*** (0.09) 1.00 1.49** (0.26) 0.96 (0.21) 0.51** (0.13) 0.27*** (0.09) 0.35** (0.16) 1.00 1.68** (0.43) 0.32* (0.22) 1.19 (0.48) 1.41* (0.26) 1.00 0.93 (0.14) 1.00 0.87 (0.27) 1.00 1.56*** (0.24) 1.00 8.88*** (1.90) 1.00 1.08 (0.35) 0.88 (0.28) 1.13 (0.40) 0.97 (0.35) 1.00 0.73* (0.14) 1.08 (0.20) 1.00 (0.00) Yes 0.04*** (0.02) 11 000 0.14

***p<0.01; **p<0.05; *p<0.1. † Dependent variable: drinker (y=1), non-drinker (y=0). ‡ Dependent variable: binge drinker (≥5 standard drinks on a usual drinking day for males and females) (y=1), non-binge drinker (y=0); non-drinkers excluded. § Dependent variable: binge drinker (y=1), non-binge drinker or non-drinker (y=0). ¶ E.g. retired or studying. || Exact number of observations that the regressions are based on. †† Blank cell because too few observations.

or to binge drink (OR 0.68; 95% CI 0.51 - 0.91 for males and OR 0.73; 95% CI 0.51 - 1.06 for females) than those who were unemployed.

The likelihood of employed males and females binge drinking was similar to that of unemployed males and females, respectively.

Differences in per capita income did not explain differences in the likelihood of drinking any amount or of binge drinking.

Discussion

Our current self-reported drinking estimate of 33.1% in 2014 - 2015 is higher than estimates (also age ≥15 years) reported in the 1998 Demographic and Health Survey (DHS)[8] of ~31%, and 27.7%

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in the South African National HIV, Incidence, Behaviour and Communication (SABSSM) survey in 2008.[7] We found that 48.2% of male drinkers reported binge drinking, while 32.4% of female drinkers reported binge drinking. Data from the 1998 DHS study revealed that rates of risky drinking were very similar for males and females, with one-third of current drinkers drinking at risky levels over weekends.[8] The difference in the estimates is likely to be due to the way we defined binge drinking for females (≥5 drinks) compared with the 1998 DHS study, which used ≥3 drinks, as well as the difference in timing of drinking (usual drinking v. weekend drinking).[8] The 2008 SABSSM data reveal that 9.6% of the

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population reported binge drinking (defined as consuming ≥4 drinks for females and ≥5 drinks for males). [7] This estimate is very similar to NIDS 2010 - 2011,[17] where self-reported binge drinking was estimated at 10.6% (females 3.5%, males 19.1%). The NIDS 2010 2011 prevalence data align closely to the WHO prevalence data for individuals aged ≥15 years in 2010 (10.4% of the population; females 3.7%, males 17.8%).[1] Whereas we defined binge drinking as ≥5 drinks per average drinking day, the WHO defined binge drinking as having consumed at least 60 g of pure alcohol on at least one occasion in the past 30 days. Although the definitions are different, the WHO estimate of 60 g of pure alcohol translates to about five 330 mL beers.

The SA government is expected to receive about ZAR20.8 billion in excise taxes on alcohol products in 2016/2017 (which is ~1.8% of total tax revenue).[15] Revenue received through alcohol excise taxes needs to be viewed in conjunction with costs resulting from alcohol harm. The economic costs in 2001 were estimated at ~1% of gross domestic product (GDP).[18] A 2009 study found that alcohol-related costs incurred by government (not society as a whole) were more than alcohol-related government revenue (excise tax and value-added tax (VAT)).[19] A 2014 study provides two estimates of the cost of alcohol as a percentage of the 2009 GDP: (i) the tangible, financial costs (e.g. healthcare, crime response, road traffic accidents) of harmful alcohol use is ~1.6% of GDP; and (ii) including the intangible costs (e.g. premature mortality and morbidity, absenteeism) increases the costs to 10 - 12% of GDP.[16,20] The manufacturing and retail of liquor was estimated to contribute 3.9% to 2009 GDP,[16] which is considerably lower than the more encompassing cost estimate of 10 - 12% of GDP. To address high rates of alcohol consumption and the associated economic and social costs to society, public health advocates in SA have been supporting higher excise taxes since as far back as 1995, arguing that the affordability of alcohol products is a strong determinant of alcohol use.[21] During the past two decades there have been substantial activities by the SA government aimed at preventing substance misuse, including public education campaigns aimed at pregnant women, drunk driving and the introduction of warning labels on containers on the harmful effects of alcohol.[22] By 2002, National Treasury set the total consumption tax burden (excise duties plus VAT) as a percentage of the weighted average retail selling price for wine, clear beer and spirits at 23%, 33%, and 43%, respectively.[23] The targeted tax burdens were increased to 35% for beer and 48% for spirits in 2012,[23] in the same year that the Minister of Health introduced the Control of Marketing of Alcoholic Beverages Draft Bill, which among other things would ban alcohol advertising. Although the SA Cabinet approved the Bill in September 2013, the alcohol industry successfully opposed the bill. In September 2016, the Minister of Trade and Industry tabled the National Liquor Policy Review, which outlines policy recommendations to be used in the draft Liquor Bill.[24] The policy recommendations in the review include, among others, advertising restrictions and increasing the legal drinking age from 18 to 21 years.

Policies and interventions aimed at reducing alcohol consumption, and especially risky consumption, are outlined in the 2014 WHO Global Status Report on Alcohol and Health.[1] These include pricing policies, marketing of alcoholic beverages and drink-driving policies and countermeasures. Since binge drinking varies substantially across demographic and socioeconomic groups, binge-drinking reduction policies should focus on groups with a high prevalence of binge drinking: males, black Africans, individuals aged 25 - 34 years, singles and people living with partners. There is very strong evidence that smokers are substantially more likely to binge drink than nonsmokers. Although we do not claim causality, measures that reduce

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smoking prevalence may have the additional benefit of reducing the prevalence of binge drinking.

Our estimates are likely to be lower bounds for several reasons.

First, whether a person consumes alcohol or not, and the quantity consumed, is self-reported in the NIDS questionnaire. It is well known that people under-report the purchase of socially undesirable goods.[8-10] A comparison between aggregate alcohol consumption, as reported in NIDS, and tax-based sales data indicates that NIDS reported only ~22% of total recorded and unrecorded consumption in 2014 - 2015. A 2017 study found that NIDS 2012 covered 14.6% (95% CI 11.3 - 20.3) of the total alcohol used per capita.[11] This suggests that either alcohol abstention is substantially less than reported, or that consumption per drinker (on average) is much more than reported, or both. Further research on how to deal with underreporting in the SA context is required.

Second, there may be under-reporting between different groups of people, since stigma is an important factor that is likely to affect the reporting of undesirable behaviours among some groups more than others. For example, women may be less likely to report drinking and binge drinking than men. Similarly, people with a religious affiliation may be less likely to report drinking and binge drinking compared with those who do not have a religious affiliation. On the other hand, self-reported smokers could be impervious to reporting drinking or binge drinking.

Third, there may be gender differences in alcohol metabolism[25] that we did not account for. Many academic studies classify binge drinking as ≥4 drinks per drinking session for females and ≥5 drinks for males.[26] The way the options for intensity of drinking are grouped in the NIDS questionnaire (1 - 2 drinks, 3 - 4 drinks, 5 - 6 drinks, etc.) makes it impossible to differentiate meaningfully between male and female binge drinking.

Fourth, our definition of binge drinking encompasses only the quantity consumed, and not the time frame of consumption or the time period of past binge-drinking episodes. A 2009 review of the scientific binge-drinking literature concludes that a definition of binge drinking should include all three factors.[26] In large household surveys, where alcohol use is not the main variable of interest, encompassing all three factors is often difficult. The NIDS questionnaire asks about the intensity of drinking as number of drinks per day, rather than per session. It is possible that some respondents could drink ≥5 drinks over the length of the day, which would not necessarily be classified as binge drinking.

Fifth, it is possible that consumers of ‘non-commercial’ forms of alcohol (home brews and other traditional forms of alcohol) do not classify themselves as drinkers, since a ‘standard drink’ in the NIDS questionnaire refers to wine, beer, spirits and mixed drinks.

Conclusion

The alcohol industry argues that it does not encourage harmful use of alcohol.[27] Since a very large proportion of alcohol consumed in SA is consumed hazardously, with associated detrimental consequences, the alcohol industry’s statements sound hollow, since they depend on these drinkers for profits. The public, and the public health community in particular, should support efforts by the ministries of Trade and Industry and Health to implement strong, evidence-based policies that reduce the detrimental effects of alcohol use.

Acknowledgements. We thank Dr Hana Ross for comments on an earlier draft of this article.

Author contributions. NV conducted the statistical analyses and wrote the first draft of the manuscript. CvW contributed to the analysis of the results

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and writing the manuscript. Both authors approved the final manuscript.

Funding. We thank the University of Cape Town for funding this research.

Conflicts of interest. None.

1. World Health Organization. Global Status Report on Alcohol and Health 2014. http://www.who.int/ substance_abuse/publications/global_alcohol_report/en/ (accessed 27 November 2017).

2. World Health Organization. Global Health Observatory (GHO) data: Patterns of drinking score.

Situation and trends 2017. http://www.who.int/gho/alcohol/consumption_patterns/drinking_score_ patterns_text/en/ (accessed 27 November 2017).

3. World Health Organization. Patterns of Drinking Score (Age 15+), 2010. Geneva: WHO, 2014. http://gamapserver.who.int/mapLibrary/Files/Maps/Global_drinking_scores_2010.png (accessed 27 November 2017).

4. Schneider M, Norman R, Parry C, Bradshaw D, Plüddemann A, and the South African Comparative Risk Assessment Collaborating Group. Estimating the burden of disease attributable to alcohol use in South Africa in 2000. S Afr Med J 2007;97(8):664-672.

5. Norman R, Bradshaw D, Schneider M, et al. A comparative risk assessment for South Africa in 2000: Towards promoting health and preventing disease. S Afr Med J 2007;97(8):637-641.

6. Peltzer K, Ramlagan S. Alcohol use trends in South Africa. J Soc Sci 2009;18(1):1-12. http://citeseerx.ist. psu.edu/viewdoc/download?doi=10.1.1.598.8726&rep=rep1&type=pdf (accessed 30 November 2017).

7. Peltzer K, Davids A, Njuho P. Alcohol use and problem drinking in South Africa: Findings from a national population-based survey. Afr J Psychiatry 2011;14(1):30-37. https://doi.org/10.4314/ajpsy.v14i1.65466 8. Parry CDH, Plüddemann A, Steyn K, Bradshaw D, Norman R, Laubscher R. Alcohol use in South Africa: Findings from the first Demographic and Health Survey (1998). J Stud Alcohol 2005;66(1):91-97. https:// doi.org/10.15288/jsa.2005.66.91 9. Livingston M, Callinan S. Underreporting in alcohol surveys: Whose drinking is underestimated? J Stud Alcohol Drugs 2015;76(1):158-164. https://doi.org/10.15288/jsad.2015.76.158 10. Stockwell T, Donath S, Cooper-Stanbury M, Chikritzhs T, Catalano P, Mateo C. Under-reporting of alcohol consumption in household surveys: A comparison of quantity-frequency, graduated-frequency and recent recall. Addiction 2004;99(8):1024-1033. https://doi.org/10.1111/j.1360-0443.2004.00815.x 11. Probst C, Shuper PA, Rehm J. Coverage of alcohol consumption by national surveys in South Africa.

Addiction 2017;112(4):705-710. https://doi.org/10.1111/add.13692 12. Southern Africa Labour and Development Research Unit. National Income Dynamics Study 2014 - 2015, Wave 4. Version 1.1. Cape Town: SALDRU, 2016.

13. Leibbrandt M, Woolard I, de Villiers L. National Income Dynamic Study. Methodology: Report on NIDS Wave 1. Technical Paper No. 1. Cape Town: Southern Africa Labour and Development Research Unit, 2009.

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14. Chinhema M, Brophy T, Brown M, Leibbrandt M, Mlatsheni C, Woolard I. National Income Dynamics Study Panel User Manual. Cape Town: Southern Africa Labour and Development Research Unit, 2016.

15. Republic of South Africa: National Treasury. 2016 Budget Review: Statistical Tables. http://www.treasury. gov.za/documents/national%20budget/2016/review (accessed 8 November 2016).

16. Truen S, Ramkolowan Y, Corrigall J, Matzopoulos R. Baseline Study of the Liquor Industry Including the Impact of the National Liquor Act 59 of 2003. Pretoria: Department of Trade and Industry, 2011.

17. Southern Africa Labour and Development Research Unit. National Income Dynamics Study 2010 - 2011, Wave 2. Version 3.1. Cape Town: SALDRU, 2016.

18. Parry CDH, Myers B, Thiede M. The case for an increased tax on alcohol in South Africa. S Afr J Econ 2003;71(2):137-145. https://doi.org/10.1111/j.1813-6982.2003.tb01308.x 19 19. Budlender D. National and Provincial Government Spending and Revenue Related to Alcohol Abuse.

