Journal of Infection Control I. Vol II by Álvaro Heming

Official Journal of the Brazilian Association of Infection Control and Hospital Epidemiology Professionals

Official Journal of the Brazilian Association of Infection Control and Hospital Epidemiology Professionals Ano I . Volume I . Número II . 2012

Executive Editor Luis Fernando Waib, SP, Brazil Marcelo Carneiro, RS, Brazil Flávia Julyana Pina Trench, PR, Brazil

National Editorial Board Adão Machado, RS, Brazil Adriana Cristina de Oliveira, MG, Brazil Alberto Chebabo, RJ, Brazil Alessandro C Pasqualotto, RS, Brazil Alexandre P. Zavascki, RS, Brazil Alexandre Marra, SP, Brazil Anaclara Ferreira Veiga Tipple, GO, Brazil Ariany Gonçalves, DF, Brazil Claudia Maria Dantas Maio Carrilho, PR, Brazil Claudia Vallone Silva, SP, Brazil Clovis Arns da Cunha, PR, Brazil Elisângela Fernandes da Silva, RN, Brazil Guilherme Augusto Armond, MG, Brazil Icaro Bosczowski, SP, Brazil Isabela Pereira Rodrigues, DF, Brazil Iza Maria Fraga Lobo, SE, Brazil José David Urbaez Brito, DF, Brazil Julival Ribeiro, DF, Brazil Kátia Gonçalves Costa, RJ, Brazil Kazuko Uchikawa Graziano, SP, Brazil Lessandra Michelin, RS, Brazil Loriane Rita Konkewicz, RS, Brazil Luci Corrêa, SP, Brazil Luciana Maria de Medeiros Pacheco, AL, Brazil Maria Clara Padoveze, SP, Brazil Maria Helena Marques Fonseca De Britto, RN, Brazil

Maria Tereza Freitas Tenório, AL, Brazil Marília Dalva Turch, GO, Brazil Marise Reis de Freitas, RN, Brazil Nádia Mora Kuplich, RS, Brazil Nirley Marques Borges, SE, Brazil Patrícia de Cássia Bezerra Fonseca, RN, Brazil Rodrigo Santos, RS, Brazil Rosângela Maria Morais da Costa, RN, Brazil Thaís Guimaraes, SP, Brazil Wanessa Trindade Clemente, MG, Brazil

International Editorial Board Omar Vesga, Colombia Pola Brenner, Chile Suzanne Bradley, United States of America

Associate Editors Afonso Barth, RS, Brazil Ana Cristina Gales, SP, Brazil Anna Sara Shaffermann Levin, SP, Brazil Eduardo Alexandrino Sérvolo de Medeiros, SP, Brazil Rosana Richtmann, SP, Brazil

Graphic Design and Diagramming Álvaro Ivan Heming, RS, Brazil aih.alvaro@hotmail.com

The Journal of Infection Control (JIC), the Official Journal of the Brazilian Association of Infection Control and Hospital Epidemiology Professionals, publishes studies dealing with all aspects of infection control and hospital epidemiology. The JIC publishes original, peer-reviewed articles, short communication, note and letter. Each three months, the distinguished Editorial Board monitors and selects only the best articles. Executives Editors: Luis Fernando Waib, MD, ID, MSc and Marcelo Carneiro, MD, ID, MSc. Frequency: Published 4 times a year. O Jornal de Controle de Infecção (JIC) é a publicação Oficial da Associação Brasileira de Profissionais em Controle de Infecção e Epidemiologia Hospitalar, publica estudos sobre todos os aspectos de controle de infecção e epidemiologia hospitalar. O JIC publica estudos originais, revisões, comunicações breves, notas e cartas. A cada três meses o corpo editorial, editores associados monitoram e selecionam somente os melhores artigos. Editores Executivos: Luis Fernando Waib, MD, ID, MSc e Marcelo Carneiro, MD, ID, MSc. Frequência: Publicação 4 vezes ao ano.

CONTENTS Editorial / pg 20-21

Infection control: why our journals are important Suzanne F. Bradley, M.D.

Short Comunication / pg 22

Adherence to the flu vaccination campaign by healthcare professionals in a teaching hospital Eliane Carlosso Krummenauer, Ana Elizabeth Kautzmann, Janete Aparecida Machado, Marcelo Carneiro, Leandro Bizarro Muller

Original Article / pg 23-25

Multidrug resistant organisms’ incidence in a University Hospital in Porto Alegre Cristófer Farias da Silva, Eloni Terezinha Rotta, Rodrigo Pires dos Santos

Original Article / pg 26-32

Comparison of surgical site infection rates among surgeons Nádia Mora Kuplich, Mário Bernardes Wagner, Ricardo de Souza Kuchenbecker, Rodrigo Pires dos Santos

Original Article / pg 33-36

Copper as an antimicrobial agent in healthcare: an integrative literature review Gleice Cristina Leite, Maria Clara Padoveze

Official Journal of the Brazilian Association of Infection Control and Hospital Epidemiology Professionals

EDITORIAL

Infection Control: why our journals are important Suzanne F. Bradley, M.D.1

1 Program Director, Infection Control & Physician Scientist Infectious Diseases Section & Geriatric Research Education and Clinical Center. VA Ann Arbor Healthcare System. Professor of Internal Medicine Divisions of Infectious Diseases & Geriatric Medicine and Palliative Care Department of Internal Medicine University of Michigan Medical School Ann Arbor, Michigan.

sbradley@umich.edu

Many societies have sought to improve the health of its citizens through major public health initiatives with the ultimate goal of providing universal access to health care. Increased access can lead to improvement in health, but at substantial cost and often with unintended consequences. It has been shown that hospitals consume a disproportionate amount of public healthcare expenditures particularly in low and middle-income countries1. Healthcare associated infections (HAIs) are a significant patient-safety issue. Per the World Health Organization, 1.4 million people worldwide will have an HAI at any given time.2 In the United States (US), 5-10% of hospitalized patients will acquire an HAI during their stay.3 These infections account for 2 million patients and 90,000 deaths per year at a cost of $4.5-5.7 billion US dollars.3 HAIs are one of the most common adverse outcomes world-wide. It has been estimated that 6-17% of patients in resource-limited countries will develop an HAI and the risk of HAIs in those settings may be 2-20 fold higher than in the developed world.1,4 Data from a national program for monitoring and control in Brazil suggests that HAIs are an important problem that is only likely to increase as access to healthcare continues to improve.1,5 In three teaching hospitals from the State of Rio de Janeiro, 7.6% of patients had an adverse event, 14.6% of events were due to a health-care associated infection (HAIs), and 67% of events were deemed preventable.6,7 Antimicrobial resistance has been a major and increasing problem. Efforts to reduce over-the-counter use and improve antimicrobial use through antimicrobial stewardship are pressing issues.8 In the past, it was estimated that $1.4 billion per year could be saved in South America and 2.3 excess days of hospital stay in Brazil if effective infection control programs were established across the continent and nationwide.9 While the situation has

J Infect Control 2012; 1 (2): 20-21

improved since 1983, and most hospitals have some infection control activity and trained personnel, access to surveillance data, microbiology support, and resources to implement control measures effectively is still limited in some regions.8,10,11 Healthcare infections can be prevented with significant reductions in cost, and the message has been slowly spreading worldwide. Since the 1970’s, it has been shown that more than one-third of all hospital infections can be prevented by a program that includes: surveillance for HAIs and methods to prevent and control them, feedback of infection rates to surgeons, provision of an infection control nurse for every 250 acute care beds, and presence of a physician with training in infection control.1,12,13 National surveillance studies and infection control guidelines that began in the US gained momentum at national levels in Europe in the 1990s and regionally thereafter.14 Through the collaborative effort of 18 countries using a standard surveillance network, the International Nosocomial Infection Control Consortium has greatly increased our understanding of the incidence and prevalence of HAIs in resource-limited settings.4 In 2005, WHO launched its “Clean Care is Safer Care” campaign for resource-limited healthcare facilities through improvements in hand hygiene, blood safety, immunization and injection practices, emergency and surgical procedures, and sanitation, water, and waste management.9,15 How can peer-reviewed journals help improve infection control programs and reduce HAIs? The discipline of Infection Control is, by its very nature, data-driven and evidence-based. Journals can provide information that can be used to convince hospital leaders and governmental authorities that evidencebased infection control resources and interventions reduce HAIs and the cost of those infections.4,16 Data from journal articles can

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INFECTION CONTROL: WHY OUR JOURNALS ARE IMPORTANT Suzanne F. Bradley, M.D.

be used as a reference for the development of infection control policies, procedures, and educational initiatives. Information from journal articles can be used to understand how infection rates at one institution compares with benchmark rates from similar institutions. Finally, peer-review journals can appraise its readership about studies that advance the field of infection control. One might think that a small discipline such as Infection Control would require few journals, but that assumption is erroneous. Healthcare systems are not the same. They reflect cultural and socio-economic preferences and differ widely in their organizational structure and scope, management style, resources, priorities, and needs.17 The prevalence of microorganisms and the problems caused by them can change from state to state, region to region, and country to country. All infection control interventions may not work in different settings or may need to be implemented in different ways. Journals may not be readily available or translated so that all infection control practitioners and healthcare epidemiologists have access to that information.4,11,14 The emergence of the electronic

journal has increased access to information for many, but not all. It is therefore important to “think globally, but act locally” (Marcel). As Professor Wey said almost 15 years ago, that “…the development of local research in all areas of infection control is an important link in adapting data from the literature to local reality”.11 The productivity of Brazilian scientists has increased markedly over the past decade exceeding the output of China, India, Mexico, and the Russian Federation and accounting for 2.7% of global publications in peer-review journals.18 Brazil has been the leading contributor outside of North America to Infection Control and Hospital Epidemiology. So, there clearly is an abundance of infection control data that needs to be published. This information needs to be disseminated as widely and as quickly as possible to all infection control practitioners at local as well as international levels. When armed with the evidence, infection control experts will be prepared to make a case for infection control in their workplaces and improve the quality and safety of the care delivered to their patients.

