CFR 5.2 by Radcliffe Cardiology

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Volume 5 • Issue 2 • Summer 2019

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Bidirectional Relationship Between Cancer and Heart Failure: Old and New Issues in Cardio-oncology Edoardo Bertero, Pietro Ameri and Christoph Maack

Treating Patients Following Hospitalisation for Acute Decompensated Heart Failure: An Insight into Reducing Early Rehospitalisations Attilio Iacovoni, Emilia D’Elia, Mauro Gori, Fabrizio Oliva, Ferdinando Luca Lorini and Michele Senni

Remote Management of Heart Failure: An Overview of Telemonitoring Technologies Darshan H Brahmbhatt and Martin R Cowie

The Limitations of Symptom-based Heart Failure Management Lampros Papadimitriou, Charles K Moore, Javed Butler and Robert C Long

Diet, the gut microbiome and heart failure

Heart with pain centre

Remote management of heart failure: ICD

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Volume 5 • Issue 2 • Summer 2019

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Editor-in-Chief Andrew JS Coats Monash University, Melbourne, Australia and University of Warwick, Coventry, UK

Deputy Editor-in-Chief Giuseppe Rosano Department of Medical Sciences, IRCCS San Raffaele, Rome, Italy; Cardiology Clinical Academic Group, St George’s Hospitals NHS Trust, University of London, UK

Associate Editor Cristiana Vitale Department of Medical Sciences, IRCCS San Raffaele, Rome, Italy

Editorial Board William T Abraham

Michael B Fowler

Ali Ahmed

Michael Fu

The Ohio State University, US

National University Heart Center, Singapore

Washington DC VA Medical Center, US

Sahlgrenska University Hospital, Sweden

Inder Anand

David L Hare

University of Minnesota, US

John Atherton

Royal Brisbane and Women’s Hospital, Australia

Michael Böhm

Saarland University, Germany

Alain Cohen-Solal

Paris Diderot University, France

Henry J Dargie

Western Infirmary, Glasgow

Carmine De Pasquale

Flinders University, Australia

Frank Edelmann

Charité University Medicine, Germany

Cover image © stock.adobe.com.

Kian-Keong Poh

Stanford University, US

University of Melbourne, Australia

Michael Henein

A Mark Richards University of Otago, New Zealand

Jose Antonio Magaña Serrano National Medical Centre, Mexico

Heart Centre and Umea University, Sweden

Martin St John Sutton

Adelino Leite-Moreira

Hospital of the University of Pennsylvania, US

University of Porto, Portugal

Allan D Struthers

Alexander Lyon

Ninewells Hospital & Medical School, UK

Imperial College London, UK

Theresa A McDonagh King’s College Hospital, UK

Kenneth McDonald

St Vincent’s Hospital, Ireland

Michal Tendera University of Silesia, Poland

Maurizio Volterrani IRCCS San Raffaele Pisana, Italy

Cheuk Man Yu

Ileana L Piña

Montefiore Einstein Center for Heart & Vascular Care, US

The Chinese University of Hong Kong, Hong Kong

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Published by Radcliffe Cardiology. All information obtained by Radcliffe Cardiology and each of the contributors from various sources is as current and accurate as possible. However, due to human or mechanical errors, Radcliffe Cardiology and the contributors cannot guarantee the accuracy, adequacy or completeness of any information, and cannot be held responsible for any errors or omissions, or for the results obtained from the use thereof. Published content is for information purposes only and is not a substitute for professional medical advice. Where views and opinions are expressed, they are those of the author(s) and do not necessarily reflect or represent the views and opinions of Radcliffe Cardiology. Radcliffe Cardiology, Unit F, First Floor, Bourne End Business Park, Cores End Road, Bourne End, Buckinghamshire SL8 5AS, UK © 2019 All rights reserved ISSN: 2057–7540 • eISSN: 2057–7559

Established: March 2015 | Frequency: Quarterly | Current issue: Summer 2019

Aims and Scope

Submissions and Instructions to Authors

• Cardiac Failure Review aims to assist time-pressured physicians to stay abreast of key advances and opinion in heart failure. • Cardiac Failure Review comprises balanced and comprehensive articles written by leading authorities, addressing the most pertinent developments in the field. • Cardiac Failure Review provides comprehensive updates on a range of salient issues to support physicians in continuously developing their knowledge and effectiveness in day-to-day clinical practice.