Johannesburg: Soul City Development Institute, 2009.

20. Matzopoulos RG, Truen S, Bowman B, Corrigall J. The cost of harmful alcohol use in South Africa. S Afr Med J 2014;104(2):127-132. https://doi.org/10.7196/SAMJ.7644 21. Yach D, Parry CDH, Harrison S. Prospects for substance abuse control in South Africa. Addiction 1995;90(10):1293-1296.

22. Parry CDH. South Africa: Alcohol today. Addiction 2005;100(4):426-429. https://doi.org/10.1111/j.13600443.2005.01015.x 23. Republic of South Africa: National Treasury. A Review of the Taxation of Alcoholic Beverages in South Africa: A Discussion Document. May 2014. http://www.treasury.gov.za/public%20comments/ Alc/Alcohol%20Tax%20Review%20-%20May%202014%20Discussion%20Paper.pdf (accessed 30 November 2017).

24. Republic of South Africa: Department of Trade and Industry. Final Liquor Policy Paper: National Liquor Policy Review. August 2016. Pretoria: Republic of South Africa. https://www.thedti.gov.za/news2016/ NLP.pdf (accessed 27 November 2017).

25. Wechsler H, Dowdall GW, Davenport A, Rimm EB. A gender-specific measure of binge drinking among college students. Am J Public Health 1995;85(7):982-985.

26. Courtney K, Polich J. Binge drinking in young adults: Data, definitions, and determinants. Psychol Bull 2009;135(1):142-156. https://doi.org/10.1037/a0014414 27. Industry Association for Responsible Alcohol Use. Alcohol Limits and Unit Guidelines. http://www.ara. co.za/alcohol-limits-and-unit-guidelines/ (accessed 1 February 2017).

Accepted 14 August 2017.

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This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

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Prevalence of tobacco use in selected Johannesburg suburbs J A Teare,1,4 MSc; N Naicker,1,2,3,4,5 MB BCh, FCPHM, MMed, PhD; P Albers,1 MSc; A Mathee,1,2,3,4 PhD Environment and Health Research Unit, South African Medical Research Council, Johannesburg, South Africa Department of Environmental Health, Faculty of Health Sciences, University of Johannesburg, South Africa 3 School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa 4 Department of Environmental Health, School of Behavioural Sciences, Faculty of Health Sciences, Nelson Mandela University, Port Elizabeth, South Africa 5 Epidemiology and Surveillance Section, National Institute of Occupational Health, National Health Laboratory Services, Johannesburg, South Africa 1 2

Corresponding author: J A Teare (june.teare@mrc.ac.za) Background. Tobacco smoking is estimated to kill more than 44 000 South Africans every year. Studies have shown that since the introduction of tobacco control measures, national smoking prevalence has declined in South Africa (SA).

Objective. To determine the prevalence of tobacco smoking over a 7-year period in five impoverished neighbourhoods in Johannesburg, SA. Methods. Data were collected through the annual administration of a prestructured questionnaire to one adult respondent in preselected dwellings from 2006 to 2012. Information was collected on socioeconomic status, smoking practices and health status.

Results. Over the 7-year period of the analysis, smoking levels remained unchanged. The proportion of households with one or more smokers varied significantly across the five study neighbourhoods. Approximately 20% of households in Hillbrow and as many as 77% in Riverlea had a member who smoked.

Conclusions. Despite a national downward trend in smoking levels, tobacco use remains high and persistent in certain vulnerable communities, requiring scaled-up action to reduce the risk of a range of tobacco-related diseases.

S Afr Med J 2018;108(1):40-44. DOI:10.7196/SAMJ.2018.v108i1.12283

Worldwide, an estimated five million deaths per year are caused by tobacco use, and this figure is expected to exceed eight million by the year 2030.[1] Common health risks associated with smoking include heart disease, chronic obstructive pulmonary disease, lung cancer and stroke.[1] International studies have shown that the lifespan of smokers is reduced by 10 years relative to non-smokers.[2] In South Africa (SA), smoking has been found to account for 8 - 9% of the burden of mortality.[3] Age, gender, ethnic group and economic status are among the factors associated with smoking prevalence,[4,5] and there appears to be an inverse association between social status and smoking, in that 82% of the world’s smokers live in low- and middleincome countries.[1] In SA, the most frequent tobacco users have been identified as poor men and women with low levels of education and income, and living in urban areas.[4,6] Second-hand smoke (SHS) and passive/secondary smoking are terms used for smoked tobacco present in the atmosphere and to which non-smokers are exposed. The use of tobacco by one or more adults impacts negatively on the health of children and other adults living in the same household.[7] In 2004, global estimates showed that 40% of children, 35% of female non-smokers and 33% of male nonsmokers were exposed to SHS, and the number of deaths resulting from this exposure was estimated at 603 000; 28% (166 000) of these deaths were of children aged <5 years.[8] In children, SHS has been associated with lower respiratory tract illnesses, acute and chronic middle ear infections, chronic respiratory symptoms, asthma and reduced lung function, and there is evidence suggesting a link between SHS and childhood cancers.[9] While studies have indicated an overall downward trend in levels of smoking in SA in recent years,[10,11] there is limited information available on smoking patterns at a disaggregated household level.

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This is especially pertinent to the rapidly changing urban context in SA, where cities such as Johannesburg have seen rapid growth associated with urbanisation in recent decades, with influx from both the rural hinterlands and elsewhere on the African continent.

This article, which describes smoking levels in five relatively impoverished Johannesburg neighbourhoods, contributes to the need for information on smoking in a rapidly changing urban African context.

Objective

To determine the prevalence of tobacco use in selected settings of poverty in Johannesburg between 2006 and 2012.

Methods

Sampling and data collection

The Health, Environment and Development (HEAD) study is a Johannesburg-based panel study initiated in 2006, involving annual cross-sectional surveys (panel study) of urban environment and health trends, where data are collected from the same dwellings (unit of analysis) in each site every year.[12,13] The HEAD study was undertaken in five Johannesburg neighbourhoods: Bertrams (a run-down inner-city suburb with a mixed residential-commercial character), Hillbrow (a densely populated, high-rise inner-city area), Riverlea (an apartheid-era township constructed in the early 1960s), Braamfischerville (a democratic-era, low-cost, mass-based housing development), and Hospital Hill (an informal settlement on the city’s western boundary).

Dwellings were randomly selected in the neighbourhoods where planning maps were available (Bertrams, Riverlea and Braamfischerville). Systematic sampling was used in the high-rise

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study area of Hillbrow, while in Hospital Hill, where no planning maps were available on initiation of the study, convenience sampling was used. The main study outcomes included environmental risk factors and health outcomes. The prevalence for the various outcomes therefore varied. Based on resources available at the time, it was decided to sample 200 stands/plots/households in each of the five sites. After excluding commercial and empty plots, the final sample size shown in Table 1 was selected. For this article, the prevalence of tobacco smoking among SA adults was taken to be ~18%.[11] The desired margin of error was 5%. The power of the study was calculated at >90% for a sample size of 548 in 2012.

Data were collected in the selected dwellings using prestructured questionnaires administered to an adult member (respondent) of the main household on each dwelling site (secondary individuals or households living on the site were not considered). The questionnaire was tested in a pilot study in 2005 before commencement of the first study in 2006. Since the primary unit of selection was the dwelling, households and/or respondents could have changed over the 7-year period. Table 1 illustrates the response rates per year and per site over the 7-year period.

Interviews were undertaken by environmental health students from the University of Johannesburgâ&#x20AC;&#x2122;s Faculty of Health Sciences.

Ethical approval for the study was obtained from the University of Witwatersrand Human Research Ethics Committee (Medical) in 2005 prior to initiation of the study (ref. no. M050451), and renewed in March 2010 for a further 5 years (ref. no. M10471).

Among other variables, data were collected on socioeconomic status, migration patterns, neighbourhood environmental conditions, housing, health status and tobacco use practices.[12] For the purpose of this article, data on smoking prevalence were analysed for the 7-year period from 2006 to 2012. For analyses of the association between household tobacco use and health, data from the year 2012 were used.

analysis package, version 3.1 (EpiData, Denmark). The data were exported into the Stata statistical package, version 14 (StataCorp, USA), for analysis. Data for each site were weighted and the Stata survey command was used for analysis to minimise the effect of clustering and adjust for the study design. The trend analysis was calculated using the np trend command. Frequencies of various independent variables were calculated for those households that had reported a member smoking and those that had not. Data from the 2012 survey were used to explore various factors potentially associated with smoking. This was done on the bivariate level using logistic regression with crude odds ratios. A p-value of <0.05 was considered statistically significant. Plausible factors that showed possible significance (p<0.25) at the bivariate level were included in multivariate forward stepwise logistic regression models.

Data analysis

In the total study sample, the proportion of households with one or more smokers ranged from 41.8% to 52.7% over the 7-year period of the study (Fig. 1). The trend analysis showed the overall increase to be insignificant (p=0.4).

A breakdown of levels of tobacco use by study site indicated considerable variation, with Riverlea consistently having the highest prevalence. Riverlea also had the highest level of expenditure on tobacco and the highest proportion of households that included a child aged <5 years. In contrast, the lowest prevalence of tobacco use was in Hillbrow (Fig. 2), so Hillbrow was chosen as the area of reference for the bivariate analysis (Table 3).

Dependent variables. Respondents were asked whether any member of the household smoked â&#x20AC;&#x201C; if one or more members in a particular household smoked, it was defined as a smoking household. No information on the method of smoking was obtained. For the purposes of this study, tobacco use was therefore defined as the smoking of cigarettes (manufactured or hand rolled) or pipe (traditional or hookah/hubbly bubbly).

Independent variables included study site and household-level characteristics (socioeconomic status, demographic characteristics and health status). Data were entered into the EpiData statistical

Results

Study population

The profile (2012) of the population in the five study sites is given in Table 2. It can be seen that the study samples differed considerably across the five sites, including in terms of their main population groups (as defined during the apartheid era of government), proportion of households headed by migrants from other countries, tertiary educational attainment, employment status, income and household composition (households with and without children aged <5 years). Overall, households in Hillbrow, which had the highest proportion of households headed by a migrant from another country, tended to have higher levels of education, employment and income, while households in the informal settlement of Hospital Hill and in Riverlea were of relatively low socioeconomic status. Hillbrow also had the lowest proportion of households with one or more children aged <5 years and the lowest level of expenditure on tobacco.

Tobacco use prevalence

Table 1. Response rates (primary households in each dwelling) per year and per site over the study period Year 2006 2007 2008 2009 2010 2011 2012 Average over 7 years

Hospital Hill (N=188), n (%) 104 (55.3) 101 (53.7) 100 (53.2) 74 (39.4) 172 (91.5)* 108 (57.4) 138 (73.4) 114 (60.6)

Riverlea (N=158), n (%) 101 (63.9) 102 (64.5) 91 (57.7) 92 (58.2) 120 (75.9) 106 (67.0) 124 (78.4) 105 (66.4)

Braamfischerville (N=188), n (%) 122 (64.9) 151 (80.3) 101 (53.7) 117 (62.2) 143 (76.1) 124 (65.9) 147 (78.2) 130 (69.1)

Bertrams (N=132), n (%) 69 (52.3) 53 (40.1) 59 (44.7) 51 (38.6) 51 (38.6) 53 (40.2) 73 (55.3) 58 (43.9)

Hillbrow (N=142), n (%) 128 (90.1) 69 (48.6) 68 (47.9) 52 (36.6) 62 (43.7) 52 (36.6) 66 (46.5) 71 (50.0)

Total (N=808), n (%) 524 (64.9) 476 (58.9) 419 (51.9) 386 (47.7) 548 (67.8) 443 (54.8) 548 (67.8) 478 (59.2)

N = number of households targeted. *The informal settlement of Hospital Hill was re-sampled in 2010 owing to changes in house numbers associated with an electricity provision programme, and the relocation of some households to a formal housing programme nearby.