REFERENCES 1.

3. 4.

7. 8. 9.

Huskins CW, Soule BM, O’Boyle C, Gulacsi L, O’Rourke EJ, Goldmann DA. Hospital infection prevention and control: A model for improving the quality of hospital care in low- and middle-income countries. Infect Control Hosp Epidemiol 1998;19:125-135. Ling ML. Chapter 47: Patient Safety. IN: Jarvis, WR (ed): Bennett and Brachman’s Hospital Infections, 5th edition ( Philadelphia, PA: WolterKluwers Health, 2007), 813-817. Burke JP. Infection control – A problem for patient safety. N Engl J Med 2003;248:651-656. Apisarnthanarak A, Ajenjo C, Roth VR. Chapter 28: Infection prevention in resource-limited settings. IN: Lautenbach E, Woeltje KF, Malani PN, (eds): Practical Healthcare Epidemiology, 3rd Edition (Chicago, IL: University of Chicago Press, 2010, 373-391. Barreto ML, Texeira MG, Bastos FI, Ximenes RAA, Barata RB, Rodrigues LC. Successes and failures in the control of infectious diseases in Brazil: social and environmental context, policies, interventions, and research needs. Lancet 2011;377:1877-1889. Mendes W, Martins M, Rozenfeld S, Travassos C. The assessment of adverse events in hospitals in Brazil. Int J Qual Health Care 2009;21:279-284. Paim J, Travassos C, Almeida C, Bahia L, Macinko J. The Brazilian health system: history, advances, and challenges. Lancet 2011;377:1778-1797. Rossi F. The challenges of antimicrobial resistance in Brazil. Clin Infect Dis 2011;52:1138-1143. Nettleman MD. Global aspects of infection control. Infect Control Hosp Epidemiol 1993;14:646-648.

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10. 11. 12.

13. 14.

15.

16.

17.

18.

Pannuti CS, Grinbaum RS. An overview of nosocomial infection control in Brazil. Infect Control Hosp Epidemiol 1995;16:170-174. Wey Sergio B. Infection control in a country with annual inflation of 3,600%. Infect Control Hosp Epidemiol 1995;16:175-178. Haley RW, Culver DH, White JW, Morgan WM, Emori TG, Munn VP et al. the efficacy of infection surveillance and control programs in preventing nosocomial infections in US hospitals. Am J Epidemiol 1985;121:182-205. Wenzel RP. The economics of nosocomial infections. J Hosp Infect 1995;31:79-97. Widmer AF, Sax H, Pittet D. Infection control and hospital epidemiology outside the United States. Infect Control Hosp Epidemiol 1999;20:17-21. Pittet D, Donaldson L. Clean care is safer care: The first global challenge of the WHO World Alliance for patient safety. Infect Control Hosp Epidemiol 2005;26:891-94. Perencevich PN, Stone PW, Wright SB, Carmeli Y, Fisman DN, Cosgrove SE. Raising standards while watching the bottom line: Making a business case for infection control. Infect Control Hosp Epidemiol 2007;28:1121-1133. Marcel1 J-P, Alfa M, Baquero F, Etienne J, Goossens H, Harbarth S, et al. Healthcare-associated infections: think globally, act locally. Clin Microbiol Infect 2008;14:895-907. Victora CG, Barreto ML, do Carmo Leal M, Monteiro CA, Schimidt MI Paim J et al. Health conditions and health-policy innovations in Brazil: the way forward. Lancet 2011;377:2042-2053.

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Official Journal of the Brazilian Association of Infection Control and Hospital Epidemiology Professionals

SHORT COMUNICATION

Adherence to the flu vaccination campaign by healthcare professionals in a teaching hospital Eliane Carlosso Krummenauer1, Ana Elizabeth Kautzmann2, Janete Aparecida Machado3, Marcelo Carneiro4, Leandro Bizarro Muller5

Enfermeira, Vice-coordenadora da Comissão de Controle de Infecção e Epidemiologia Hospitalar, Hospital Santa Cruz, Santa Cruz do Sul, RS, Brasil. Enfermeira, Serviço Especializado em Engenharia de Segurança e Medicina do Trabalho, Hospital Santa Cruz. 3Técnica de enfermagem, Comissão de Controle de Infecção e Epidemiologia Hospitalar, Hospital Santa Cruz. 4Médico Infectologista, Coordenador da Comissão de Controle de Infecção e Epidemiologia Hospitalar, Hospital Santa Cruz. 5Médico gastroentereologista, Diretor Técnico do Hospital Santa Cruz. 1 2

Received: 28/06/2012 Accepted: 31/08/2012 carneiromarcelo@yahoo.com.br

After three years of sustained circulation of H1N1 subtype (pandemic A/H1N1), when the biggest pandemic of this century caused many deaths, we realized that the conducts have been improved with the availability of specific vaccines and antiviral drugs that allowed the decrease in morbidity and mortality. These measures lessened the panic, but many questions on forms of contagion and treatment indication persist, including the disregard of severity. The institution of risk groups for the development of severe acute respiratory syndrome (SARS) permitted therapeutic and preventive alternatives. Healthcare professionals (HCP) were included as an at-risk population for the disease. With the establishment of this disease as endemic, during the winter months, the population needed to adopt/reinforce prevention and control measures, such as hand hygiene, respiratory etiquette, avoiding crowded places and respiratory precautions for suspected cases. Increased attendance and overcrowding of health services has generated insecurity for EDs, as well as administrative and socioeconomic problems in a global context. Regardless of all the indicators and evidence, the population has not acquired or maintained preventive habits. A systematization of suspected flu syndrome (FS) and SARS, especially in urgency/emergency care units, has become necessary to minimize the occupational risk and therefore, absenteeism. The use of screening protocols aids in the protection and optimization of personal protective equipment (PPE) against respiratory disease transmission. The systematization of vaccination campaigns is disseminated and encouraged by the Specialized Safety Engineering and Occupational Medicine Service (SESMT) of Hospital Santa Cruz (Santa Cruz do Sul,

RS, Brazil). It is a regional teaching hospital with 194 beds, of high complexity, with 798 employees, located in the region of Rio Pardo and Taquari Valleys. The aim of this study was to evaluate the institutional campaign against flu in this community hospital. During the National Flu Vaccination Campaign, 659 doses were applied at SESMT-HSC. The national target for immunization of risk groups is 80.0%. In our institution 457 (57.3%) employees were vaccinated, of which 221 (47.5%) worked in assistential care and 236 (70.87%) in administrative functions. It has not been analyzed to date, whether the employees who did not adhere to the vaccination campaign received the vaccine elsewhere, which may be a relevant limiting factor for the study. The results show low adherence by the assistential care team and this fact worries hospital administration. We identified reports discrediting the vaccination effect as well as fear of adverse events. Based on that, we established the following questions: Why did the healthcare professionals refuse the vaccination? What is the impact of this attitude when managing their patients? In this context one needs to consider cultural issues, beliefs, values and the continuing education process in professional training. Changes in behavior are a slow and gradual process and interfere with the acceptance of evidence-based preventive and safety technical standards, which will culminate in a change of habit. This study showed a gap in the development of educational activities with healthcare teams in order to make them aware about the importance of immunization and prevention of occupational diseases.

REFERENCES 1.

Carneiro M, Bercini, MA, Lara BS et al. The Influenza A/H1N1 Pandemic in Southern Brazil. Infect Control Hosp Epidemiol 2011; 32:12.

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Carneiro M, Trench FJP, Waib LF et al. Influenza H1N1 2009: revisão da primeira pandemia do século XXI. Revista da AMRIGS 2010; 54: 206-213.

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Official Journal of the Brazilian Association of Infection Control and Hospital Epidemiology Professionals

ORIGINAL ARTICLE

Multidrug resistant organisms’ incidence in a university Hospital in Porto Alegre Cristófer Farias da Silva, PharmaD1, Eloni Terezinha Rotta, PharmaD, Msc 1, Rodrigo Pires dos Santos, MD, PhD2

1 Hospital Infection Control Committee and Pharmacy Department – Hospital de Clínicas de Porto Alegre. 2Hospital Infection Control Committee - Hospital das Clínicas de Porto Alegre.

Received: 19/03/2012 Accepted: 08/05/2012 far.cristofer@gmail.com

ABSTRACT Introduction: Multidrug-resistant organisms (MDRO) are a growing worldwide public health problem. Few therapeutic options remain available to treat infections caused by MDRO. Local actions should be implemented to reduce bacterial resistance and MDRO diffusion. Objective: Evaluate the incidence of MDRO in the institution and assess the outcome of patients. Methods: Was performed a prospective cohort. Were included patients hospitalized between June 2010 and May 2011, with microbiological isolates, classified according to 2010 Hospital Infection Control Committee criteria. Patients were followed until their outcomes. Results: Were identified 981 multidrugresistant organisms in 808 patients. The median length of stay for the

identification of the MDRO was 12 days (IQR 25-75%, 3-26 days). The monthly rate came to minimal and maximal amplitude of, respectively, 2.7 and 5.9 MDRO/1000 patient-days per period. During the studied period was not observed a significant increase in the incidence rate of MDRO at institution. Conclusion: Our findings show that MDRO with major incidence was extended-spectrum β-lactamase-producing organism and the vancomicin-resistant Enterococcus spp. The definition of a local epidemiologic profile of resistant organisms is important to drive preventive and therapeutic actions inside the institution. Keywords: Multidrug resistance. Bacterial resistance. Incidence. Multidrug-resistant organisms.

INTRODUCTION Multidrug-resistant organisms (MDRO) are a growing public health problem worldwide and few therapeutic options are available to treat infections caused by those organisms. Consequently, a multidisciplinary approach (infection control procedures, bacterial surveillance, patient isolation and antimicrobial stewardship) should be implemented to reduce those microorganisms dissemination1. Hospital-acquired infection is one of the most common hospital complications2,3, and, when caused by MDRO, they increase hospital costs, length of stay and also patient morbidity and mortality4,5. The rise in resistant organisms, non-responsive to conventional treatment, emphasizes the need for new antibiotics development6. In the past 40 years, only four new classes of antibiotics have been launched and few pharmaceutical companies show interest in research and develop this kind of drugs7. Emergence of MDRO is mostly associated with inappropriate use of antibiotics, which promotes selective pressure on microorganisms8.