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Table 2. Profile of the study populations for 2012 Variable Place of birth South Africa Elsewhere Population group Black African Coloured Other (white, Indian) Households with children <5 years of age Head of household has tertiary education Head of household has full-time employment Household income (ZAR) â&#x2030;¤1 000 1 001 - 5 000 >5 000 Government grant* (at least one grant) Mean monthly expenditure on tobacco (ZAR)

Hospital Hill (N=138), n (%)

Riverlea (N=124), n (%)

119 (86.2) 19 (13.8)

124 (100.0) 0

138 (100.0) 0 0 64 (46.4) 3 (2.2) 10 (7.2)

57 (41.3) 58 (42.0) 19 (13.8) 67 (48.6) 38.80

Braamfischerville (N=147), n (%)

Bertrams (N=73), n (%)

Hillbrow (N=66), n (%)

145 (98.6) 2 (1.4)

60 (82.2) 13 (18.0)

34 (51.6) 32 (48.5)

12 (9.7) 112 (90.3) 0 64 (51.6) 5 (4.0) 13 (10.5)

146 (99.3) 1 (0.7) 0 63 (42.9) 18 (12.2) 27 (18.4)

47 (64.4) 10 (13.7) 16 (21.9) 28 (38.4) 3 (4.1) 18 (24.7)

65 (98.5) 0 1 (1.5) 19 (28.8) 18 (27.3) 32 (48.5)

36 (29.0) 52 (41.9) 31 (25.0) 80 (64.5) 140.80

33 (22.4) 71 (48.3) 39 (26.5) 72 (48.9) 24.08

8 (10.9) 40 (54.8) 24 (32.9) 31 (42.5) 92.95

4 (6.1) 28 (42.4) 34 (51.5) 7 (10.6) 15.15

*Disability, child and old age merged.

neighbourhoods was significantly elevated: Hillbrow 19.7% v. Hospital Hill 40.6% (p=0.004), Riverlea 77.4% (p=0.000), Braamfischerville 37.4% (p=0.013) and Bertrams 50.7% (p=0.000). Smoking levels were also significantly elevated in households headed by an individual born in SA relative to elsewhere (48.9% v. 31.9%; p=0.01; 95% confidence interval (CI) 0.28 - 0.842). In this study, levels of smoking were not associated with the educational status or income of the head of the household. Smoking levels were, however, elevated in households with heads who were not in full-time employment (p=0.05; 95% CI 0.998 2.414) or who had been born in SA rather than being a migrant from another country (p=0.01; 95% CI 0.28 - 0.842), and in households that had a member who received a government grant (p=0.005; 95% CIÂ 1.163 - 2.256). However, after controlling for socioeconomic status and study area, none of the risk factors remained significantly associated with household smoking status.

Bivariate analyses indicated statistically significant associations between households with a member who smoked and a member who reported acute respiratory symptoms (2-week recall period), asthma, hypertension, heart disease or stroke (1-year recall period). However, after adjusting for socioeconomic factors and study site, smoking prevalence was not associated with household-level ill health.

HouseholdsHouseholds using tobacco,using % tobacco, %

60 50 40 60

30

50

20

40

3010 20 0

2006

10

2007

2008

2009

2010

2011

2012

Year

0 2006

2007

2008

2009

2010

2011

2012

Households usingusing tobacco, % Households tobacco, %

Fig. 1. Tobacco use in households Year by year, 2006 - 2012 (total sample).

90 80 70

90 60 80 7050 6040 5030 4020 3010 20 10 0 0

Hospital Hill Hospital Hill

2006

2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012

2012

40 52 36 49 36 36 41

40 52 36 49 36 36 41

Riverlea Riverlea 72 84 75 78 73 76 77

Braamfischerville Bertrams

Braamfischerville Bertrams

72 84 75 78 73 76 77

31 39 35 47 45 44 37

31 39 35 47 45 44 37

49 57 51 47 49 55 51

49 5725 33 5125 4729 4929 5525 5120

The socioeconomic and demographic profile for households reporting tobacco use (n=257, 46.7%) for 2012 is shown in Table 3.

Compared with Hillbrow, smoking prevalence for the remaining four

44

Over the 7-year study period, no statistically significant change in

25 levels of smoking occurred in the total sample. This finding contrasts 33 with the finding at national level of an overall downward trend in 25 29 smoking prevalence since the introduction of the Tobacco Products 29 Control Act of 1993.[14] National tobacco smoking levels for 2010 were 25 19.4% (upper CI 24.1), declining to 18.2% (upper CI 23.8) by 2015. [15] 20

Fig. 2. Prevalence of tobacco use per year and per site.

Risk factors for elevated tobacco use (2012)

Discussion

Hillbrow

Hillbrow

In contrast, this study shows that in certain neighbourhoods, such as Riverlea, tobacco consumption continues to be highly elevated.

The relatively low levels of tobacco use in Hillbrow (19.7% of households had a member who smoked) may be attributable to the high proportion of respondents who were migrants from other countries. In the current study, the vast majority of international migrant household heads had originated from elsewhere in Africa.

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Table 3. Bivariate analysis of the socioeconomic and demographic profile of households reporting tobacco use for 2012

Variable Study site Hospital Hill (n=138) Riverlea (n=124) Braamfischerville (n=147) Bertrams (n=73) Hillbrow (ref) (n=66) Migration status (place of birth of head of household) South African (n=482) Non-South African (n=66) Households with children <5 years of age* None (n=295) One or more (n=238) Head of household has tertiary education* No (n=479) Yes (n=47) Head of household has full-time employment* No (n=441) Yes (n=100) Household income (ZAR)* <1 000 (n=138) 1 001 - 5 000 (n=249) >5 000 (ref) (n=147) Government grant† None (n=291) At least one grant (n=257)

Prevalence of reported smoking (N=257, 46.7%), n (%)

56 (40.6) 96 (77.4) 55 (37.4) 37 (50.7) 13 (19.7)

236/ 482 (48.9) 21/66 (31.9)

139 (47.1) 109 (45.8)

223 (46.6) 21(44.7)

215 (48.8) 38 (38.0)

68 (49.3) 125 (50.2) 60 (40.8)

120 (41.2) 137 (53.3)

Crude OR 2.78 13.97 2.44 4.19 ref

0.48

0.95

0.97

1.55 ref 1.04 0.71

1.63

p-value

0.004 0.000 0.013 0.000

0.01

0.76

0.81

95% CI 1.381 - 5.612 6.637 - 29.439 1.212 - 4.902 1.944 - 9.031 -

0.28 - 0.842

0.674 - 1.335

0.513 - 1.677

0.05

0.998 - 2.414

0.86 0.15

0.005

0.685 - 1.573 0.445 - 1.131

1.163 - 2.256

OR = odds ratio; CI = confidence interval. *Information missing, so total does not add up to 548. † Disability, child and old age merged.

Global estimates of tobacco use show that SA has a relatively low prevalence of smoking[15] compared with the USA,[16] Europe and Asia,[15] but a higher prevalence than neighbouring African countries such as Zimbabwe and Malawi.[15] Concomitant with the significantly elevated levels of smoking in Riverlea, these households also spent more than nine times as much money on tobacco as Hillbrow households, despite the lower socioeconomic status in Riverlea. There is concern regarding childhood exposure to SHS in Riverlea, which also had the highest proportion of households with children aged <5 years. The findings of this study are in keeping with previous SA studies that have found particularly elevated levels of tobacco use and tobacco-related deaths in coloured communities, while black African communities had the lowest levels.[4,6] Smokers in the coloured population have been reported to have a 50% higher overall mortality than otherwise similar non-smokers or ex-smokers.[17] With regard to exposure to SHS, an SA birth cohort study showed that coloured children were most frequently exposed to SHS owing to the presence of a primary caregiver who smoked; 42% of children lived in homes with two or more smokers.[18] The present study confirms the need for scaledup action to reduce smoking levels and the associated ill-health outcomes in vulnerable neighbourhoods such as Riverlea.

Stringent tobacco control policies in developed countries have resulted in low levels of tobacco consumption. This declining demand for tobacco products and a difficult tobacco market have triggered aggressive tobacco sales strategies in low- and middle-income

45

African countries.[19] Young people in particular are being targeted by tobacco companies by the placement of products in movies and music videos and distribution of tobacco products at student parties, and by appealing to the naturally rebellious nature of adolescents. [10] SA studies relating to the initiation of smoking have shown that with each successive generation individuals began smoking at a younger age, proving that the tobacco industry is having success in recruiting adolescent smokers.[10] Prevention and cessation efforts should therefore focus on the youth. In addition, the rising income in fast-growing countries increases the affordability of cigarettes in the majority of low- and middle-income countries.[20] However, of the tobacco control policies in place in SA, tobacco price increases have been shown to be the most effective intervention. Other factors associated with an increase in tobacco use in low socioeconomic areas are low levels of education and low status of workers.[21]

Study limitations

A limitation to this study may be information bias at respondent level, outcomes for this interview-based study having been constructed on the respondent’s ability to recollect household events and activities accurately.[22] For example, difficulty may be experienced by a respondent who is requested for household information in an impromptu scenario, or who may be ignorant of certain information such as household earnings. Findings may also have been affected by incomplete data and lower response rates in some study sites (Bertrams and Hillbrow), which were affected by xenophobic violence

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during 2008/2009.[23] Limitations of the cross-sectional study design are applicable to this study as well, in that the study reflected information at one point in time only and the incidence of smoking could not be measured in the sample over the 7-year period.[24] In addition, associations that were determined in the multivariate analyses may be difficult to interpret owing to the study design; no data were available on individual household members who engaged in smoking and the health effects on them, so we were not able to comment on any individual risk factors for/consequences of smoking.

Conclusions

Our study confirms that in spite of the national downward trend in smoking prevalence, levels of tobacco use continue to be highly elevated in certain groups and settings. Scaled-up action is required in such vulnerable communities to reduce tobacco use and the associated ill-health conditions. Efforts towards smoking prevention and cessation should include specifically designed interventions according to age, culture and living conditions.

Acknowledgements. We thank the community members who participated in the project by generously offering their time and responses. We also thank the environmental health students of the University of Johannesburg who diligently collected the data.

Author contributions. AM and NN conceptualised and designed the study, PA and NN analysed the data, and JAT led the writing with participation and constructive discussion from AM, NN and PA. Funding. This study was made possible by funding from the South African Medical Research Council.

Conflicts of interest. None.

1. World Health Organization. Systematic Review of the Link between Tobacco and Poverty. Geneva: WHO, 2011. http://libdoc.who.int/publications/2011/9789241500548_eng.pdf (accessed 4 March 2016).

2. Doll R, Peto R, Boreham J, Sutherland I. Mortality in relation to smoking: 50 years’ observations on male British doctors. BMJ 2004;328:1519. https://doi.org/10.1136/bmj.38142.554479.ae 3. Groenewald P, Vos T, Norman R, et al. Estimating the burden of disease attributable to smoking in South Africa in 2000. S Afr Med J 2007;97(8):674-681.

4. Steyn K, Bradshaw D, Norman R, Laubscher R, Saloojee Y. Tobacco use in South Africans during 1998: The first demographic and health survey. Eur J Prev Cardiol 2002;9(3):161-170. https://doi.org/10.117 7%2F174182670200900305 Erratum in Eur J Prev Cardiol 2002;9(4):inside back cover. http://journals. sagepub.com/doi/pdf/10.1177/174182670200900407 (accessed 14 December 2016).

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5. Lim KH, Jasvindar K, Cheong SM, et al. Prevalence of smoking and its associated factors with smoking among elderly smokers in Malaysia: Findings from a nationwide population-based study. Tob Induc Dis 2016;14:8. https://doi.org/10.1186/s12971-016-0073-z 6. Van Walbeek C. Economics of Tobacco Control Project – Phase II. The tobacco epidemic can be reversed: Tobacco control in South Africa during the 1990s. Applied Fiscal Research Centre, School of Economics, University of Cape Town, 2002. http://s3.amazonaws.com/zanran_storage/www.idrc.org. sg/ContentPages/1302304619.pdf (accessed 13 October 2016).

7. World Health Organization. The World Health Organization Report on the Global Tobacco Epidemic, 2008: The MPOWER Package. Geneva: WHO, 2008. http://www.who.int/tobacco/mpower/mpower_ report_full_2008.pdf (accessed 29 March 2016).

8. Öberg M, Jaakkola MS, Woodward A, Peruga A, Prüss-Ustün A. Worldwide burden of disease from exposure to second-hand smoke: A retrospective analysis of data from 192 countries. Lancet 2011;377(9760):139-146. https://doi.org/10.1016/s0140-6736(10)61388-8 9. World Health Organization. Tobacco Free Initiative: International Consultation on Environmental Tobacco Smoke (ETS) and Child Health. Geneva: WHO, 1999. http://www.who.int/entity/tobacco/ research/en/ets_report.pdf (accessed 4 March 2016).

10. Shisana O, Labadarios D, Rehle T, et al. The South African National Health and Nutrition Examination Survey (SANHANES-1). Cape Town: HSRC Press, 2013. http://www.hsrc.ac.za/uploads/pageNews/72/ SANHANES-launch%20edition%20(online%20version).pdf (accessed 7 April 2016).

11. Reddy P, Zuma K, Shisana O, Jonas K, Sewpaul R. Prevalence of tobacco use among adults in South Africa: Results from the first South African national health and nutrition examination survey. S Afr Med J 2015;105(8):648-655. https://doi.org/10.7196/SAMJnew.7932 12. Mathee A. Indicators of Health Environment and Development: Longitudinal study in Johannesburg, 2006 - 2008 Johannesburg: Environmental and Health Research Unit, South African Medical Research Council, 2009. http://www.mrc.ac.za/environmenthealth/head0608.pdf (accessed 13 December 2016).

13. Mathee A, Harpham T, Naicker N, et al. Overcoming fieldwork challenges in urban health research in developing countries: A research note. Int J Soc Res Method 2010;13(2):171-178. https://doi. org/10.1080/13645570902867742 14. Ayo-Yusuf OA, Olutola BG. ‘Roll-your-own’ cigarette smoking in South Africa between 2007 and 2010.

BMC Public Health 2013;13(1):597. https://doi.org/10.1186/1471-2458-13-597 15. World Health Organization. WHO Global Report on Trends in Prevalence of Tobacco Smoking 2015. Geneva: WHO, 2015. http://apps.who.int/iris/bitstream/10665/156262/1/9789241564922_eng. pdf?ua=1 (accessed 23 June 2016).

16. Centers for Disease Control and Prevention. Current Cigarette Smoking Among Adults – United States, 2005 - 2014. MMWR 2015;64(44):1233-1240. https://doi.org/10.15585%2Fmmwr.mm6444a2 17. Sitas F, Egger S, Bradshaw D, et al. Differences among the coloured, white, black, and other South African populations in smoking-attributed mortality at ages 35 - 74 years: A case control study of 481,640 deaths. Lancet 2013;382(9893):685-693. https://doi.org/10.1016/s0140-6736(13)61610-4 18. Steyn K, de Wet T, Richter L, Cameron N, Levitt NS, Morrell C. Cardiovascular disease risk factors in 5-year-old urban South African children – the Birth to Ten study. S Afr Med J 2000;90(7):719-726.

19. Van Walbeek C. Why South Africa needs to up the ante against smoking again. The Conversation, Health & Medicine, May 2016. http://theconversation.com/why-south-africa-needs-to-up-the-anteagainst-smoking-again-59922 (accessed 25 July 2017).

20. Blecher EH, van Walbeek CP. Cigarette affordability trends: An update and some methodological comments. Tob Control 2009;18(3):167-175. https://doi.org/10.1136%2Ftc.2008.026682 21. Pampel F. Tobacco use in sub-Sahara Africa: Estimates from the demographic health surveys. Soc Sci Med 2008;66(8):1772-1783. https://doi.org/10.1016%2Fj.socscimed.2007.12.003 22. Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening the reporting of observational studies in epidemiology (STROBE): Explanation and elaboration. PLoS Med 2007;4(10)e297:1628-1654. https://doi.org/10.1371%2Fjournal.pmed.0040297 23. Kapp C. South Africa failing people displaced by xenophobia riots. Lancet 2008;371(9629):1986-1987. https://doi.org/10.1016/s0140-6736(08)60852-1 24. Morromi C, Myer L. Study design. In: Ehrlich R, Joubert G, eds. Epidemiology: A Research Manual for South Africa. 3rd ed. Cape Town: Oxford University Press Southern Africa, 2014:78-83.

Accepted 17 August 2017.

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This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

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Predictors of treatment success in smoking cessation with varenicline combined with nicotine replacement therapy v. varenicline alone F Noor,1 MB ChB, MSc; C F N Koegelenberg,1 MB ChB, MMed (Int), FCP (SA), FRCP (UK), Cert Pulm (SA), PhD; T M Esterhuizen,2 MSc; E M Irusen,1 MB ChB, FCP (SA), PhD 1 2

Division of Pulmonology, Department of Medicine, Stellenbosch University and Tygerberg Academic Hospital, Cape Town, South Africa Centre for Evidence-based Health Care, Stellenbosch University, Cape Town, South Africa

Corresponding author: C F N Koegelenberg (coeniefn@sun.ac.za) Background. Identification of the predictors of treatment success in smoking cessation may help healthcare workers to improve the effectiveness of attempts at quitting.

Objective. To identify the predictors of success in a randomised controlled trial comparing varenicline alone or in combination with nicotine replacement therapy (NRT).

Methods. A post-hoc analysis of the data of 435 subjects who participated in a 24-week, multicentre trial in South Africa was performed.

Logistic regression was used to analyse the effect of age, sex, age at smoking initiation, daily cigarette consumption, nicotine dependence, and reinforcement assessment on abstinence rates at 12 and 24 weeks. Point prevalence and continuous abstinence rates were self-reported and confirmed biochemically with exhaled carbon monoxide readings.

Results. The significant predictors of continuous abstinence at 12 and 24 weeks on multivariate analysis were lower daily cigarette consumption (odds ratio (OR) 1.86, 95% confidence interval (CI) 1.21 - 2.87, p=0.005 and OR 1.83, 95% CI 1.12 - 2.98, p=0.02, respectively) and older age (OR 1.52, 95% CI 1.00 - 2.31, p=0.049 and OR 1.79, 95% CI 1.13 - 2.84, p=0.01, respectively). There was no difference in the predictors of success in the univariate analysis, except that older age predicted point prevalence abstinence at 12 weeks (OR 1.47, 95% CI 1.00 - 2.15, p=0.049). The findings were inconclusive for an association between abstinence and lower nicotine dependence, older age at smoking initiation and positive reinforcement.

Conclusion. Older age and lower daily cigarette consumption are associated with a higher likelihood of abstinence in patients using varenicline, regardless of the addition of NRT. S Afr Med J 2018;108(1):45-49. DOI:10.7196/SAMJ.2018.v108i1.12671

Tobacco dependence is a global epidemic and a major preventable cause of morbidity and mortality. The World Health Organization reported that nearly 6 million tobacco-related deaths occur annually.[1] Despite the well-known benefits of smoking cessation, it remains a challenge for many smokers who attempt to quit. Approximately 70% of smokers want to discontinue smoking;[2] however, only 3 - 5% of those who attempt to do so without assistance remain abstinent in the long term.[3] Behavioural interventions and pharmacotherapy are effective methods in smoking cessation,[4] and when combined, are even more efficacious.[5] Commonly used pharmacotherapies include nicotine replacement therapy (NRT), bupropion and varenicline. All have been proven to be efficacious to varying degrees.

Studies investigating factors that predict smoking cessation success have identified the following: male gender, older age, older age at initiation of smoking, lower nicotine dependency, lower exhaled carbon monoxide levels, fewer cigarettes smoked per day and higher confidence with regard to quitting (self-efficacy). Heavier smokers and smokers with a high nicotine dependency in particular are more likely to continue smoking.[6-15] A tobacco user who smokes at least 20 cigarettes per day is generally considered to be a heavy smoker. The level of nicotine dependence may be assessed with the FagerstrĂśm test for nicotine dependence (FTND) â&#x20AC;&#x201C; a frequently used questionnaire scored out of 10, with a score of at least 7 denoting high dependency.[16] Reasons for successful cessation include health concerns and the high cost of cigarettes.[17] The motivation for

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continued smoking may also contribute â&#x20AC;&#x201C; smoking for pleasure or reward (positive reinforcement), or to relieve a negative state (negative reinforcement).[18] A recent study reported that combining varenicline and bupropion improved abstinence rates in heavier smokers and in persons with a high nicotine dependency.[19] This suggests that combination therapies may improve success rates in these difficult groups.

In a recent randomised controlled trial (RCT), we established that varenicline combined with NRT was more effective than varenicline alone, with a favourable safety profile.[20] We performed a post-hoc analysis of the data from the original RCT to identify the independent predictors of successful abstinence at 12 and 24 weeks after the target quit date. The objective was to assist healthcare workers to select interventions according to the characteristics of the individual smoker to improve their chances of success.

Methods

Study design

We performed a post-hoc analysis of a study dataset prospectively collected from April 2011 to October 2012 at seven sites throughout South Africa (SA). The study was conducted in accordance with the principles outlined in the Declaration of Helsinki, and local and international Good Clinical Practice guidelines. Ethical approval was obtained from the Health Research Ethics Committee of Stellenbosch University (ref. no. S15/02/029). The original study methods and

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outcomes have been described elsewhere.[20] In the original study, 446 adult smokers were randomised to receive either varenicline 1 mg twice daily with active nicotine patches 15 mg per day (combination therapy) or varenicline twice daily with placebo patches (monotherapy) for 12 weeks, and were followed up for a further 12 weeks.

Study procedures and assessment

In the current analysis, all randomised participants who were administered at least one dose of both medications were included in the study population. They were categorised by specific baseline characteristics, including age, sex, age at smoking initiation, cigarette consumption per day, nicotine dependence as measured by the FTND and motivation for continued smoking using the reinforcement assessment, and were followed up until weeks 12 and 24. The measures of cessation included 7-day point prevalence abstinence, referring to the preceding 7 days, and continuous abstinence – a prolonged period of at least 4 weeks before the assessment date.

At week 12, the 7-day point prevalence abstinence rate (PPAR) and the 4-week continuous abstinence rate (CAR) for weeks 9 - 12 were evaluated. At week 24, the 7-day PPAR and CAR for weeks 9 - 24 were also measured. Abstinence from tobacco was self-reported using the Nicotine Use Inventory (NUI), which evaluates tobacco or nicotine use (other than that provided) since the last contact and the preceding 7 days. This was biochemically confirmed by exhaled carbon monoxide measurements of ≤10 parts per million. Participants who missed the visits at weeks 12 and 24 were considered smokers at those time points, and those who discontinued the study or were lost to follow-up were also considered smokers.

Statistical aspects

The data were analysed using Stata version 13.1 (StataCorp., USA).

Univariate logistic regression was used to do a crude analysis of the entire study population to identify predictors of abstinence for each of the four outcomes. Participants for whom the relevant baseline data were missing, were excluded from that particular category for univariate analysis as per protocol.

Multivariate logistic regression was used to measure the association between all the baseline characteristics and abstinence rates at weeks 12 and 24, adjusting for the treatment received. To include all participant data in the models for multivariate analysis, missing data were coded as missing and included in the models as a separate category. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated and statistical significance was indicated at p 0.05.

Results

A total of 446 participants were randomised, 435 of whom were included – 216 in the combination therapy arm, and 219 in the monotherapy arm. Their baseline characteristics have been reported elsewhere.[20] No statistically significant differences in baseline predictors were found between the participants in the active treatment group and those in the placebo group. Missing baseline data were minimal and comparable across treatment arms (<2%).

The short-term (7-day point prevalence) and long-term (continuous) abstinence rates in each treatment arm according to baseline characteristics are shown in Table 1. In keeping with our previous findings, the active group had a higher abstinence rate than the placebo group across all categories.[20] In the univariate analysis conducted at 12 and 24 weeks, CARs were significantly higher in light smokers than in heavy smokers at both time points, and in older participants than in those <50 years of age at the 24-week time point (Table 2). These associations remained

48

significant in the multivariate analysis. The only predictor of PPAR was younger age – at 12 weeks. In the sample, heavily nicotine-dependent participants were more likely to continue smoking than those who were less nicotine dependent; however, this difference was not statistically significant, indicating no population differences. No other factors significantly predicted successful smoking cessation, including sex, age at smoking initiation and motivation for continued smoking, i.e. the reinforcement assessment.

The multivariate analysis did not markedly change the ORs for all variables, except for identifying younger age as a predictor of the 12-week CAR. Participants who started smoking after the age of 20 had a relatively poorer response on varenicline alone (CAR 22.2%) than those on combination therapy (CAR 39.1%) (p<0.01).

Discussion

The original study confirmed that the addition of NRT improved smoking cessation success at both time points. The only other significant predictors of success identified in the current analysis were older age and lower daily cigarette consumption.

The reasons for smoking cessation, self-efficacy (a participant’s belief in his/her ability to succeed) and level of motivation were not assessed, but it may be that older persons are more likely to be motivated to quit because of health concerns. Younger persons may consider future opportunities to quit and be less committed or motivated.[11] Preparedness for the challenges of tobacco abstinence was not assessed, but quit attempts were well supported by smoking cessation counselling during all visits before and after quitting.

The finding that heavier smokers had lower abstinence rates than those who smoked fewer cigarettes per day is in keeping with previous research;[7,8,10-12] however, it contrasts with a recent study, where a combination of varenicline and bupropion improved abstinence in heavy smokers and in those who were more nicotine dependent.[19] This may be due to the average daily cigarette consumption in this study population being lower, as was the average FTND. The data from our study did not suggest that combination therapy (varenicline and NRT) conferred any benefit to heavy and more-dependent smokers.

Unlike previous research, which indicated that lower levels of nicotine dependence were associated with increased abstinence,[7,9-11,14] we did not observe this. We investigated whether highly dependent smokers would benefit more, but unexpectedly there were fewer patients with high dependence.

Studies have also found that men are more likely to abstain than women;[7-10,12] however, we could not confirm this – perhaps because we had a greater number of female participants.