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Bacteria have the ability of easily transfer genes, which contributes to perpetuation of the resistant species, and the expression of resistance genes reduces treatment options9. Facing the growing problem of bacterial resistance, the aim of this study was evaluate the MDRO incidence at Hospital de Clínicas de Porto Alegre (HCPA), to provide information to plan new actions to control these organisms spread.

METHODS Setting - Hospital de Clínicas de Porto Alegre, a 790-bed, university affiliated, tertiary level public hospital, is located in the city of Porto Alegre, in southern Brazil. All hospital units, i.e., intensive care units (adult, neonatal and pediatric), clinical and surgical wards were included. The study was approved by the institution’s Ethics Committee under number 110129.

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MULTIDRUG RESISTANT ORGANISMS’ INCIDENCE IN A UNIVERSITY HOSPITAL IN PORTO ALEGRE Cristófer Farias da Silva, Eloni Terezinha Rotta, Rodrigo Pires dos Santos.

Study design and definitions - We performed a prospective cohort study, from June 2010 to May 2011. Data were collected daily, by the review of the microbiological laboratory report and hospital electronic database for patient clinical and demographic data. The identification of bacterial species was performed according to standard laboratory protocols. Susceptibility data was tested by disc-diffusion method, interpreted according to Clinical and Laboratory Standards Institute guidelines10. The first microbiological MDRO isolate per patient was included, irrespective of the body site from which the specimen was obtained. If the same isolate was cultured after 10 days of the first identification, it was considered a new microorganism and included in the study. Patients re-hospitalized with the same MDRO isolate created a second entrance in the database. Patients were followed until their outcomes. Resistance Data - Bacterial resistance was classified according to 2010 Hospital Infection Control Committee criteria, and included the following: carbapenem-resistant Acinetobacter spp., Citrobacter spp., Enterobacter spp., Pseudomonas spp. and Serratia marcescens; extended-spectrum β-lactamase (ESBL)-producing Escherichia coli, Klebsiella spp. and Proteus spp.; sulfamethoxazole/trimethoprim resistant Stenotrophomonas maltophilia; vancomycin-resistant Enterococcus spp. (VRE); methicillin-resistant Staphylococcus aureus (MRSA); any Clostridium difficile and Burkholderia cepacea. Isolates with intermediate susceptibility were considered resistant. Statistical analysis - Bacterial resistance rate was calculated by dividing the number of isolates for each species by the entire hospital number of patient-days multiplying the quotient by 1000. Data were reported on a monthly basis. Data normally distributed was shown as mean and standard deviation and otherwise distribution was shown as median and interquartile ranges (IQR). To determine the distribution pattern of the variables, the Kolmogorov-Smirnov test was performed. Linear regression was used to measure the curve trends of MDRO incidence. Statistical significance in all analyses was defined as P <0.05. Data was analyzed with Statistical Package for Social Science (SPSS) 18.0.

RESULTS In this study, we identify 981 MDRO in 808 patients. Most patients were men 56.4% (N=456), 92.1% were white (N=744), and 5.2% were black (N=42). The median age was 57 years (IQR25-75%, 37-69 years). From 808 patients, 17.3% had respiratory disease (N=140), 14.9% cardiovascular disease (N=120), 13.0% renal disease (N=105), 11.6% solid organ cancer (N=94), 9.8% gastrointestinal disease (N=79), 8.3% cystic fibrosis (N=67), 7.4% of patients were transplanted (N=60), 6.8% had hematology cancer (N=55) and 32.3% had other comorbidities (N=261). The median length of stay of patients with MDRO was 31 days (IQR 25-75%, 17-56 days). The median time for identification of the organisms was twelve days (IQR 25-75%, 3-26 days). Considering the 808 patients, 69.1% (N=558) had been hospitalized before at HCPA. Thirty percent (N=247) of patients were readmitted to HCPA within 60 days after hospital discharge. Monthly incidence of MDRO identified as infection or colonization, from hospital or community origin is shown in Figure 1. The trend curve shows no significant increase in MDRO in the studied period (P=0.16). Among the 981 identified multiresistant organisms, 232 were Enterococcus spp. (23.6%), 224 were Klebsiella spp. (22.8%), 162 were Staphylococcus aureus (16.5%), 133 were E. coli (13.6%), 112 were Pseudomonas aeruginosa (11.4%), 63 were Acinetobacter spp. (6.4%), 18

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were Clostridium difficile (1.8%), 16 were Burkholderia cepacea (1.6%), 10 were Proteus spp. (1.0%), 7 were Stenotrophomonas maltophilia. (0.7%) and 4 were Enterobacter spp. (0.4%). Monthly incidence of MDRO stratified by the main bacterial species is shown in Figure 2.

DISCUSSION The aim of this study was to evaluate the MDRO incidence in HCPA. Our findings show that MDRO with major incidence was ESBL-producing organisms, VRE, MRSA, and carbapenem-resistant Pseudomonas aeruginosa. Patients with MDRO had a long hospital stay, compared to the mean entire hospital length of stay (8.13 days; personal communication) and a significant percentage of re-admissions. During the study period, there was no increase in trend of identification of MDRO. Many studies show an increase of bacterial resistance to antibiotics. For instance, studies in Latin America observed that 48.3% of Staphylococcus aureus were resistant to methicillin, 21.4% of Acinetobacter spp. were resistant to carbapenems and 36.7% Klebsiella pneumonia and 20.8% E. coli were ESBL-producers11. Furthermore, the rate of Enterococcus spp. resistant to vancomycin increased from 5.0% in 2003 to 15.5% in 200812. In Europe, there is an increasing incidence of ESBL, VRE, Acinetobacter spp., Pseudomonas spp., and others13,14. In our study, the global monthly incidence of MDRO shows some oscillations in the period. The monthly rate came to minimal and maximal amplitude of, respectively, 2.7 and 5.9 MDRO/1000 patient-days per period. These variations may be related to the new measures taken by Hospital Infection Control Committee (HICC) through the observed period, in an attempt to decrease MDRO incidence. Some of the measures include: the campaign involving patient empowerment and hand hygiene compliance initiated in August 2010; the at distance learning course about hand hygiene directed to the hospital assistant team in December 2010; and the creation of a unit for cohorting patients with MDRO in March 2011. Those interventions were not controlled in this study. These differences in MDRO incidence may be the evidence that measures taken for the global MDRO reduction may have distinct effect for each microorganism. If we stratify incidence by microorganisms, we can see two distinct incidence profiles, one of them with few oscillation and the other with more variations in specific periods. MRSA and carbapenem-resistant Pseudomonas aeruginosa show an incidence profile with few variations, the other bacteria show a profile with more oscillations in specific periods of time (Figure 2). Studies show the importance of hand contamination for dissemination of MRSA or the environment for spread of C. difficile, VRE and Acinetobacter spp., therefore measures that aim hand hygiene or environment disinfection can affect rates of MDRO differently5,15-17. Another interesting observation was the reduction in MDRO incidence in December, for almost all microorganisms, which might be related to the at distance learning course on hand hygiene, although our study was not design to confirm this hypothesis. This study has some limitations. Seasonality may have affected the incidence of certain bacteria in the period, like, for instance, Acinetobacter spp., whose incidence increases at summer time18. It was not possible to identify the rate resistance profile for each bacteria, because we included in this cohort only the resistant bacteria, which makes the comparison to other studies not possible. The mortality of patients cannot be attributed directly to colonization/ infection by MDRO, since the study was not designed to evaluate this outcome. The profile of bacterial resistance in HCPA shows predominance of ESBL-producing organisms and the VRE. There was not a significant increase in MDRO incidence rate in the period. The definition of a local epidemiologic profile of resistant organisms is important to drive preventive and therapeutic actions inside the institution.

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MULTIDRUG RESISTANT ORGANISMS’ INCIDENCE IN A UNIVERSITY HOSPITAL IN PORTO ALEGRE Cristófer Farias da Silva, Eloni Terezinha Rotta, Rodrigo Pires dos Santos.

ACKNOWLEDGEMENTS

Figure 1. Monthly incidence from infection or colonization by MDRO (community or hospital acquired) at HCPA per 1000 patient-days.

MDRO / 1000 patient-days

Acinetobacter spp.

The authors want to thank the participation and discussions of all members of the Hospital Infection Control Committee of Hospital de Clínicas de Porto Alegre and the contributions of Souza D.G.

1 0,28

MDRO/1000 pacient-days

7 5,9

6 5

4,3

4 3

2,8

3,2

2,8

3,7

4,2 3,3

5,8

2,7

1 0 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-11 Feb-11 Mar-11 Apr-11 May-11

Figure 2. Monthly incidence from infection or colonization, stratified by MDRO (community or hospital acquired) at HCPA, per 1000 patient-days.

MDRO / 1000 patient-days

1,28 0,98

MDRO / 1000 patient-days

1,09

1,21

1,87

1,71

1,53

1,51

1,42

1,30

0,91

7. Jun-10

Jul-10

Aug-10

Sep-10

Oct-10

Nov-10

Dec-10

Jan-11

Feb-11

Mar-11

Apr-11

May-11

Enterococos spp.

8. 9.

2 1,55 1,35

0,80

1,36

1,21

0,92

1,11 0,61

0,56

Jun-10

0,42

11. Jul-10

Aug-10

Sep-10

Oct-10

Nov-10

Dec-10

Jan-11

Feb-11

Mar-11

Apr-11

May-11

Staphylococos aureus

12.

13.

1 0,61

0,71

0,63

0,74

Jun-10

Jul-10

Aug-10

Sep-10

0,70 0,50

0,43

10.