Despite the original study findings in favour of the addition of NRT to varenicline, we found little difference in the ORs between univariate and multivariate analyses, suggesting that the addition of nicotine replacement to varenicline did not markedly alter the predictors of abstinence. Baseline characteristics that predicted success in participants who received varenicline alone were found to be similar to those of the group who received both varenicline and NRT. There may be other factors that contribute to smoking cessation success. Genetic studies of variations in the nicotine-receptor gene cluster CHRNA5-CHRNA3-CHRNB4 found that although smokers with the high-risk haplotype had a heightened response to pharmacotherapy, they were more likely to relapse than the low-risk group.[21] Recent research also found that the therapeutic response to a nicotine patch and varenicline is influenced by the nicotine

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Table 1. Abstinence rates in each treatment arm according to baseline characteristics 12 weeks Baseline characteristics

24 weeks

Treatment arm

Total

7-day PPAR, n (%)

CAR 9 - 12 weeks, n (%)

7-day PPAR, n (%)

CAR 9 - 24 weeks, n (%)

Active

94

61 (64.89)

52 (55.32)

50 (53.19)

40 (42.55)

Placebo

90

35 (38.89)

28 (31.11)

23 (25.56)

18 (20.00)

Active

122

55 (45.08)

47 (38.52)

44 (36.07)

31 (25.41)

Placebo

129

52 (40.31)

42 (32.56)

40 (31.01)

24 (18.60)

Active

87

43 (49.43)

38 (43.68)

34 (39.08)

28 (32.18)

Placebo

83

31 (37.35)

25 (30.12)

24 (28.92)

15 (18.07)

Active

129

73 (56.59)

61 (47.29)

60 (46.51)

43 (33.33)

Placebo

136

56 (41.18)

45 (33.09)

39 (28.68)

27 (19.85)

Active

85

45 (52.94)

35 (41.18)

34 (40.00)

24 (28.24)

Placebo

93

31 (33.33)

20 (21.51)

21 (22.58)

12 (12.90)

Age, years ≥50 <50 Sex Male Female Cigarettes/day, n ≥20 <20

Active

131

71 (54.20)

64 (48.85)

60 (45.80)

47 (35.88)

Placebo

126

56 (44.44)

50 (39.68)

42 (33.33)

30 (23.81)

Level of nicotine dependence* FTND ≥7 FTND <7

Active

12

4 (33.33)

3 (25.00)

3 (25.00)

2 (16.67)

Placebo

15

4 (26.67)

4 (26.67)

3 (20.00)

3 (20.00)

Active

202

111 (54.95)

95 (47.03)

89 (44.06)

68 (33.66)

Placebo

201

83 (41.29)

66 (32.84)

59 (29.35)

39 (19.40)

Active

46

29 (63.04)

24 (52.17)

24 (52.17)

18 (39.13)

Placebo

54

24 (44.44)

20 (37.04)

19 (35.19)

12 (22.22)

Age at smoking initiation, years ≥20 <20

Active

170

87 (51.18)

75 (44.12)

70 (41.18)

53 (31.18)

Placebo

165

63 (38.18)

50 (30.30)

44 (26.67)

30 (18.18)

Reinforcement assessment† NR PR NR + PR N/A

Active

44

23 (52.27)

20 (45.45)

21 (47.73)

16 (36.36)

Placebo

52

18 (34.62)

15 (28.85)

13 (25.00)

10 (19.23)

Active

54

29 (53.70)

24 (44.44)

20 (37.04)

15 (27.78)

Placebo

49

24 (48.98)

16 (32.65)

18 (36.73)

10 (20.41)

Active

95

53 (55.79)

44 (46.32)

42 (44.21)

31 (32.63)

Placebo

97

40 (41.24)

35 (36.08)

29 (29.90)

20 (20.62)

Active

20

10 (50.00)

10 (50.00)

8 (40.00)

8 (40.00)

Placebo

19

5 (26.32)

4 (21.05)

3 (15.79)

2 (10.53)

PPAR = point prevalence abstinence rate; CAR = continuous abstinence rate; FTND = Fagerström test for nicotine dependence; NR = negative reinforcement (smoking to avoid a negative state); PR = positive reinforcement (smoking for pleasure); N/A = not applicable (never tried to quit). * FTND not done – 2 (0.93%) in active group, and 3 (1.37%) in placebo group. † Reinforcement assessment not done – 3 (1.39%) in active group, and 2 (0.91%) in placebo group.

metabolite ratio (NMR), a genetically influenced biomarker measuring the ratio of two nicotine metabolites produced during smoking.[22] Participants with a normal metabolism had better abstinence rates when receiving varenicline, whereas those with a slow metabolism fared better on nicotine patches. Genetic factors and NMR were not assessed in the current study, but correcting for this ratio may change the predictors of success. From a

49

behavioural science perspective, another recent study found that financial incentives were associated with successful smoking cessation and that harnessing the individual’s aversion to loss in a cessation programme may encourage a change in smoking behaviour.[23] Our study has limited generalisability, as we enrolled mostly healthy persons without a history of psychiatric illness in the

January 2018, Print edition

RESEARCH

Table 2. Predictors of smoking cessation success at weeks 12 and 24 Univariate

Multivariate*

7-day PPAR Predictors

OR (95% CI)

CAR

7-day PPAR

CAR

p-value

OR (95% CI)

p-value

OR (95% CI)

p-value

OR (95% CI)

p-value

12 weeks (CAR 9 - 12 weeks) Combination therapy v. monotherapy

1.76 (1.20 - 2.57)

0.004§

1.80 (1.22 - 2.66)

0.003§

-

-

-

-

Age (≥50 v. <50), years

1.47 (1.00 - 2.15)

0.049§

1.40 (0.95 - 2.07)

0.09

1.49 (0.99 - 2.23)

0.056

1.52 (1.00 - 2.31)

0.049§

Sex (male v. female)

0.81 (0.55 - 1.20)

0.29

0.88 (0.59 - 1.31)

0.54

0.83 (0.55 - 1.24)

0.36

0.93 (0.62 - 1.41)

0.74

Cigarettes/day (<20 v. ≥20), n†

1.31 (0.89 - 1.93)

0.17

1.78 (1.19 - 2.67)

0.005§

1.29 (0.85 - 1.96)

0.23

1.86 (1.21 - 2.87)

0.005§

FTND (<7 v. ≥7)‡

2.20 (0.94 - 5.15)

0.07

1.90 (0.79 - 4.6)

0.15

1.80 (0.74 - 4.35)

0.19

1.39 (0.55 - 3.52)

0.48

Age started smoking (≥20 v. <20), years

1.39 (0.89 - 2.18)

0.15

1.32 (0.84 - 2.08)

0.23

1.25 (0.78 - 1.99)

0.36

1.17 (0.73 - 1.89)

0.51

Reinforcement assessment, PR v. NR

1.42 (0.81 - 2.49)

0.22

1.11 (0.62 - 1.97)

0.73

1.32 (0.74 - 2.34)

0.35

1.04 (0.58 - 1.89)

0.89

Reinforcement assessment, NR + PR v. NR

1.26 (0.77 - 2.06)

0.36

1.22 (0.74 - 2.02)

0.44

1.25 (0.75 - 2.08)

0.39

1.23 (0.73 - 2.08)

0.43

24 weeks (CAR 9 - 24 weeks) Combination therapy v. monotherapy

1.91 (1.28 - 2.84)

0.001§

2.06 (1.33 - 3.20)

0.001§

-

-

-

-

Age (≥50 v. <50), years

1.31 (0.88 - 1.94)

0.18

1.64 (1.07 - 2.53)

0.03§

1.41 (0.93 - 2.15)

0.11

1.79 (1.13 - 2.84)

0.01§

Sex (male v. female)

0.87 (0.58 - 1.30)

0.49

0.94 (0.61 - 1.47)

0.80

0.94 (0.62 - 1.44)

0.79

1.02 (0.64 - 1.62)

0.94

Cigarettes/day (<20 v. ≥20), n†

1.47 (0.98 - 2.21)

0.06

1.69 (1.07 - 2.65)

0.02§

1.38 (0.90 - 2.14)

0.14

1.83 (1.12 - 2.98)

0.02§

FTND (<7 v. ≥7)‡

2.03 (0.80 - 5.15)

0.14

1.59 (0.59 - 4.31)

0.36

1.59 (0.60 - 4.18)

0.35

1.21 (0.43 - 3.45)

0.72

Age started smoking (≥20 v. <20), years

1.46 (0.93 - 2.31)

0.10

1.30 (0.79 - 2.13)

0.30

1.42 (0.88 - 2.28)

0.15

1.17 (0.70 - 1.97)

0.54

Reinforcement assessment, PR v. NR

1.07 (0.60 - 1.90)

0.83

0.86 (0.46 - 1.63)

0.65

1.02 (0.56 - 1.86)

0.95

0.82 (0.42 - 1.58)

0.55

Reinforcement assessment, NR + PR v. NR

1.07 (0.64 - 1.78)

0.80

0.97 (0.56 - 1.69)

0.93

1.08 (0.64 - 1.83)

0.78

0.99 (0.56 - 1.76)

0.98

PPAR = point prevalence abstinence rate; CAR = continuous abstinence rate; OR = odds ratio; FTND = Fagerström test for nicotine dependence; NR = negative reinforcement (smoking to avoid a negative state); PR = positive reinforcement (smoking for pleasure); N/A = not applicable (never tried to quit). *Adjusted for treatment and all other factors in the model. † <20 cigarettes/day indicates light smokers; ≥20 cigarettes/day indicates heavy smokers. ‡ FTND <7 indicates less nicotine dependence, and ≥7 indicates heavy nicotine dependence. § Statistically significant.

previous 2 years. Our findings are nonetheless similar to those of studies resembling real-life situations.[7,15] The overall attrition rate of 36.1% may have affected the outcomes, but attrition was similar across the two treatment arms (33.3% in the active arm v.

38.8% in the placebo arm) and is comparable to that in previous studies. The results may have been underestimated by defining all participants who withdrew, defaulted on visits or were lost to follow-up as smokers, but this is in keeping with previous research and the high likelihood of treatment failure in such subjects.[19] We did not assess the effect of the financial cost of continued smoking on abstinence rates and smoking behaviour, but as our study was conducted during a worldwide economic recession, this may have

50

influenced the predictors of successful cessation attempts. We could also not specifically evaluate the potential impact of the level of education and smoking status of participants’ partners on smoking cessation.

Conclusion

Advanced age and lower daily cigarette consumption are associated with a higher likelihood of abstinence in patients who receive varenicline, regardless of the addition of NRT. Future studies should consider genetic factors, NMR, effect of personal resources, financial implications and local tobacco regulations, and possibly also novel ways of incentivising subjects.

January 2018, Print edition

RESEARCH

Acknowledgements. Prof. Eric D Bateman, Prof. Richard N van Zyl-Smit, Drs Axel Bruning, John A O’Brien, Clifford Smith, Mohamed S AbdoolGaffar and Shaunagh Emanuel, who contributed to the data collection of the original study.

Author contributions. All authors contributed to the study concept and design. FN had full access to all study data and performed analyses and interpretation with the assistance of EMI and TME. FN drafted the manuscript with support from all authors. The study was supervised by EMI. Funding. None.

Conflicts of interest. None.

1. World Health Organization. World Health Organization tobacco factsheet No. 339. http://www.who. int/mediacentre/factsheets/fs339/en/ (accessed 21 November 2017).

2. Centers for Disease Control and Prevention. Quitting smoking among adults – United States, 2001 - 2010.

MMWR Morb Mortal Wkly Rep 2011;60(44):1513-1519. https://doi.org/10.15585/mmwr.mm6552a1 3. Hughes JR, Keely J, Naud S. Shape of the relapse curve and long-term abstinence among untreated smokers. Addiction 2004;99(1):29-38. https://doi.org/10.1111/j.1360-0443.2004.00540.x 4. Hartmann-Boyce J, Stead LF, Cahill K, Lancaster T. Efficacy of interventions to combat tobacco addiction: Cochrane update of 2013 reviews. Addiction 2014;109(9):1414-1425. https://doi.org/10.1111/add.12633 5. Stead LF, Lancaster T. Combined pharmacotherapy and behavioural interventions for smoking cessation.

Cochrane Database Syst Rev 2012;(10):CD008286. https://doi.org/10.1002/14651858.cd008286.pub2 6. Caponnetto P, Polosa R. Common predictors of smoking cessation in clinical practice. Respir Med 2008;102(8):1182-1192. https://doi.org/10.1016/j.rmed.2008.02.017 7. Dorner TE, Trostl A, Womastek I, Groman E. Predictors of short-term success in smoking cessation in relation to attendance at a smoking cessation program. Nicotine Tob Res 2011;13(11):1068-1075. https://doi.org/10.1093/ntr/ntr179 8. Hymowitz N, Cummings KM, Hyland A, Lynn WR, Pechacek TF, Hartwell TD. Predictors of smoking cessation in a cohort of adult smokers followed for five years. Tob Control 1997;6(Suppl 2):S57-S62. https://doi.org/10.1136/tc.6.suppl_2.s57 9. Iliceto P, Fino E, Pasquariello S, D’Angelo Di Paola ME, Enea D. Predictors of success in smoking cessation among Italian adults motivated to quit. J Subst Abuse Treat 2013;44(5):534-540. https://doi. org/10.1016/j.jsat.2012.12.004 10. Monso E, Campbell J, Tonnesen P, Gustavsson G, Morera J. Sociodemographic predictors of success in smoking intervention. Tob Control 2001;10(2):165-169. https://doi.org/10.1136/tc.10.2.165 11. Myung SK, Seo HG, Park S, et al. Sociodemographic and smoking behavioral predictors associated with smoking cessation according to follow-up periods: A randomized, double-blind, placebocontrolled trial of transdermal nicotine patches. J Korean Med Sci 2007;22(6):1065-1070. https://doi. org/10.3346/jkms.2007.22.6.1065

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12. Schuck K, Otten R, Kleinjan M, Bricker JB, Engels RC. Predictors of cessation treatment outcome and treatment moderators among smoking parents receiving quitline counselling or self-help material.

Prev Med 2014;69:126-131. https://doi.org/10.1016/j.ypmed.2014.09.014 13. Smit ES, Hoving C, Schelleman-Offermans K, West R, de Vries H. Predictors of successful and unsuccessful quit attempts among smokers motivated to quit. Addict Behav 2014;39(9):1318-1324. https://doi.org/10.1016/j.addbeh.2014.04.017 14. Stolz D, Scherr A, Seiffert B, et al. Predictors of success for smoking cessation at the workplace: A longitudinal study. Respiration 2014;87(1):18-25. https://doi.org/10.1159/000346646 15. Wee LH, Shahab L, Bulgiba A, West R. Stop smoking clinics in Malaysia: Characteristics of attendees and predictors of success. Addict Behav 2011;36(4):400-403. https://doi.org/10.1016/j. addbeh.2010.11.011 16. Huang CL, Lin HH, Wang HH. Evaluating screening performances of the Fagerstrom tolerance questionnaire, the Fagerstrom test for nicotine dependence and the heavy smoking index among Taiwanese male smokers. J Clin Nurs 2008;17(7):884-890. https://doi.org/10.1111/j.1365-2702.2007.02054.x 17. Kaleta D, Korytkowski P, Makowiec-Dabrowska T, Usidame B, Bak-Romaniszyn L, Fronczak A. Predictors of long-term smoking cessation: Results from the global adult tobacco survey in Poland (2009 - 2010). BMC Public Health 2012;12(1):1020. https://doi.org/10.1186/1471-2458-12-1020 18. Fagerström K, Carlos J, Mochales J, Hans G. Can smoking for positive or negative reinforcement together with dependence help us better diagnose smokers? J Smoking Cessation 2007;2(1):5-7. https://doi.org/10.1375/jsc.2.1.5 19. Ebbert JO, Hatsukami DK, Croghan IT, et al. Combination varenicline and bupropion SR for tobaccodependence treatment in cigarette smokers: A randomized trial. JAMA 2014;311(2):155-163. https:// doi.org/10.1001/jama.2013.283185 20. Koegelenberg CF, Noor F, Bateman ED, et al. Efficacy of varenicline combined with nicotine replacement therapy vs varenicline alone for smoking cessation: A randomized clinical trial. JAMA 2014;312(2):155-161. https://doi.org/10.1001/jama.2014.7195 21. Chen L, Baker TB, Piper ME, et al. Interplay of genetic risk factors (CHRNA5-CHRNA3-CHRNB4) and cessation treatments in smoking cessation success. Am J Psychiatry 2012;169(7):735-742. https:// doi.org/10.1176/appi.ajp.2012.11101545 22. Lerman C, Schnoll RA, Hawk LW Jr, et al. Use of the nicotine metabolite ratio as a genetically informed biomarker of response to nicotine patch or varenicline for smoking cessation: A randomised, doubleblind placebo-controlled trial. Lancet Respir Med 2015;3(2):131-138. https://doi.org/10.1016/s22132600(14)70294-2 23. Halpern SD, French B, Small DS, et al. Randomized trial of four financial-incentive programs for smoking cessation. N Engl J Med 2015;372(22):2108-2117. https://doi.org/10.1056/nejmoa1414293

Accepted 26 September 2017.

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RESEARCH

Good correlation between the Afinion AS100 analyser and the ABX Pentra 400 analyser for the measurement of glycosylated haemoglobin and lipid levels in older adults in Durban, South Africa N S Abbai,1 PhD; M Nyirenda,2 PhD; T Reddy,3 PhD; G Ramjee,2,4,5 PhD; on behalf of the SHIOP team School of Clinical Medicine Research Laboratory, Nelson Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa HIV Prevention Research Unit, South African Medical Research Council, Durban, South Africa 3 Biostatistics Unit, South African Medical Research Council, Durban, South Africa 4 Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, UK 5 Department of Global Health, School of Medicine, University of Washington, USA 1 2

Corresponding author: N S Abbai (abbain@ukzn.ac.za) Background. The Afinion AS100 analyser is a small bench-top, multi-assay, point-of-care (POC) analyser that is able to measure glycated haemoglobin (HbA1c) and lipid levels.

Objective. To assess performance of the Afinion analyser compared with a reference laboratory test for the measurement of HbA1c and lipid levels.

Method. The study involved men and women enrolled in a cross-sectional study, Sexual health, HIV infection and comorbidity with non-communicable diseases among Older Persons (SHIOP), which was conducted from February to May 2016. Whole blood was drawn aseptically by a trained study nurse into a serum separator gel tube and an ethylenediaminetetra-acetic acid (EDTA) tube. The EDTA whole blood was used to measure HbA1c levels, and serum to measure total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), lowdensity lipoprotein cholesterol (LDL-C) and triglyceride levels. Linâ&#x20AC;&#x2122;s correlation coefficient was used to assess the agreement between the Afinion and ABX Pentra 400 analysers for each marker.

Results. A total of 435 older individuals were included in the study. The proportion of HbA1c results that were correctly classified by the Afinion analyser was 92.2%. Bland-Altman analysis and linear regression analysis showed a very good agreement (correlation concordance 0.89) between the two analysers for the measurement of HbA1c. The two-way scatter plot for TC showed a substantial correlation (0.80).

However, a total of 69 cholesterol results that were within the normal range on the Pentra were misclassified as abnormal on the Afinion. The readings obtained for HDL-C levels with the Afinion were shown to be slightly overestimated when compared with the Pentra. However, correlation for HDL-C on the two analysers was 0.93, indicating an almost perfect agreement. Seventy-four LDL-C results were erroneously classified as abnormal on the Afinion but were within the normal range on the Pentra, resulting in a substantial correlation of 0.75. An excellent agreement was observed between triglyceride measurements (0.99).

Conclusion. This study supports the use of the Afinion AS100 analyser in POC testing for the measurement of HbA1c, triglycerides and HDL-C in a South African setting.

S Afr Med J 2018;108(1):50-55. DOI:10.7196/SAMJ.2018.v108i1.12548

Globally, 18 million people die annually from cardiovascular disease (CVD).[1] Findings from the INTERHEART Africa study[2] indicated that the highest number of premature acute myocardial infarctions in the world occur in sub-Saharan Africa, as a result of lack of early detection of CVD and effective management of risk factors.[3] Various point-of-care (POC) tests (mainly finger-prick tests) are available that provide results ranging from total cholesterol (TC) alone to a full lipogram. However, the limitation with many of these tests is that the results obtained are not adequate to commit a patient to a lifetime of therapy. In addition, finger-prick testing that measures TC alone will not detect raised triglycerides.[3] Patients with diabetes mellitus (DM) are at high risk of developing CVD, with increased associated mortality.[4] In many primary care settings, testing for glycaemic control involves sending a blood sample away for laboratory testing and waiting a number of days for the result to be returned. This delays patient counselling and treatment

52

adjustments based on glycated haemoglobin (HbA1c) levels, and sometimes follow-up can be lost completely.[4] Measurement of HbA1c levels using POC tests provides rapid results, improving patient management.[4-6] Findings from a randomised controlled trial of POC testing in an Australian setting showed that POC tests of samples from patients with established hyperlipidaemia or established type 1 or type 2 DM, or taking anticoagulant therapy, had the same clinical effectiveness as testing in a pathology laboratory.[7] Reports have also shown that access to a POC test is associated with improved treatment adherence.[8] The Afinion AS100 analyser (Alere, South Africa (SA)) is a small bench-top, multi-assay analyser for in vitro diagnostic POC testing using whole blood, plasma or urine samples. The unique feature of the analyser is that both the HbA1c and the lipid panel test can be done on one instrument. The turnaround time from collection of samples to all results being available to the patient is <30 minutes.

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RESEARCH

Preliminary results from a recent study on sexual health and chronic morbidities in people aged ≥50 years conducted in the Chatsworth and Botha’s Hill areas of Durban, SA, found that >70% of older adults had elevated blood glucose levels indicating prediabetes and diabetes, and that over half of the study participants had elevated blood pressure readings (unpublished data). In addition, >15% of the study participants were HIV-infected, which is higher than the national average.[9] There is therefore an urgent need to respond to the growing twin health challenges of HIV and non-communicable diseases among older adults.

Objective

To evaluate the performance of the lipid and HbA1c panels of the Afinion AS100 analyser compared with standard laboratory methods in a population of HIV-positive and HIV-negative older adults.

Methods

Study participants

The study was a sub-analysis of a cross-sectional study, Sexual health, HIV infection and comorbidity with non-communicable diseases among Older Persons (SHIOP). The SHIOP study enrolled both men and women and was conducted between February and May 2016.

The primary aim of SHIOP was to describe sexuality, sexual health and the comorbidity of HIV and sexually transmitted infections with chronic non-communicable diseases in adults aged ≥50 years in a setting of high HIV prevalence. Participants were recruited from two sub-areas of Durban (Botha’s Hill and Chatsworth), SA. Botha’s Hill is a semi-rural area located west of Durban, and Chatsworth is an urban setting located south of Durban. The study eligibility criteria included age ≥50 years, being willing and able to provide written informed consent and able to communicate in English or isiZulu, and not being terminally ill or cognitively impaired.

Ethical considerations

As part of the study procedure, all study participants provided written informed consent prior to enrolment. Participants who were illiterate (i.e. unable to read or write English or isiZulu), were assisted by an impartial literate witness during the informed consent process. The participant used a thumbprint to mark the informed consent form and the impartial witness signed to confirm that the participant provided informed consent. We followed the usual procedure adopted in large-scale multi-site HIV prevention clinical trials. Ethical approval for SHIOP was obtained from the South African Medical Research Council (SAMRC) Ethics Committee (ref. no. EC030-9/2015).

Sample collection and processing

All eligible participants were requested to provide a venous blood sample for laboratory testing. Whole blood was drawn aseptically by a trained study nurse into a serum separator gel tube and an ethylenediaminetetra-acetic acid (EDTA) tube. The serum gel tube was centrifuged at the research clinics and the separated serum used for measuring lipid levels, and the EDTA whole-blood tube was used to measure HbA1c levels using the POC Afinion AS100 analyser, which was placed at the research clinics. The remaining serum and EDTA whole blood was transported on ice on the day of collection to the SAMRC HIV Prevention Research Unit’s central routine laboratory for measurement of blood glucose and lipid levels on the ABX Pentra 400 analyser (Horiba, USA). All testing was performed by trained medical technologists.

54

POC testing using the Afinion analyser

HbA1c measurements HbA1c levels were measured using 1.5 µL of EDTA whole blood. The Afinion works on the boronic acid affinity test principle and is not affected by haemoglobin variants. The analyser claims a 4.0 - 15.0% (20.0 - 140.0 mmol/mol) HbA1c measuring range. The assay time was ~3 minutes, and controls with HbA1c-specific target values were included in the assay runs.

Lipid measurements TC, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides were measured using 1.5 µL of serum. The assay time was ~8 minutes, and ready-touse control material was included in the assay runs. The measuring ranges for lipids using the Afinion analyser were as follows: TC 2.59 12.95 mmol/L, HDL-C 0.39 - 2.59 mmol/L, and triglycerides 0.51 7.34 mmol/L. LDL-C was a computed value using the Friedewald formula[10,11] LDL-C (mmol/L) = TC – HDL-C – triglycerides/2.2.

Reference laboratory testing

The Pentra analyser was used as the reference laboratory test according to the manufacturer’s instructions. According to SA national guidelines, the reference (normal) range for testing and management of lipids is as follows: TC <4.5 mmol/L, LDL-C <2.5 mmol/L, HDL-C 1.0 mmol/L (men) and ≥1.2 mmol/L (women), and triglycerides <1.70 mmol/L. The diagnostic cut-off for HbA1c is 6.5% (or 48 mmol/mol). We used these reference ranges to compare participants categorised as normal v. abnormal on the Pentra and Afinion for each marker.

Data analysis

Lin’s correlation coefficient was used to assess the agreement between the Afinion and Pentra analysers for each marker. The mean bias was calculated, as well as the 95% limits of agreement to quantify the difference between a reading on the Afinion and the Pentra. Results were graphically depicted using Bland-Altman plots and two-way scatterplots. The coefficients were classified as indicating poor (<0.69), fair (0.70 - 0.79), good (0.80 - 0.89) or excellent (0.90 - 1.00) correlation.

Results

Sample description

We obtained data on 435 older adults from Durban, SA. The overall median age of the study participants was 61 years (interquartile range 12), with male participants being slightly older than female participants (62 v. 60 years). Using World Health Organization categorisations of clinically assessed weight and height, ~60% of study participants were overweight or obese, and ~40% (n=172) were hypertensive. Furthermore, 16.1% of participants (n=70) were HIVpositive, of whom 84.3% (n=59) knew their HIV status prior to study participation (data not shown).