0,86

0,24

MDRO / 1000 patient-days

2,58

MDRO / 1000 patient-days

4. ESBL*

Oct-10

Nov-10

0,87 0,61

0,70

0,80

0,35

Dec-10

14. Jan-11

Feb-11

Mar-11

Apr-11

May-11

15.

Pseudomonas spp.

16.

17. 1 0,38

Jun-10

0,43

0,48

0,56

0,60

0,23

Jul-10

Aug-10

Sep-10

Oct-10

J Infect Control 2012; 1 (2): 23-25

Nov-10

0,35

0,37

Dec-10

Jan-11

0,50

0,55

0,66 0,22

Feb-11

Mar-11

Apr-11

Jul-10

0,09

0,10

0,09

0,05

Aug-10

Sep-10

Oct-10

Nov-10

0,15 Dec-10

0,23

0,25

Jan-11

Feb-11

Mar-11

0,33

0,35

Apr-11

May-11

REFERENCES 1.

Jun-10

0,23

*ESBL (Klebsiella spp., E. coli, Proteus spp.) 4,0

3,7

0,78

May-11

18.

Orsi, G.B., M. Falcone, and M. Venditti, Surveillance and management of multidrug-resistant microorganisms. Expert Rev Anti Infect Ther, 2011. 9(8): p. 653-79. Geffers, C., D. Sohr, and P. Gastmeier, Mortality attributable to hospitalacquired infections among surgical patients. Infect Control Hosp Epidemiol, 2008. 29(12): p. 1167-70. Aranaz-Andres, J.M., et al., Incidence of adverse events related to health care in Spain: results of the Spanish National Study of Adverse Events. J Epidemiol Community Health, 2008. 62(12): p. 1022-9. Siegel, J.D., et al., Guideline for Isolation Precautions: Preventing Transmission of Infectious Agents in Health Care Settings. Am J Infect Control, 2007. 35(10 Suppl 2): p. S65-164. Siegel, J.D., et al., Management of multidrug-resistant organisms in health care settings, 2006. Am J Infect Control, 2007. 35(10 Suppl 2): p. S165-93. Paterson, D.L., “Collateral damage” from cephalosporin or quinolone antibiotic therapy. Clin Infect Dis, 2004. 38 Suppl 4: p. S341-5. Cooper, M.A. and D. Shlaes, Fix the antibiotics pipeline. Nature, 2011. 472(7341): p. 32. Walsh, C., Where will new antibiotics come from? Nat Rev Microbiol, 2003. 1(1): p. 65-70. Rossolini, G.M., et al., Epidemiology and clinical relevance of microbial resistance determinants versus anti-Gram-positive agents. Curr Opin Microbiol, 2010. 13(5): p. 582-8. Clinical and Laboratorial Standards Institute. Performance Standards for Antimicrobial Susceptibility Testing; Seventeenth Informational Supplement. Wayne, PA: CLSI, 2007. Rossi, F., et al., Rates of antimicrobial resistance in Latin America (20042007) and in vitro activity of the glycylcycline tigecycline and of other antibiotics. Braz J Infect Dis, 2008. 12(5): p. 405-15. Rossi, F., The challenges of antimicrobial resistance in Brazil. Clin Infect Dis, 2011. 52(9): p. 1138-43. Geffers, C. and P. Gastmeier, Nosocomial infections and multidrugresistant organisms in Germany: epidemiological data from KISS (the Hospital Infection Surveillance System). Dtsch Arztebl Int, 2011. 108(6): p. 87-93. Miyakis, S., A. Pefanis, and A. Tsakris, The challenges of antimicrobial drug resistance in Greece. Clin Infect Dis, 2011. 53(2): p. 177-84. Jawad, A., et al., Survival of Acinetobacter baumannii on dry surfaces: comparison of outbreak and sporadic isolates. J Clin Microbiol, 1998. 36(7): p. 1938-41. Boyce, J.M., MRSA patients: proven methods to treat colonization and infection. J Hosp Infect, 2001. 48 Suppl A: p. S9-14. Pittet, D., et al., Effectiveness of a hospital-wide programme to improve compliance with hand hygiene. Infection Control Programme. Lancet, 2000. 356(9238): p. 1307-12. McDonald, L.C., S.N. Banerjee, and W.R. Jarvis, Seasonal Variation of Acinetobacter Infections: 1987 - 1996. Clin Infect Dis, 1999. 29: p. 1133-7.

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Official Journal of the Brazilian Association of Infection Control and Hospital Epidemiology Professionals

ORIGINAL ARTICLE

Comparison of surgical site infection rates among surgeons Nádia Mora Kuplich1, Mário Bernardes Wagner2 , Ricardo de Souza Kuchenbecker2 e Rodrigo Pires dos Santos1a1

1 Comissão de Controle de Infecção Hospitalar, Hospital de Clínicas de Porto Alegre (HCPA). 2Programa de Pós-Graduação em Epidemiologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.

Received: 22/05/2012 Accepted: 10/07/2012 nkuplich@hcpa.ufrgs.br

ABSTRACT This paper presents a comparison of surgical site infection (SSI) rates among surgeons taking into account surgical procedures and risk factors. This methodological approach allows and facilitate such comparisons as it considers potential confounding factors that may be involved. A database of 5,023 surgical procedures classified according to the National Nosocomial Infection Surveillance System (NNIS) was used to obtain adjusted SSI rates considering the surgical site and three essential variables part of the NNIS surgical risk index: (i) the ASA (American Society of Anesthesiology) physical status score; (ii) the surgical wound classification and (iii) the duration of surgery. Surgical procedures were then categorized into four risk strata: low-risk,

medium low risk; medium high risk and high risk. The comparison of these rates was done using indirect standardization. The SSI rate observed for each surgeon was compared to the expected rate for the same risk strata according to the hospital database, which was taken as the reference population. Finally, dividing the number of observed SSI by the expected SSI a standardized surgical site infection ratio (SSIR) was obtained for each surgeon by procedures. The SSIR may be considered a relative, indirect and adjusted rate by risk strata, which provides a feasible alternative to compare rates among surgical teams in the same institution. Key-words: hospital infections, surveillance, surgical site infection.

INTRODUCTION Surgical site infections (SSI) are the third most common type of healthcare acquired infections (HAI) in hospitals.3,4 Apart from representing substantial morbidity and mortality, SSI cause duplication of the hospital stay5 and an estimated additional cost of 2,000 dollars per patient.6 Different SSI surveillance methods have been developed and validated.2, 6, 7 These methods include the classification of the main risk factors related to SSI occurrence depending on the patient or the surgical procedure itself.7 Among these, the most frequently mentioned factors are: (i) the surgical wound classification; (ii) the operative technique (iii) events occurring during the surgery; (iv) the patient’s intrinsic susceptibility to infection2, 6, 7 and (v) aspects related to the patient surgical preparation.8, 9 One of the roles of SSI surveillance is to enable adequate comparison within hospitals, services and surgical teams.10 For an adequate comparison of the SSI rates, specific diagnostic criteria and adequate identification of the cases of patients with HAI are necessary and should accurately reflect the hospital population exposed to risk.

J Infect Control 2012; 1 (2): 26-32

Since the widespread of the “wound contamination class” in the sixties,2,7,11 several additional factors have been proposed in order to gather patient-related morbidity information, and thus enhance the comparability between the SSI rates.7 Existing SSI surveillance systems that provide HAI information for surgical teams can reduce SSI rates by as much as 32%.12 The Study on the Efficacy of Nosocomial Infection Control (SENIC) developed a multi-variable risk index for comparing the SSI which included four dichotomous factors: (i) surgeries lasting more than two hours; (ii) classification of the operative surgical wound in contaminated or infected; (iii) patients with three or more diagnostics on discharge and (iv) surgery involving the abdominal cavity.7 At the end of the 1980´s, in the National Nosocomial Infection Surveillance (NNIS) study, the Centers of Disease Control and Prevention (CDC) further improved the SENIC proposed surgical risk index by incorporating the American Society of Anesthesiology (ASA) classification scale to measure the patient’s intrinsic susceptibility to

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COMPARISON OF SURGICAL SITE INFECTION RATES AMONG SURGEONS Nádia Mora Kuplich, Mário Bernardes Wagner, Ricardo de Souza Kuchenbecker, Rodrigo Pires dos Santos.

infection.13 For the duration of surgery, the percentile 75, specific for each type of procedure, was substituted by a cut-off point for above or bellow two hours. When the NNIS results were divulged it was found that the risk index of the study had a good capacity to distinguish between the majority of the surgical procedures even though it was very dependent on the number of procedures in each risk level.14 This dependency prevented its use for the classification of hospital infections in small hospitals, and made it insuitable for detecting differences in databases containing a reduced number of surgeries. Therefore, an alternative method of classification for detecting small variations between the SSI risk categories was required. Furthermore, even if the relevance of the adoption of an index that permits better comparisons between the SSI risks is accepted, it is true that very few hospitals now use any form of infections grading.15 This is mainly due to the difficulty in obtaining patient details that make up the index and the inadequacy of the patient details in computer records.16,17 In this context, the CDC specialists suggested different approaches to permit comparison between the rates and surgeries over the last ten years. However, for minor surgical procedures, or in hospitals where a reduced number of interventions take place, no adequate system to estimate surgical performance and risks is available at present . Gaynes18 recommended that the SSI rates should incorporate some form of indirect standardization process.19 The expected SSI value for samples is calculated to obtain the SSI referential rates for each level of risk. This number, multiplied by the number of procedures in the sample, is the SSI number expected for each risk level. The total of the SSI numbers expected in all risk categories is the SSI expected number for the sample. Finally the author18 proposes the calculation of the standardized SSI ratio for use as an indicator between the rates. In this way, values lower than one would indicate intervention rates competitive with the average, while rates over one would signify that hospital infections over the average had occurred and required deeper investigation. Starting with the grading process described above, it would be possible to obtain a standardized surgical site infection ratio (SSIR) represented by an SSI coefficient adequately adjusted, that permit the confrontation of the expected SSI number with that obtained in the systematic SSI surveillance.18 The SSIR would offer a relatively simple and accessible alternative to compare SSI rates.18,20 The objective of this paper is to propose and evaluate a method for SSI comparison rates between the various surgical teams who operate in a teaching hospital in the Southern of Brazil.