Diagnostic accuracy of the Afinion v. the Pentra analysers

Table 1 describes the diagnostic performance of the Afinion analyser for the measurement of HbA1c, TC, LDL-C, HDL-C and triglyceride levels in comparison with the Pentra. In addition, the differences between the Afinion and Pentra measurements using Bland-Altman plots are described in Table 2 and Figs 1 - 5.

HbA1c levels The proportion of HbA1c results that were correctly classified by the Afinion analyser was 92.2% (Table 1). We also observed high diagnostic

January 2018, Print edition

RESEARCH

Table 1. Diagnostic accuracy of the Afinion analyser compared with the Pentra, using target levels as cutoffs Pentra

HbA1c

TC

LDL-C

HDL-C, males

HDL-C, females

TG

Afinion Normal Abnormal Afinion Normal Abnormal Afinion Normal Abnormal Afinion Normal Abnormal Afinion Normal Abnormal Afinion Normal Abnormal

Afinion

Normal, n

Abnormal, n

Correctly classified, %

214 17

7 70

92.2

90.9

92.6

122 69

0 142

79.3

100

63.9

126 74

1 113

76.1

99.1

63.0

12 7

2 78

90.9

97.5

63.2

76 18

5 129

89.9

96.3

80.9

158 0

15 154

95.4

91.1

100

Sensitivity, %

Specificity, %

HbA1c = glycated haemoglobin; TC = total cholesterol; HDL-C = high-density cholesterol; LDL-C = low-density cholesterol; TG = triglycerides.

Table 2. Differences between the Afinion and Pentra measurements using BA plots HbA1c TC LDL-C HDL-C TG

N 308 333 314 327 327

Mean bias (SD) 0.224 (0.840) 0.569 (0.377) 0.528 (0.385) 0.089 (0.095) –0.124 (0.127)

95% BA limits of agreement –1.421 - 1.870 –0.169 - 1.307 –0.227 - 1.283 –0.097 - 0.275 –0.373 - 0.125

Concordance correlation 0.89 0.80 0.75 0.93 0.99

BA = Bland-Altman; SD = standard deviation; HbA1c = glycated haemoglobin; TC = total cholesterol; HDL-C = high-density cholesterol; LDL-C = low-density cholesterol; TG = trigycerides.

15

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Fig. 1. Scatterplot and regression line of HbA1c values (%) produced by the Afinion (A) and Pentra (P) analysers. The Bland-Altman study and linear regression analysis showed good agreement between the 3 10 two analysers. (HbA1c = glycated haemoglobin.)

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the two test results 55 January 2018, Print edition

The readings obtained for HDL-C levels with6 the Afinion were shown to be slightly overestimated compared with the Pentra (mean bias 0.089). The correlation between 4 the two methods was 0.93, indicating excelTC A

2 in a sensitivity of 100%. The mean bias observed for TC measurements between 1 the Afinion and the Pentra analysers was 0.569, with 95% limits of agreement of –0.1690- 1.307 (Table 2).

Choles_A

Lipid levels The proportion of TC results that were correctly classified by the Afinion analyser was 79.3% (Table 1). The TC two-way scatter plot represented in Fig. 2 showed a good correlation (0.80) between the two analysers. However, a total of 69 TC results that were within the normal range on the Pentra were misclassified as abnormal on the Afinion, leading to a poor specificity of 63.9%. However, the Afinion correctly classified all 142 results that were in the abnormal range on the Pentra, resulting

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accuracy of the Afinion in detecting results that were above target levels, as indicated by both sensitivity and specificity >90%.

According to our analysis, higher values for HbA1c levels were detected with the Afinion than with the Pentra. Bland-Altman analysis and linear regression analysis showed an almost excellent agreement between the two analysers (Fig. 1). A correlation of 0.89 was observed (Table 2).

2 2

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Fig. 2. Scatterplot and regression line of TC values (mmol/L) produced by the Afinion (A) and Pentra (P) analysers. The Bland-Altman study and linear regression analysis showed a substantial agreement between the two analysers. (TC = total cholesterol.)

2 0

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Observed average agreement 95% limits of agreement Reduced major axis perfect concordance Fig. 3. Scatterplot and regression line of HDL-C values (mmol/L) producedLine byofthe Afinion (A) and = 0 isanalysers. the line of perfect agreement Pentra y3(P) Theaverage Bland-Altman study and linear regression analysis showed an almost perfect 6 between the two test results agreement between the two analysers. (HDL-C = high-density lipoprotein cholesterol.)

3 1

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Fig. 4. Scatterplot and regression line of LDL-C values (mmol/L) produced by the Afinion (A) and Pentra (P) analysers. The Bland-Altman study and linear regression analysis showed a substantial agreement between the two analysers. (LDL-C = low-density lipoprotein cholesterol.)

lent agreement between the two analysers (Fig. 3). Misclassification of HDL-C results was low in both males and females. The specificity of the Afinion test was lower in males, 7 of 19 HDL results that were below the target levels on the Pentra being incorrectly classified as normal by the Afinion.

poor specificity was observed, the sensitivity of the Afinion was 99.1%, indicating that the analyser performs well in detecting values above the target range. However, it is important to note that the LDL-C was a computed value using the Friedewald formula, and because it was not measured directly it may not be a direct reflection of the accuracy of the analysers used. Despite this, a fair correlation of 0.75 was observed between the two analysers (Fig. 4).

Excellent agreement was observed between triglycerides measured on the Afinion and the Pentra, evidenced by the mean bias of 0.124 and almost perfect agreement between the two analysers, with a correlation of 0.99 (Fig. 5). When categorising values according to target levels, excellent diagnostic accuracy was observed, with a sensitivity of 91.1% and specificity of 100%.

LDL-C values tended to be overestimated by the Afinion, with a mean bias of 0.528.

According to the analysis, 74 LDL-C results were erroneously classified as abnormal according to the Afinion but were within the normal range on the Pentra, giving a specificity of 63.0% (Table 1). Although

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January 2018, Print edition

The objective of this study was to evaluate the performance of the Afinion AS100 analyser compared with a standard laboratory method for the measurements of lipids and HbA1c in a population of HIVpositive and HIV-negative older adults.

Overall, Bland-Altman plots revealed a good correlation between the Afinion and Pentra 400 analysers for the measurement of HbA1c levels. In addition, the Afinion was able to correctly classify >90% of the samples. With regard to the measurement of lipid levels, the results showed very good correlation between the Afinion and the Pentra, with almost perfect correlations noted for HDL-C and triglycerides.

HbA1c measurement is an important tool in the management of patients with DM. Evidence for the utility of HbA1c for the diagnosis and detection of DM in an SA population has been described

by Hird et al.[12] However, in SA primary healthcare facilities, random blood glucose measurement is commonly used to make clinical decisions with regard to glycaemic control, as HbA1c tests have not been done or the results are not yet available or are out of date.[13] In addition, the DiabCare Africa study found that <50% of patients with DM had had an HbA1c test as part of their management during the previous year. [12] To this end, the availability of a rapid and accurate method of HbA1c evaluation is of paramount importance.[14] According to Gaziano et al.,[15] since the late 1990s, deaths due to non-communicable diseases have increased steadily in adults aged ≥50 years.

A number of risk factors contributing to mortality, such as hypertension, increased

0.5

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RESEARCH

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Fig. 5. Scatterplot and regression line of TG values (mmol/L) produced by the Afinion (A) and Pentra (P) analysers. The Bland-Altman study and linear regression analysis showed an almost perfect agreement between the two analysers. (TG = triglycerides.)

smoking prevalence, dietary changes and obesity, have been identified. These risk factors have also led to increases in symptomatic cardiovascular conditions such as stroke, ischaemic heart disease and DM, to which health policy makers have yet to provide an effective response. The global diagnostics industry is growing rapidly, since new diagnostic platforms have advanced modern healthcare in terms of the accuracy (sensitivity, specificity and reproducibility), speed and scope of diagnoses.[16] The present study revealed a good correlation between the Afinion and Pentra analysers for the measurement of HbA1c levels. Our findings are supported by other published studies. A study by LentersWestra et al.[17] evaluated seven point-of-care analysers for HbA1c (DCA Vantage, Afinion, Innova Star, Quo-Lab, Quo-Test, Cobas B101, B-analyst). The Afinion passed the National Glycohemoglobin Standardization Program (NGSP) criteria with two different lot numbers. In addition, the Afinion remained unaffected by the common haemoglobin variants. The study concluded that the Afinion met the performance criteria for HbA1c.[12] Previous studies on the diagnostic accuracy of the Afinion have been conducted on paediatric samples, as described by Wood et al.[18] In this study, the Afinion’s accuracy and precision was compared with highperformance liquid chromatography (HPLC) and DCA methods. The findings showed that the Afinion generated higher HbA1c results when compared with HPLC, while the DCA produced lower values. At high HbA1c levels, the DCA tended to read lower than HPLC, but the Afinion’s accuracy did not vary according to HbA1c.[18] Jain et al.[5] evaluated the performance of the Afinion in a DM and CVD screening programme. In this study, the Afinion and the reference laboratory

method identified similar numbers of new patients with suspected DM. In the present study, the researchers also found that the Afinion detected HbA1c levels that were above target levels. Similar findings were reported by Jain et al.,[5] with the Afinion being shown to overestimate HbA1c levels for certain samples. However, similar to the present study, the overestimation did not affect the overall diagnostic performance of the instrument. The Afinion is still recommended as a useful screening instrument for DM in a community setting, but diagnosis needs to be confirmed by an NGSP-certified method.[5] In SA, since the prevalence of familial hypercholesterolaemia is as high as 1 in 100 in some communities, ideally everyone should undergo a full lipogram, or at minimum TC/LDL-C measurement, at least once in young adulthood (from 20 years of age).[3] Although the measurement of lipids in the blood is a widely accepted biochemical marker for cardiovascular risk assessment and management in primary healthcare,[19,20] testing performed in hospital laboratories may result in excess travel for the patient, sample loss and repeat clinic visits.[19] A survey of the literature showed a limited number of studies that have investigated the performance of the Afinion analyser in measuring lipid levels.

Our study is one of two suggesting that the Afinion is an acceptable POC tool for the measurement of lipids. Our findings support those of Jain et al.,[5] who compared the Afinion with the Cholestech LDX for the measurement of TC, HDL-C and triglyceride levels. The Afinion was shown to meet the performance criteria recommended by the National Education Cholestrol Program in the UK for TC and HDL-C measurements.[5] In the present study, the readings obtained for HDL-C levels with the Afinion were shown

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January 2018, Print edition

to be slightly overestimated compared with the Pentra. Similarly, the Afinion was shown to overestimate HDL-C levels in the study by Jain et al.[5] Despite the overestimated values in the present study, overall the correlation between the two instruments used showed an excellent level of agreement. Our study adds to the growing body of evidence regarding the diagnostic performance of the Afinion for the measurement of lipid levels.

Study limitations

A limitation of this study is that the testing was performed in a laboratory setting by trained laboratory personnel and is not truly representative of a primary healthcare clinic setting. Field studies at primary healthcare facilities using healthcare workers (nurses) to perform the testing could be a future research direction. The study was also limited to a targeted population (older individuals). We have provided a strong rationale of why we chose to work with this population. However, future studies may need to be conducted in a more general population group. Cost-effectiveness studies on the use of the Afinion in resource-poor settings are needed.

Conclusion

The study is unique in that it provides the first report on the diagnostic performance of the Afinion AS100 analyser in measuring HbA1c and lipid levels in a population of HIV-infected and uninfected adults aged ≥50 years in KwaZulu-Natal Province, SA. In our study population there were no significant differences in HbA1c and lipid levels according to HIV status. In addition, there have been no reports demonstrating the role of HIV infection and antiretroviral use in affecting the diagnostic performance of point-of-care instruments for HbA1c and lipid levels. This study supports the use of the Afinion as a POC test for the measurement of HbA1c, triglycerides and HDL-C in an SA setting.

Acknowledgements. We thank all the men and women who participated in the SHIOP study, and the SHIOP study teams at the SAMRC HIV Prevention Research Unit in Durban.

Author contributions. NSA and MN developed the concept, NSA, MN and TR performed the data interpretations, TR completed the statistical analysis, and NSA wrote the article with input from MN, TR and GR. Funding. This study was supported by the SAMRC HIV Prevention Research Unit.

Conflicts of interest. None.

RESEARCH

1. Yusuf S, Rangarajan S, Teo K, et al. Cardiovascular risk and events in 17 low-, middle-, and highincome countries. N Engl J Med 2014;371(9):818-827. https://doi.org/10.1056/NEJMoa1311890 2. Steyn K, Sliwa K, Hawken S, et al. Risk factors associated with myocardial infarction in Africa: The INTERHEART Africa study. Circulation 2005;112(23):3554-3561. https://doi.org/10.1161/ CIRCULATIONAHA.105.563452 3. Klug EQ, Raal F, Marais A, et al. South African Dyslipidaemia Guideline Consensus Statement: A joint statement from the South African Heart Association (SA Heart) and the Lipid and Atherosclerosis Society of Southern Africa (LASSA). S Afr Fam Pract 2013;55(1):9-18. https://doi.org/10.1080/2078 6204.2013.10874296 4. Khunti K, Stone MA, Burden AC, et al. Randomised controlled trial of near-patient testing for glycated haemoglobin in people with type 2 diabetes mellitus. Br J Gen Pract 2006;56(528):511-517.