PATIENTS AND METHODS We included 5023 surgical procedures conducted in the Hospital de Clínicas de Porto Alegre (Porto Alegre Clinical Hospital) (HCPA), in Rio Grande Sul State, South of Brazil. All the procedures were classified according to CDC surgical procedures categories and further subdivided by NNIS risk index levels, to reduce the considerable number of sub-categories obtained and enable standardization of the SSI. Surgical procedures were grouped and distributed within a reduced number of risk corresponding to progressive levels of SSI risk occurrence. Accordingly, the entire database was concentrated into four pre-fixed strata defined as (i) low risk of SSI occurrence risk (< 2,0%), medium low-risk (2,0% |— 5,0%), medium high risk (5,0% |— 9,0%) and high risk (> 9,0%).14 Surgical teams who performed less than 20 surgical procedures were not included in the overall indirect standardization. In this process, the SSI reference rate was multiplied by the number of surgical

J Infect Control 2012; 1 (2): 26-32

procedures performed by each surgical team in that same strata. With this, the expected SSI number for each surgeon was obtained. The total of SSI numbers observed in the different risk grades for each surgeon divided by the corresponding total of the expected SSI risk (obtained by the above-mentioned method) generated the SSIR or surgical site infection ratio. The SSIR is equivalent to the standardized morbidity/ mortality ratio or SMR generally used in the process of indirect standardization.19 Therefore, the SSIR may be considered an indirect relative rate adjusted for the potential of risk of infection represented, in our study, by the four grades proposed.14,18,20 In mathematical terms the SSIR may be expressed by the following equation: SSIR= (SSI observed)/ (SSI expected) For the interpretation of the SRSSI the following criteria were used: SSIR = 0, the surgeon did not present cases of patients with SSI. SSIR = <1, the surgeon presented a SSI rate lower than that expected for the distribution of his/her patients in the SSI risk grade. SSIR = 1, the surgeon presented a SSI rate equal to that expected for the distribution of his/her patients in the SSI risk grade. SSIR = >1, the surgeon presented a SSI rate greater than that expected for the distribution of his/her patients in the SSI risk grade. To enable SSI rates comparison amongst surgeons considering potential risk factors, SSIR ratios were ranked from the surgeon with the lowest SSIR value (lowest rate of relative SSI) to the highest value (highest rate of relative SSI). For deciding between surgeons with the same SSIR result, the surgeon with the greatest number of performed surgical procedures was chosen. Two trained research assistants revised all patients records21,22 and gathered the following information: (i) surgical procedures (number of surgical procedures, type of surgery, surgical team, and ASA score), (ii) types and location site of HAI, if applicable, (iii) invasive procedures (e.g catheter and mechanical ventilation) performed; and (iv) preventive measures for HAI prevention. HAI data is processed using an informatized system developed at HCPA. HAI were classified using the diagnostic criteria of the CDC. Statistical Analysis The SSIR confidence interval was obtained using the Poisson distribution because of its similarity to the standardized ratio of morbidity/mortality (SMR) and in accordance with the method proposed by Kahn and Sempos.19 A 5% significance level was used. The data were processed and analyzed using the following softwares: MS EXCEL® 14.0, Pepi® version 4.0 and SPSS® version 16.0.26

RESULTS The original databank contained 5,023 surgical procedures of which all those presenting a frequency less than 20 were excluded The final number of patients considered was 4,627 . The general SSI incidence rate observed was 7.78%. Approximately 160 subcategories of surgical procedures were performed and graded into four risk strata (0, 1, 2 and 3) with their respective SSI rates (Table 1). Some surgical procedures (e.g. neurosurgeries, nephrectomies, and transplants) were infrequent, and therefore, the related SSI rate was low or inexistent. The SSI in the column of risk level 1 of the NNIS, for example, present considerable internal variation which required grouping of the proportions or SSI rates to enable comparison. The reduced number of surgical procedures graded in NNIS level 3 corresponded to 1.87% (n = 94) of the sample studied. It was observed a linear increase in the SSI frequency as the level of the risks increased. This tendency was especially demonstrated in surgery involving the abdominal cavity, such as, cholecystectomies, appendectomies,

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COMPARISON OF SURGICAL SITE INFECTION RATES AMONG SURGEONS NĂĄdia Mora Kuplich, MĂĄrio Bernardes Wagner, Ricardo de Souza Kuchenbecker, Rodrigo Pires dos Santos.

geniturinaries, of the liver and pancreas, for example. The abdominal surgeries were the most representative in the sample, reaching a total of 965 (77.3%) of the surgical procedures submitted to the NNIS risk level classification. Table 2 presents the surgical procedures (n = 4,627) and the respective SSI rates after grading into the four NNIS risk levels. The surgical procedures were grouped into SSI rates below 2% (low risk), from 2 to 5% (medium risk), from 5 to 9% (medium high risk) and over 9% (high risk). The expected SSI values in each of these grades were 1.43%, 3.31%, 6.62% and 18.47%, respectively. The SSI rate of the surgical procedures classified as of high risk (SSI rate above 9%) represented 56.25% (n = 207) of the studied sample. Table 3 demonstrates the surgeons, the number of surgical procedures and the respective SSI number distributed into the considered risk levels. A reasonable level of heterogeneity between expected and observed SSI rates amongst surgical teams can be observed. The discrepancies were more often within 3 and 4 surgical risk levels. Of note, some surgeons performed interventions belonging to only one of the risk levels, such as the surgeons codes 6, 7 and 33. On the other hand, surgeons 101,102 and 103 performed surgical interventions in 3 risk levels (2, 3, and 4). To enable the comparison amongst surgeons, the SSIR general numbers were calculated for each surgeon by adding up all procedures registered in the databank for that surgeon and presented with their respective confidence intervals in Table 4. In this table, the surgeons were ranked in ascending SSIR order, listed from the first (surgeon code 401, SSIR 0.00) to the last (surgeon code 502, SSIR =1.85). It should be pointed out that only the one surgeon, ( code 502, SSIR=1.85) who was classified in position 26th, presented a confidence interval statistically significant (CI 95% 1.25 â&#x20AC;&#x201C;2.65). This finding may suggest the need for a more detailed monitoring of his/her performance prospectively to determine if the finding was an fortuity event or if that indicates a problem that requires intervention from the hospital infection control committee.

DISCUSSION Using an existing databank of surgical procedures, it was possible to demonstrate the feasibility of a quite simple method for SSI standardized rates comparison amongst surgeons in a teaching hospital. The applicability of the proposed SSI adjustment method precludes the use of relatively more complex multivariable regression models, 27,28,29 and thus applicable for single hospitals. The results showed here demonstrate that it was possible to improve the understanding of the adjustment process of SSI rates thought a quite simple comparison method that can be used by any infection control committee as an easy and feasible method for surgical teams comparative performance analysis.20, 21 Of note, one of the limitations of the proposed methodology relies on the assumption of a necessary certain number of surgical procedures in each risk category. That means that the proposed method for SSI rates comparison may not be used in small or low surgical volume hospitals. In our study, considering the surgical procedures graded by the NNIS index as it was shown in Table 1, a pulverization of the number of surgical procedures was observed. The reduced number, or even the inexistence of surgeries in many of the NNIS risk levels, may preclude an accurate observation of any discrepant behaviour of SSI rates. Accordingly, only in surgeries with a constant and stable number in each NNIS category level it was possible to detect the increase in rates with addition of the risk factor, as in cholecystectomies, genitourinaries

J Infect Control 2012; 1 (2): 26-32

procedures, gastric and liver and pancreas surgeries, for example. However, in procedures with increase of the risk factors between levels 0 and 1, such as in cholecystectomies and genitourinaries procedures, even when an increase in the SSI rate was detected in levels 2 and 3, this did not adequately reflect the increasing risk due to the insufficient number of surgeries in these levels. In other surgical procedures, however, even with a sufficient number of stable cases in the first two risk levels (0 and 1) as in abdominal hysterectomies e appendectomies; in levels 3 and 4 the tendency was not confirmed. That is, in our databank, the inherent risk level per surgical procedure was not reflected adequately in the NNIS classification.14 The predominance of surgeries involving the abdominal cavity, (which has a high infection risk, e.g. > 9%) permits the observation of an increasing linear tendency of the frequency of SSI that could have been effectively confirmed with a larger number of surgical procedures. This limitation was originated after grouping categories that could more clearly reflect the inherently procedure-specific risk to enable SSI rates comparison. More importantly than just simple grouping, the distribution of the procedure in risk grades (Table 2) permits the interpretation of the value of SSI rate, taking into account the risk inherent in the surgical procedure. To use this methodological approach in SSI epidemiological surveillance, the process of distribution of the surgical procedures in the risk grades should be dynamic, that is, it should change with each addition of a consistent number of surgeries, half-yearly or yearly, for example. The ratios of the standardized SSI (SSIR) vary considerably between professionals and categories, as it was shown in Table 4. The criteria for differentiating between two surgeons with equal scores was the number of procedures performed. Therefore a surgeon who operated more and thus exposed himself/herself to a greater risk ought to get a superior performance classification than another who had not performed so many interventions. The HAI risk factors have been sufficiently studied in the last two decades and the complexity involving the SSI phenomenon also has been studied with multivariable regression models using extensive databanks in the SENIC and the NNIS studies. 31 Some authors have demonstrated that the variables used in the NNIS study (surgical procedure duration or ASA score) are not necessarily associated to SSI in certain specific surgical procedures.29,30 Those studies recommend the development of a combination of specific risk factors for certain surgeries because they may be more predictive of SSI risk than the NNIS index alone.25 Other studies recommend that infection control committees should focus on large, clean surgeries, such as the hip prostheses, due to the morbidity, mortality and economic impact of an SSI in these procedures.17 As the classical risk factors have already been established,14,20, the challenge now facing the infection control comittee is to integrate this knowledge in the practical context of daily SSI surveillance.31 The use of the SSIR, as suggested, permits the identification of local comparison references making it possible to detect more clearly changes of SSI risk behavior or to monitor trends between different surgeons or surgical procedures.

CONCLUSION We believe that the proposed methodological approach to SSI standardized comparison rates enhances the possibility of adopting preventive measures27, 32,33 towards a relatively simple approach which precludes the utilization of multivariable analysis models.

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COMPARISON OF SURGICAL SITE INFECTION RATES AMONG SURGEONS Nádia Mora Kuplich, Mário Bernardes Wagner, Ricardo de Souza Kuchenbecker, Rodrigo Pires dos Santos.

Table 1. Operative procedure and SSI rates by NNIS risk index category, HCPA, (N=5023).

Operative procedure category

NNIS Risk Index 0

Description

Code

Nº

SSI rate(%)

Nº

SSI rate(%)

Nº

SSI rate(%)

Nº

SSI rate(%)

9.1

0.0 16.7

Herniorraphy

HER

387

3.6

130

10.0

Cholecystectomy

CHOL

242

5.8

220

8.2

8.0

Open reduction of fracture

166

1.2

115

3.5

0.0

Appendectomy

APPY

0.0

3.4

25.0

0.0

Colon

COLO

0.0

26.9

32.2

40.0

Coronary artery bypass graft

CABG

0.0

4.5

0.0

Mastectomy

MAST

132

3.8

7.8

0.0

Other genitourinary

OGU

311

5.1

291

6.5

26.0

100.0

Gastric

GAST

12.5

20.8

12.5

0.0

23.1

20.0

Other hem/lymph system

OBL

Other digestive

OGIT

0.0

105

1.9

27.0

12.5

Other endocrine system

OES

2.1

13.3

25.0

0.0

Other nervous system

ONS

Other integumentary system

OSKN

3.4

8.8

5.3

Prostatectomy

PRST

1.2

13.8

19.4

32.3

Laparotomy

XLAP

14.8

6.7

23.4

Skin graft

SKGR

7.1

0.0

Nephrectomy

NEPH

0.0

5.6

0.0

Vascular

196

2.6

10.4

16.7

0.0

Cardiac

CARD

6.7

20.0

0.0

Abdominal hysterectomy

HYST

165

7.3

12.5

0.0

Other musculoeskeletal

OMS

273

1.8

159

6.3

5.6

0.0

Thoracic

THOR

0.0

23.5

27.3

Knee/Hip

PROS

2.9

0.0

Vaginal hysterectomy

VHYS

0.0

6.5

5.9

0.0

Other obstetric

OOB

0.0

Limb amputation

AMP

0.0

7.4

10.0

20.0

Head and neck

50.0

100.0

Liver/pancreas

BILI

24.6

18.5

29.4

33.3

Splenectomy

SPLE

0.0

Organ transplant

0.0

100.0

Other ENT (ear, nose, and throat).

OENT

9.1

33.3

0.0

37.5

0.0

Small bowel

0.0

27.3

Ventricular shunt

VSHN

0.0

Cholecystectomy with laparoscope

CHL2

0.0

25.0

Herniorraphy with laparoscope

HER2

0.0

Laparotomy with laparoscope

XLP2

0.0

Other eye

OEYE

0.0

Other respiratory

ORES

0.0

Spinal fusion

FUS

0.0

2330

1929

670

N: number of operative procedures in each NNIS risk index category , SSI expressed per 100 operations.

J Infect Control 2012; 1 (2): 26-32

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COMPARISON OF SURGICAL SITE INFECTION RATES AMONG SURGEONS Nádia Mora Kuplich, Mário Bernardes Wagner, Ricardo de Souza Kuchenbecker, Rodrigo Pires dos Santos.

Table 2. Operative procedures according to risk index category, occurrence of surgical site infection (SSI) and SSI rate (%), HCPA, 1996 (N=4627). N

SSI frequency

SSI Rate (%)

Low risk (< 2%)

Risk Index category

698

1.43

Medium-low (> 2% a <5%)

1056

3.31

Medium-high (> 5% a <9%)

1752

116

6.62

High risk (> 9%)

1121

207

18.47

4627

368

SSI: surgical site infection; SSI rate (%): SSI expressed per 100 operations.

Table 3. Surgeon and operative procedure performed by risk index category, Observed SSI (OSSI), Observed SSI rate (OSSI rate, %). Expected SSI (ESSI) and Expected SSI rate (ESSI rate, %) Surgeon (code)

Risk Index category

OSSI

OSSI rate (%)

ESSI

ESSI rate (%)

14.29

3.88

18.47

7.41

4.99

18.47 1.43

0.00

0.29

101

179

1.68

5.92

3.31

101

193

2.59

12.78

6.62 18.47

101

226

12.39

41.74

102

1.19

2.78

3.31

102

9.38

4.24

6.62

102

27.40

13.48

18.47

103

8.47

1.95

3.31

103

118

7.63

7.81

6.62 18.47

103

19.64

10.34

104

0.00

0.56

1.43

104

102

2.94

6.75

6.62

105

8.06

2.05

3.31

105

9.52

4.17

6.62

105

14.29

9.05

18.47

106

2.44

2.71

3.31

106

114

7.89

7.55

6.62

106

100

22.00

18.47

202

0.00

0.56

1.43

203

2.00

0.72

1.43

204

3.51

0.82

1.43

204

5.08

1.95

3.31

205

101

0.00

1.44

1.43

205

3.03

1.09

3.31

206

0.00

0.50

1.43

207

1.85

0.77

1.43

207

0.00

0.70

3.31

207

0.00

1.32

6.62

301

4.00

0.83

3.31

301

12.70

4.17

6.62

401

0.00

1.39

3.31

402

2.04

1.62

3.31

402

25.00

8.87

18.47

403

2.94

1.13

3.31

403

10.26

7.20

18.47

502

1.39

1.03

1.43

502

35.37

15.15

18.47

602

0.00

0.33

1.43 (CONTINUES)

J Infect Control 2012; 1 (2): 26-32

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COMPARISON OF SURGICAL SITE INFECTION RATES AMONG SURGEONS Nádia Mora Kuplich, Mário Bernardes Wagner, Ricardo de Souza Kuchenbecker, Rodrigo Pires dos Santos.

Risk Index category

OSSI

OSSI rate (%)

ESSI

ESSI rate (%)

602

7.07

6.55

6.62

602

24.56

10.53

18.47

603

5.00

0.29

1.43

603

100

6.00

6.62

603

20.83

8.87

18.47

701

3.70

0.89

3.31 6.62

701

6.90

3.84

702

0.00

0.83

3.31

702

12.50

4.24

6.62

705

166

5.42

10.99

6.62

705

4.76

3.88

18.47

707

8.00

3.31

6.62

N: number of operative procedures by risk index category; SSI: surgical site infection; SSI expressed per 100 operations.

Table 4. Surgeon’s classification according to operational procedures and ratios of standardised surgical site infection (RSSSI). Details in the text. Surgeon (code)

SSI observed

SSI expected

RSSSI*

95 CI%

Classification

401

1.39

0.00

0.00 – 2.65

202

0.56

0.00

0.00 – 6.59

206

0.50

0.00

0.00 – 7.38

0.29

0.00

0.00 – 12.72

207

2.79

0.36

0.01 – 2.00

205

134

2.53

0.40

0.01 – 2.20

4.99

0.40

0.05 – 1.45

104

141

7.31

0.41

0.08 – 1.20

101

598

60.44

0.60

0.42 – 0.82

9 10

403

8.33

0.60

0.19 – 1.40

705

187

14.87

0.67

0.32 – 1.24

3.88

0.77

0.16 – 2.26

701

4.73

1.06

0.34 – 2.47

603

168

15.78

1.08

0.63 – 1.72

106

296

28.73

1.15

0.79 – 1.61

105

174

15.27

1.18

0.70 – 1.86

602

179

17.41

1.21

0.75 – 1.84

707

3.31

1.21

0.33 – 3.09

402

10.49

1.24

0.66 – 2.12

103

233

20.10

1.24

0.80 – 1.84

102

221

20.50

1.32

0.87 – 1.92

203

0.72

1.39

0.04 – 7.74

702

5.07

1.58

0.68 – 3.11

23 24

301

5.00

1.80

0.82 – 3.42

204

116

2.77

1.81

0.58 – 4.21

502

154

16.18

1.85

1.25 – 2.65

N: nº of operative procedures in each strata; SSI: surgical site infection; expressed per 100 operations.

J Infect Control 2012; 1 (2): 26-32

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COMPARISON OF SURGICAL SITE INFECTION RATES AMONG SURGEONS Nádia Mora Kuplich, Mário Bernardes Wagner, Ricardo de Souza Kuchenbecker, Rodrigo Pires dos Santos.

REFERENCES 1. 2.

3. 4.

5. 6. 7. 8.

9. 10.

11.

12.

13. 14.

15.

16.

17.