5. Jain A, Rao N, Sharifi M, et al. Evaluation of the point of care Afinion AS100 analyser in a community setting. Ann Clin Biochem 2016;54(3):331-341. https://doi.org/10.1177/0004563216661737 6. Schwartz KL, Monsur JC, Bartoces MG, West PA, Neale AV. Correlation of same-visit HbA1c test with laboratory-based measurements: A MetroNet study. BMC Fam Pract 2005;6(1):28. https://doi. org/10.1186/1471-2296-6-28 7. Bubner TK, Laurence CO, Gialamas A, et al. Effectiveness of point-of-care testing for therapeutic control of chronic conditions: Results from the PoCT in General Practice Trial. Med J Aust 2009;190(11):624-626. https://doi.org/10.1186/1471-2296-6-28 8. PlĂźddemann A, Thompson M, Price CP, Wolstenholme J, Heneghan C. Point-of-care testing for the analysis of lipid panels: Primary care diagnostic technology update. Br J Gen Pract 2012;62(596):e224-e226. https://doi.org/10.3399/bjgp12X630241 9. Simbayi L, Shisana O, Rehle T, et al. South African National HIV Prevalence, Incidence and Behaviour Survey, 2012. Pretoria: Human Sciences Research Council, 2014.

10. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18(6):499-502.

11. Johnson R, McNutt P, MacMahon S, Robson R. Use of the Friedewald formula to estimate LDLcholesterol in patients with chronic renal failure on dialysis. Clin Chem 1997;43(11):2183-2184.

12. Hird TR, Pirie FJ, Esterhuizen TM, et al. Burden of diabetes and first evidence for the utility of HbA1c for diagnosis and detection of diabetes in urban black South Africans: The Durban Diabetes Study.

PLoS One 2016;11(8):e0161966. https://doi.org/10.1371/journal.pone.0161966

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13. Mash R, Ugoagwu A, Vos C, Rensburg M, Erasmus R. Evaluating point-of-care testing for glycosylated haemoglobin in public sector primary care facilities in the Western Cape, South Africa. S Afr Med J 2016;106(12):1236-1240. https://doi.org/10.7196/SAMJ.2016.v106.i12.10728 14. Motta LA, Shephard MDS, Brink J, Lawson S, Rheeder P. Point-of-care testing improves diabetes management in a primary care clinic in South Africa. Prim Care Diabetes 2017;11(3):248-253. https:// doi.org/10.1016/j.pcd.2016.09.008 15. Gaziano TA, Abrahams-Gessel S, Gomez-Olive F, et al. Cardiometabolic risk in a population of older adults with multiple co-morbidities in rural South Africa: The HAALSI (Health and Aging in Africa: Longitudinal studies of INDEPTH communities) study. BMC Public Health 2017;17(1):206. https:// doi.org/10.1186/s12889-017-4117-y 16. Thompson M, Weigl B, Fitzpatrick A, Ide N. More than just accuracy: A novel method to incorporate multiple test attributes in evaluating diagnostic tests including point of care tests. IEEE J Transl Eng Health Med 2016;4:1-8. https://doi.org/10.1109/JTEHM.2016.2570222 17. Lenters-Westra E, Slingerland RJ. Three of 7 hemoglobin A1c point-of-care instruments do not meet generally accepted analytical performance criteria. Clin Chem 2014;60(8):1062-1072. https://doi. org/10.1373/clinchem.2014.224311 18. Wood JR, Kaminski BM, Kollman C, et al. Accuracy and precision of the Axis-Shield Afinion hemoglobin A1c measurement device. J Diabetes Sci Technol 2012;6(2):380-386. https://doi. org/10.1177/193229681200600224 19. Carey M, Markham C, Gaffney P, Boran G, Maher V. Validation of a point of care lipid analyser using a hospital based reference laboratory. Ir J Med Sci 2006;175:30. https://doi.org/10.1007/BF03167964 20. Shephard MD. Comparative performance of two point-of-care analysers for lipid testing. Clin Lab 2007;53(9-12):561-566.

Accepted 3 August 2017.

January 2018, Print edition

This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

RESEARCH

Anaemia, renal dysfunction and in-hospital outcomes in patients with heart failure in Botswana J C Mwita,1,2 MD, MMed, MSc; M G M D Magafu,3 MD, MPHM, MPH, MSc, PhD; B Omech,1,2 MB ChB, MMed; M J Dewhurst,4 MD, FRCP; Y Mashalla,5 MD, PhD Department of Internal Medicine, Faculty of Medicine, University of Botswana, Gaborone, Botswana Department of Internal Medicine, Princess Marina Hospital, Gaborone, Botswana 3 Department of Family Medicine and Public Health, Faculty of Medicine, University of Botswana, Gaborone, Botswana 4 Department of Cardiology, University Hospital Hartlepool, UK 5 Department of Biomedical Sciences, Faculty of Medicine, University of Botswana, Gaborone, Botswana 1 2

Corresponding author: J C Mwita (mwitajc@ub.ac.bw) Background. Anaemia and renal dysfunction are associated with an increased morbidity and mortality in heart failure (HF) patients.

Objective. To estimate the frequency and impact of anaemia and renal dysfunction on in-hospital outcomes in patients with HF. Methods. A total of 193 consecutive patients with HF admitted to Princess Marina Hospital, Gaborone, Botswana, from February 2014 to February 2015, were studied. Anaemia was defined as haemoglobin <13 g/dL for men and <12 g/dL for women. Renal dysfunction was defined by an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2, calculated by the simplified Modification of Diet in Renal Disease formula. The in-hospital outcomes included length of hospital stay and mortality.

Results. The mean (standard deviation (SD)) age was 54.2 (17.1) years and 53.9% of the patients were men. The overall median eGFR was 75.9 mL/min/1.73 m2 and renal dysfunction was detected in 60 (31.1%) patients. Renal dysfunction was associated with hypertension (p=0.01), diabetes mellitus (p=0.01) and a lower haemoglobin level (p=0.008). The mean (SD) haemoglobin was 12.0 (3.0) g/dL and 54.9% of the patients were anaemic. Microcytic, normocytic and macrocytic anaemia were found in 32.1%, 57.5% and 10.4% of patients, respectively.

The mean (SD) haemoglobin level for males was significantly higher than for females (12.4 (3.3) g/dL v. 11.5 (2.5) g/dL; p=0.038). Anaemia was more common in patients with diabetes (p=0.028) and in those with increased left ventricular ejection fraction (p=0.005). Neither renal dysfunction nor anaemia was significantly associated with the length of hospital stay or in-hospital mortality.

Conclusion. Anaemia and renal dysfunction are prevalent in HF patients, but neither was an independent predictor of length of stay or in-hospital mortality in this population. These findings indicate that HF data in developed countries may not apply to countries in subSaharan Africa, and call for more studies to be done in this region.

S Afr Med J 2018;108(1):56-60. DOI:10.7196/SAMJ.2018.v108i1.12686

Full article available online at https://doi.org/10.7196/SAMJ.2018.v108i1.12686

59

January 2018, Print edition

This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

RESEARCH

Keeping our heads above water: A systematic review of fatal drowning in South Africa C J Saunders,1,2,3 BSc (Med) Hons, PhD; D Sewduth,2 MEd, MDP; N Naidoo,3 N Dip AEC, BTech EMC, H Dip Ed, MPH Division of Emergency Medicine, Department of Surgery, Faculty of Health Sciences, University of Cape Town, South Africa Lifesaving South Africa, Durban, South Africa 3 Department of Emergency Medical Sciences, Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa 1 2

Corresponding author: C J Saunders (c.saunders@uct.ac.za) Background. Drowning is defined as the process of experiencing respiratory impairment from submersion/immersion in liquid, and can have one of three outcomes â&#x20AC;&#x201C; no morbidity, morbidity or mortality. The World Health Organization African region accounts for approximately 20% of global drowning, with a drowning mortality rate of 13.1 per 100 000 population. The strategic implementation of intervention programmes driven by evidence-based decisions is of prime importance in resource-limited settings such as South Africa (SA).

Objective. To review the available epidemiological data on fatal drowning in SA in order to identify gaps in the current knowledge base and priority intervention areas.

Methods. A systematic review of published literature was conducted to review the available epidemiological data describing fatal drowning in SA. In addition, an internet search for grey literature, including technical reports, describing SA fatal drowning epidemiology was conducted.

Results. A total of 13 published research articles and 27 reports obtained through a grey literature search met the inclusion and exclusion criteria. These 40 articles and reports covered data collection periods between 1995 and 2016, and were largely focused on urban settings.

The fatal drowning burden in SA is stable at approximately 3.0 per 100Â 000 population, but is increasing as a proportion of all non-natural deaths. Drowning mortality rates are high in children aged <15 years, particularly in those aged <5.

Conclusions. This review suggests that SA drowning prevention initiatives are currently confined to the early stages of an effective injury prevention strategy. The distribution of mortality across age groups and drowning location differs substantially between urban centres and provinces. There is therefore a need for detailed drowning surveillance to monitor national trends and identify risk factors in all SA communities.

S Afr Med J 2018;108(1):61-68. DOI:10.7196/SAMJ.2018.v108i1.11090

Full article available online at https://doi.org/10.7196/SAMJ.2018.v108i1.11090

60

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CPD questionnaires must be completed online at www.mpconsulting.co.za.

True (A) or false (B): SAMJ â&#x20AC;&#x2DC;Covering doctorsâ&#x20AC;&#x2122; standing in for unavailable colleagues: What is the legal position?

1. Covering doctors who begin to issue telephonic instructions to nurses or other healthcare practitioners regarding the treatment of the patients they are covering are in the same position as any other doctors treating patients.

2. Covering doctors cannot rely on telephone instructions for long periods of time when the patientâ&#x20AC;&#x2122;s health may be in danger, without seeing the patient.

Self-reported alcohol use and binge drinking in South Africa (SA): Evidence from the National Income Dynamics Study, 2014 - 2015 3. In 2010, the World Health Organization (WHO) African Region, reported that SA had one of the lowest per capita levels of alcohol consumption among people aged >15 years.

4. The harmful drinking practices in SA relate more to the manner and circumstances under which alcohol is consumed than the prevalence of drinking.

Predictors of treatment success in smoking cessation with varenicline combined with nicotine replacement therapy v. varenicline alone 5. The World Health Organization (WHO) reported that nearly 6 million tobacco-related deaths occur annually.

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Keeping our heads above water: A systematic review of fatal drowning in SA 7. In 2012, drowning mortality in the WHO African region accounted for 20% of drowning globally.

8. Non-fatal drowning incidents are often associated with significant morbidity and a socioeconomic burden from severe pulmonary and neurological sequelae.

10. Renal dysfunction and anaemia are independent predictors of allcause mortality in patients with heart failure.

CME 11. Platelet and vessel wall disorders usually present with mucocutaneous bleeding (petechiae, purpura, ecchymoses, epistaxis, menorrhagia, haematuria and/or gastrointestinal tract blood loss).

12. A basic initial work-up includes a full blood count with peripheral blood smear review, prothrombin time/international normalised ratio and a partial thromboplastin time.

13. If the basic initial work-up is normal, no further investigations are required.

14. Regarding haemophilia, both haemophilia A and B are inherited in an X-linked fashion with male carriers of the mutant gene afflicted with the bleeding diathesis and females being obligate carriers.

15. Regarding haemophilia, the hallmark of haemophilia bleeding is spontaneous intra-articular bleeding.

16. Regarding von Willebrand disease, patients usually present with mucocutaneous bleeding, including epistaxis, easy bruising, menorrhagia and excessive bleeding from minor wounds, tooth extractions and surgery.

17. Regarding inherited platelet disorders, these usually present as prolonged bleeding post haemostatic challenges or in childhood with spontaneous mucocutaneous bleeding from gastrointestinal and genitourinary sites.

18. Regarding inherited platelet disorders, the bleeding time has largely been replaced with automated platelet function assays as a screening test to evaluate platelet function because of the poor reproducibility and wide variability of bleeding time tests.

19. Vessel wall abnormalities are among the inherited bleeding disorders that are associated with normal screening tests.

20. The most common inherited bleeding disorder is hereditary haemorrhagic telangiectasia.

Anaemia, renal dysfunction and in-hospital outcomes in patients with heart failure in Botswana 9. The prevalence of anaemia in patients with heart failure ranges from 4% to 70%.

Readers please note: Articles may appear in summary/abstract form in the print edition of the Journal, with the full article available online at www.samj.org.za

A maximum of 3 CEUs will be awarded per correctly completed test.

INSTRUCTIONS 1. Read the journal. All the answers will be found there, in print or online.

2. Go to www.mpconsulting.co.za to answer the questions.

Accreditation number: MDB015/033/01/2018

January 2018, Print edition

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