Wenzel RP, Pfaller MA. Feasible and desirable future targets for reducing the costs of hospital infections. J Hosp Infect 1991:94-98. Mangram AJ et al. The Hospital Infection Control Practices Advisory Committee. Guideline for Prevention of Surgical Site Infection 1999. Infect Control Hosp Epidemiol 1999, 20: 247-80. Pittet D, Boyce JM, Hand hygiene and patient care: pursing the Semmelweis legacy, The Lancet Infectious Diseases 2001; April: 9-20. National Nosocomial Infections Surveillance (NNIS) System Report, Data Summary from January 1992 to June 2002, issued 2002. Am J Infect Control 2002; 30: 458-475. Nichols RL. Surgical wound infection, Am J of Medicine 1991; 91(Suppl 3B): 54-64. Menzies D. Postoperative wound infection. Surgical Infection 1993; 6: 3-7 Sherertz RJ, Garibaldi RA, Marosok RD et al. Consensus paper on the surveillance of surgical wound infections, Am J Infect Control 1992; 20: 263-270, Wagner MB, Hospital-acquired infections among surgical patients in Porto Alegre, Brazil:Risk factors for surgical wound infections, London: University of London (Ph,D, Thesis), 1995. Garibaldi RA, Cushing D, Lerer T. Risks factors for postoperative nosocomial infections. Am J Med 1991, 91(Suppl): 158S-163S. Grinbaum RS. Análise da validade dos índices preditivos do risco de infecção de sítio cirúrgico e desenvolvimento de modelo de ajuste para avaliação de cirurgias vasculares. São Paulo Universidade Federal de São Paulo- Escola Paulista de Medicina (Ph.D, Thesis), 1999. (Analysis of the validity of the predictive indices of infection in the surgical location and the development of an adjustment model for the evaluation of vascular surgery) Howard JM, Baker WF, Culbertson WR. Postoperative wound infections: the influence of ultraviolet irradiation of the operating room and of various other factors.Ann Surg 1964; 160 (Suppl):1-192. Haley RW, Culver DH, White JW, Morgan WM, Emori TG, Munn VP et al .The efficacy of infection surveillance and control programs in preventing nosocomial infections in US hospitals. Am J Epidemiol 1985; 121(2):182-205. Keats AS, The ASA classification of physical status- A recapitulation. Anesthesiology 1978, 49: 236-238. Culver DH, Horan TC, Gaynes RP, Martone WJ, Jarvis WR. Surgical wound infection rate by wound class, operative procedure and patient risk index. Am J Med 1991; 91 (Suppl. 3B): 152s-157s. National Nosocomial Infections Surveillance (NNIS) System. Nosocomial infection rates for interhospital comparison: limitations and possible solutions. Infect Control Hosp Epidemiol 1991; 12: 609-621. Campos ML, Cipriano ZM, Freitas PF. Suitability of the NNIS index for estimating surgical-site infection risk at a small university hospital in Brazil. Infect Control Hosp Epidemiol 2001, 22: 268-272. QI- Project-Indicator II-a: Surgical site infections. http:www.qiproject.org/

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18.

19. 20.

21.

22. 23. 24.

25. 26. 27. 28.

29.

30.

31.

32. 33.

Publicdata/Acute/Indicator2a/Index.asp acessado em 01/07/11. Gaynes RP et al. Surgical site infection(SSI) rates in the United States, 1992-1998: The National Nosocomial Infections Surveillance System Basic SSI Risk Index. Clin Infect Dis, 2001; 33(Suppl 2):S69-77. Kahn HA, Sempos CT. Statistical methods in Epidemiology. New York: Oxford University Press, 1989, 85-105. Gaynes RP. Surveillance of Surgical Site Infections: The NNIS Basic Risk Index, In: Recognition, surveillance, and management of Surgical Site Infections in the 21st, Continuing Education Dinner Symposium, 4th Decennial International Conference on Nosocomial and Healthcare-Associated Infections, March 2000:15-22, Atlanta, EUA. Haley RW, Schaberg DR, McClish DK, Quade D, Crossley KB, Culver DH et al. The accuracy of retrospective chart review in measuring nosocomial infection rates. Results of validation studies in pilot hospitals. Am J Epidemiol 1980; 111: 516-533. Glenister, HM et al. An evaluation of surveillance methods for detection of infections in hospital inpatients. J Hosp Infect 1993, 23: 229-224. Garner JS, Jarvis WR, Emori TG, Horan TC, and Hughes JM. CDC definitions for nosocomial infections, 1988. Am J Infect Control 1988; 16: 128-140. Horan TC et al. CDC definitions of nosocomial surgical site infections, 1992: a modification of CDC definitions of nosocomial surgical site infections. Am J Infect Control 1992, 20: 271-274. Emori TG et al. National nosocomial infections surveillance system (NNIS): description of surveillance methods. Am J Infect Control 1991, 19: 19-35. SPSS. SPSS Release 16.0. Chicago: SPSS Inc, 2010. Platt R. Progress in surgical-site infection surveillance. Infect Control Hosp Epidemiol 2002: 361-363. Roy MCR et al. Does the Centers for Diseases Control´s NNIS system risk index stratify patients undergoing by their risk of surgical-site infection? Infect Control Hosp Epidemiol 2000, 21: 186-190. Russo PL, Spelman DW. A new surgical-site infection risk index using risk factors identified by multivariate analysis for patients undergoing coronary artery bypass procedures. Infect Control Hosp Epidemiol 2002, 23: 372-376. Wagner MB, Silva NB, Vinciprova AR, Becker AB, Burtet LM, Hall AJ. Hospital-acquired infections among surgical patients in a Brazilian hospital. J Hosp Infect 1997, 35: 277-285. Martone WJ, Nichols RL. Recognition, Prevention, Surveillance, and Management of surgical site infections: Introduction to the problem and symposium overview. Clin Infect Dis 2001, 33, Suppl 2: S67-68. Kirby JP, Mazuski JE, Prevention of Surgical Site Infection. Surg Clin N Am 2009, 89: 365–389. Turtiainen J et al. Surgical wound infections after vascular surgery: prospective multicenter observational study. Scand J Surg. 2010: 99(3):167-72.

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Official Journal of the Brazilian Association of Infection Control and Hospital Epidemiology Professionals

ORIGINAL ARTICLE

Copper as an antimicrobial agent in healthcare: an integrative literature review Gleice Cristina Leite1, Maria Clara Padoveze1

School of Nursing, University of S達o Paulo, S達o Paulo/Brazil.

Received: 17/05/2012 Accepted: 10/07/2012 padoveze@usp.br

ABSTRACT Object: This study is an integrative literature review aiming to identify the potential application of copper surfaces to prevent infections in healthcare assistance. Methods: The descriptive study was conducted by searching the electronic Medline database and the Brazilian Copper Institute website using predefined descriptors. Papers published from 1990 in English, Spanish, French, Portuguese, and Italian were searched. For each article included in the integrative literature review, previously defined variables were analyzed including the range and the level of antimicrobial action

of cooper alloys, types of surfaces to be coated with the greatest potential for application in healthcare, and the potential interactions of copper with products used in healthcare. Results: The results showed an antimicrobial activity of copper with a significant reduction compared to other metals. Conclusion: Pure copper showed better results, followed by brass alloy with higher copper concentration, showing the need for studies that move further in this direction. Keywords: copper, antimicrobial, copper, copper surfaces, hospital infections

INTRODUCTION Copper has been used by human civilizations for millennia, being the first metal used by man, found in its native form.1 Its use became constant throughout the centuries, marking a presence in the technological evolution of man. Due to its physical and chemical properties, copper and its derivatives, such as bronze and brass, have shown durability and high resistance to corrosion and therefore, great utility and functionality.2 The sanitizing properties of copper have long been advocated, and some studies have reported the antimicrobial power of copper through different methods of analysis. Copper has been referred, along with other metals such as silver and iron ions, as a potentially useful element to control the environment associated with healthcare related infections.3 Studies have reported the antimicrobial power of copper, claiming that the use of pure and dry metal is better than alloys.4 The mechanism of cell death through contact with copper is not clearly established. It has been suggested that the involvement of

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copper ions in the process where these ions are in contact with the cell wall or membrane, provokes structural damage in eukaryotic cells, causing rupture and subsequently fragmenting their DNA.5 Touch surfaces commonly found in healthcare facilities may be potentially contaminated with microorganisms that cause Healthcare-Associated Infections (HAI).6 Such surfaces can act as ongoing sources of contamination by direct contact with the patient or indirectly through the hands of professionals. Regular cleaning combined with hand hygiene reduces the risk of microorganism transmission, but the reduction of the microbial load is always limited.7 Copper has been found among the potential resources applicable to the coating surface, in which the germicidal action could have a role in health service infection control. As copper refers to a resource little explored in healthcare, a review of the literature is needed in order to unveil its potential applicability and possible contraindications or side effects.

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COPPER AS AN ANTIMICROBIAL AGENT IN HEALTHCARE: AN INTEGRATIVE LITERATURE REVIEW Gleice Cristina Leite, Maria Clara Padoveze.

INTRODUCTION This is a descriptive study carried out by means of an integrative literature review, the method permitting search, critical evaluation and synthesis of available evidence regarding certain topics being investigated.8 Papers or congress healthcare related abstracts were included, in which there were indications of copper use as an antimicrobial agent. Papers, editorials or letters without original study data and papers concerning copper application in other situations not directly linked to healthcare, were excluded. Papers were obtained from the Medline electronic database and the Brazilian Copper Institute website. (www.procobre.org). The descriptors used were: copper; copper surfaces and antimicrobial copper. The following variables were analyzed: year of publication; study financing sources; study location (city/country); study type: (non experimental or experimental; descriptive or comparative); study duration (weeks); copper alloy type; type of surface or material used; microorganisms studied; microbial isolation methods: quantitative or qualitative; type of setting where the study was carried out; interaction with cleaners, drugs and other products used regularly in healthcare; contraindications or cautions in use; study objectives and results.

RESULTS There were a total of 4,580 papers in the databases. After applying the inclusion and exclusion criteria, with the elimination of repeats and evaluation of abstracts, 51 papers were selected for reading in full. Among them, there was a predominance of papers published in 2010; 43 (84,3%) were funded by companies linked to copper. The analysis of the papers showed that 11 countries conducted previous studies, predominantly the United Kingdom (13) and the United States (11). Only 37 papers fully met the inclusion criteria previously established and were analyzed to identify the variables previously defined. The objectives of the analyzed studies have in common the evaluation of the effectiveness of copper against microorganisms, whether through direct contact with copper or through the surfaces of biocide products based on copper (70.2%). The majority of research was carried out in institution labs (62.2%); studies carried out in healthcare assistance settings account for 29.7%. There was a predominance of comparative experimental studies with pre-defined inoculums (51.4%). In this type of study, a known inoculum is applied to different surfaces and the antimicrobial action is identified by counting the survivors after exposure to the surface. Among the studies analyzed, 12 (32.4%) of them presented their duration time, an average of 24.3 weeks. Studies using copper-based biocides had longer duration due to the need of repeated sampling for several consecutive days to verify the reduction of microorganisms. The types of alloys used in studies of the antimicrobial activity of copper are shown in Table 1. Thirty two (86.5%) studies used pure copper in the experiments and most of them used more than one type of alloy in order to assess which showed the best results.

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Regarding the surfaces used in the experiments, metal coupons with predefined measures, ranging from 1cm 2 to 3cm 2 were those used most. These coupons were aseptically prepared before use in order to compare the antimicrobial effect of the metals against previously known pathogens. Different organisms were used in the analyzed studies. The distribution frequency of micro-organisms used in studies of copper antimicrobial effectiveness can be seen in Figure 1. From the 37 studies analyzed, 22 (59.4%) inoculated more than one pathogen to test the antimicrobial action of copper. Studies that used metal coupons in research laboratories were able to quantify the bacteria before and after contact with the copper coupon or copper alloys in different time periods, allowing time to evaluate that inhibition occurs in the growth of the microorganisms studied. The evaluated studies were predominantly of the quantitative method (94.6%), which allows checking the amount of pathogens after contact with copper and copper alloys. The results were similar to each other with respect to the reduction of microorganisms when placed in contact with copper. This reduction was significant compared to other metals, especially when compared to stainless steel. Pure copper (Cu 100%) showed the best results, followed by alloys containing a higher concentration of metal, bronze for example. Amongst the alloys tested in the studies, pure copper followed by bronze and copper-nickel (CuNi) were those used the most. Studies using solutions of copper-based biocides also had satisfactory results, exerting antimicrobial activity at the site and maintaining the bacterial growth inhibition. Table 2 presents the average time and average reduction of microorganisms in the main studies regarding the use of pure copper. Only one study has not shown satisfactory results in relation to the significant decrease of microorganisms. The study was carried out with different fungal species tested in contact with copper and aluminium. The same method was applied to the different species, but one of them, Aspergillus niger, showed no significant decrease after 576 hours (24 days). The studies analyzed in this review had no data regarding any contraindication or caution situations for copper use in health services. One of the studies analyzed showed that copper does not fix to latex items, such as gloves, thus excluding studies using this type of testing material.

Table 1. Types of alloys used in studies on the antimicrobial activity of copper. S達o Paulo, June 2011. Number of studies= 37. Type of alloy

Frequency

Copper

86.5

Bronze

37.8

Cupronickel

35.1

CuNiZn (Cupronickel Zinc)

13.5

Other copper alloys (*)

24.3

Other alloys without copper (**)

21.6

Stainless steel

43.2

Uninformed

2.7

(*) Other copper alloys: CuFe, CuCr, CuAg, CuAl and copper-based solutions. (**) Other alloys without copper: Tin, Silver, Aluminum, Nickel, Titanium, Cobalt, Zinc, Chromium, Lead, Molybdenum, Zirconium, Plastic.

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COPPER AS AN ANTIMICROBIAL AGENT IN HEALTHCARE: AN INTEGRATIVE LITERATURE REVIEW Gleice Cristina Leite, Maria Clara Padoveze.

Figure 1. Frequency distribution of micro-organisms used in studies of antimicrobial efficacy of copper, São Paulo, June 2011. Number of studies = 37 (#).

MRSA (Methicillin Resistant Staphylococcus aureus), VRE (Vancomycin resistant Enterococci), HIV1 (Human Immunodeficiency Virus 1). (#) Some papers assessed more than one species of microorganism.

Table 2. Average time and amount of reduction of microorganisms in studies evaluating pure copper (Cu 100%). Number of studies = 32. São Paulo, June 2011. Main microorganism

Average time (minutes)

Average reduction (Log)

Acinetobacter baumannii

60 – 180

Candida albicans

24 – 60

Clostridium difficile

80 – 220

Enterococcus sp

60 – 90

Escherichia coli

45 – 100

MRSA

60 – 120

Pseudomonas aeruginosa

60 – 72

NI *

Staphylococcus aureus

60 – 120

NI*

VRE

60 – 90

NI *

MRSA (Methicillin Resistant Staphylococcus aureus), VRE (Vancomycin resistant Enterococci), NI* Not Informed.

DISCUSSION The present literature review identified a high frequency of comparative experimental studies in order to find a copper alloy which is more effective against microorganisms. Experimental study with pre-defined inoculums is the best method to find appropriate responses to the antimicrobial action of previously known pathogens commonly found in hospitals. A metal used in comparison with copper alloys is stainless steel, a metal found predominantly in hospital settings, due to its appearance of cleanliness and corrosion resistance, but there are no advantages in using this antimicrobial metal. Recent studies have concluded that important microorganisms were found alive

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on stainless steel surfaces for an extended period. 5 These surfaces can act as reservoirs for the transfer of microorganisms between healthcare workers and patients; this method of transmission is one of the most frequent found in hospitals.9 Therefore it is reasonable that the majority of studies found in the present review favour research on pathogens most frequently found in hospital settings, MRSA, Escherichia coli, Candida albicans, and Staphylococcus sp., for instance. The present literature revision concludes that there is evidence that surfaces of copper and copper alloys reduce some living cells of bacteria when in contact with the metal. The results showed that pure copper has good efficacy when exposed to pathogens and its alloys containing high concentrations of copper also showed good results. The mode of action exerted by copper against microbial agents has not been determined in the studies evaluated. The mechanism of death by contact with the copper surface has not yet been clearly explained. It was found that bacteria placed in contact with the dry antimicrobial copper surface suffered the greatest impact, suggesting the involvement of dissolution of copper ions in the process.10 One of the alternatives suggested in the studies is that cell membrane can be subjected to stress caused by the copper surface, where membrane damage occurring in contact with the copper surface leads to physical disruption of cells and consequently cell lysis. Another suggestion proposes a model of DNA damage as a subjacent mechanism.4 The Centres for Disease Control and Prevention (CDC) guideline for preventing infections associated with the environment included copper among other elements to be evaluated in future research to prevent contamination of water systems by Legionella spp. The same guide cites the possible incorporation of copper in

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COPPER AS AN ANTIMICROBIAL AGENT IN HEALTHCARE: AN INTEGRATIVE LITERATURE REVIEW Gleice Cristina Leite, Maria Clara Padoveze.

building materials with a view to a fungicide effect, targeting the prevention of Aspergillus sp infections.11 Assessment developed by Wexford Labs, DKI and HillRom, on behalf of the Copper Development Association to identify the effect of disinfectants on copper alloy surfaces, indicate the possible use of the most frequently used germicidal agents in healthcare institutions.12 However, this use in clinical practices has not been sufficiently explored. Despite the knowledge of very ancient civilizations in the use of copper, this review identified a major gap in information regarding the toxicity and potential interactions with substances used in healthcare, pointing out the need for studies that go further in this direction. In conclusion, the present study demonstrated that there is evidence of an antimicrobial action of copper, although the mechanism is still not well understood. Surfaces with pure copper showed the best effects on microorganisms, followed by alloys containing high concentrations of copper. The antimicrobial effect of copper showed variations in time and degree, related to

the reduction of microorganisms according to different species. Studies to recognize aspects of toxicity and interactions with products used in healthcare can contribute to the evaluation of the potential use of copper as an agent for preventing healthcare-associated infections.

ACKNOWLEDGEMENTS This study was sponsored by Brazilian Copper Institute, International Cooper Association, Ltda. The study design, data collection, analysis and interpretation of data, writing of manuscript and the decision to submit the manuscript for publication was independently carried out by the authors.

CONFLICT OF INTEREST STATEMENT The authors declare that there is no conf lict of interest related to the present study.

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Dollvet HHA, Sorenson JRJ. Historic uses of copper compounds in medicine. Trace Elem Med. 1985; 2: 80-7. Silva CB, Bizinelli DF, Balmant FF. Cobre. Trabalho de Pesquisa apresentado Ă Disciplina de Conforto Ambiental II. Curitiba, 2005. Rutala WA, Weber DJ and the Healthcare Infection Control Practices Advisory Committee (HICPAC). Guideline for Disinfection and Sterilization in Healthcare Facilities, 2008. EspĂrito Santo C, Lam EW, Elowsky CG, Quaranta D, Domaille DW, Chang CJ, Grass G. Bacterial killing by dry metallic copper surfaces. Appl Environ Microbiol. 2011; 77 (3): 794-802. Grass G, Rensing C, Solioz M. Metallic copper as an antimicrobial surface. Appl Environ Microbiol. 2011. 77(5): 1541-47. Karlin KD. Metalloenzymes, structural motifs and inorganic models. Science, 1993; 261: 701-8. Dancer SJ. Importance of the environment in methicillin-resistant Staphylococcus aureus acquisition: the case of hospital cleaning. Lancet

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Infect Dis. 2008; 8: 101-113. Whittemore R, Knafl K. The integrative review: updated methodology. J Adv Nurs. 2005 Dec; 52(5): 546-53. Halvani M, Solaymani-Dodaran M, Grundmann H, Coupland C, Slack RJ. Cross-transmission of nosocomial pathogens in an adult intensive care unit: incidence and risk factors. J Hosp Infect. 2006; 63: 39-46. Elguindi J, Wagner J, Rensing C. Genes involved in copper resistance influence survival of Pseudomonas aeruginosa on copper surfaces. J Appl Microbiol. 2009; 106: 1448-55. Sehulster LM, Chinn RYW, Arduino MJ, et al. Guidelines for Environmental infection control in health-care facilities. Recommendations from CDC and the Healthcare Infection Control Practices Advisory Committee (HICPAC). Chicago IL; American Society for Healthcare Engineering/American Hospital Association; 2004. PROCOBRE Connects Life. Common Disinfectants for Copper Touch Surfaces. Personal communication.

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