• Contributors are identified by the Editor-in-Chief with the support of the Editorial Board and Managing Editor. • Following acceptance of an invitation, the author(s) and Managing Editor, in conjunction with the Editor-in-Chief, formalise the working title and scope of the article. • The ‘Instructions to Authors’ document and additional submission details are available at www.CFRjournal.com • Leading authorities wishing to discuss potential submissions should contact the Managing Editor, Rosie Scott rosie.scott@radcliffe-group.com

Structure and Format • Cardiac Failure Review is a quarterly journal comprising review articles, expert opinion articles and guest editorials. • The structure and degree of coverage assigned to each category of the journal is the decision of the Editor-in-Chief, with the support of the Editorial Board. • Articles are fully referenced, providing a comprehensive review of existing knowledge and opinion. • Each edition of Cardiac Failure Review is available in full online at www.CFRjournal.com

Reprints All articles included in Cardiac Failure Review are available as reprints. Please contact the Sales Director, Rob Barclay rob.barclay@radcliffe-group.com

Distribution and Readership Cardiac Failure Review is distributed quarterly through controlled circulation to senior healthcare professionals in the field in Europe.

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Abstracting and Indexing

Cardiac Failure Review is supported by various levels of expertise: • Overall direction from an Editor-in-Chief, supported by the Editorial Board comprising leading authorities from a variety of related disciplines. • Invited contributors who are recognised authorities in their respective fields. • Peer review – conducted by experts appointed for their experience and knowledge of a specific topic. • An experienced team of Editors and Technical Editors.

CFR is abstracted, indexed and listed in PubMed and Crossref. All articles are published in full on PubMed Central one month after publication.

Peer Review • On submission, all articles are assessed by the Editor-in-Chief to determine their suitability for inclusion. • The Managing Editor, following consultation with the Editor-in-Chief sends the manuscript to reviewers who are selected on the basis of their specialist knowledge in the relevant area. All peer review is conducted double-blind. • Following review, manuscripts are accepted without modification, accepted pending modification (in which case the manuscripts are returned to the author(s) to incorporate required changes), or rejected outright. The Editor-in-Chief reserves the right to accept or reject any proposed amendments. • Once the authors have amended a manuscript in accordance with the reviewers’ comments, the manuscript is assessed to ensure the revised version meets quality expectations. The manuscript is sent to the Editor-in-Chief for final approval prior to publication.

Open Access, Copyright and Permissions Articles published within this journal are open access, which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly. The author retains all non-commercial rights for articles published herein under the CC-BY-NC 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/ legalcode). Radcliffe Cardiology retain all commercial rights for articles published herein unless otherwise stated. Permission to reproduce an article for commercial purposes, either in full or in part, should be sought from the publication’s Managing Editor. To support open access publication costs, Radcliffe Cardiology charge an Article Publication Charge (APC) to authors upon acceptance of an unsolicited paper as follows: £1,050 UK | €1,200 Eurozone | $1,369 all other countries. Waivers are available as specified in the ‘Information for authors’ section on www.CFRjournal.com.

Online All manuscripts published in Cardiac Failure Review are available free to view at www.CFRjournal.com. Also available at www.radcliffecardiology.com are articles from other journals within Radcliffe Cardiology’s cardiovascular portfolio – including, Arrhythmia and Electrophysiology Review, Interventional Cardiology Review, European Cardiology Review and US Cardiology Review.

Cardiology

Lifelong Learning for Cardiovascular Professionals

Contents

Foreword Andrew JS Coats and Giuseppe Rosano

DOI: https://doi.org/10.15420/cfr.2019.14.1

Clinical Practice Use of Renin–Angiotensin–Aldosterone System Inhibitors in Older Patients with Heart Failure and Reduced Ejection Fraction

Davide Stolfo and Gianluigi Savarese DOI: https://doi.org/10.15420/cfr.2019.6.2

The Limitations of Symptom-based Heart Failure Management

Lampros Papadimitriou, Charles K Moore, Javed Butler and Robert C Long DOI: https://doi.org/10.15420/cfr.2019.3.2

Treating Patients Following Hospitalisation for Acute Decompensated Heart Failure: An Insight into Reducing Early Rehospitalisations

Attilio Iacovoni, Emilia D’Elia, Mauro Gori, Fabrizio Oliva, Ferdinando Luca Lorini and Michele Senni DOI: https://doi.org/10.15420/cfr.2018.46.2

Winter Peaks in Heart Failure: An Inevitable or Preventable Consequence of Seasonal Vulnerability?

Simon Stewart, Trine T Moholdt, Louise M Burrell, Karen Sliwa, Ana O Mocumbi, John JV McMurray, Ashley K Keates and John A Hawley DOI: https://doi.org/10.15420/cfr.2018.40.2

Remote Management of Heart Failure: An Overview of Telemonitoring Technologies

Darshan H Brahmbhatt and Martin R Cowie DOI: https://doi.org/10.15420/cfr.2019.5.3

Hospice Use Among Patients with Heart Failure

Sarah H Cross, Arif H Kamal, Donald H Taylor Jr and Haider J Warraich DOI: https://doi.org/10.15420/cfr.2019.2.2

Co-morbidities Aortic Stenosis and Heart Failure: Disease Ascertainment and Statistical Considerations for Clinical Trials

Ernest Spitzer, Rebecca T Hahn, Philippe Pibarot, Ton de Vries, Jeroen J Bax, Martin B Leon and Nicolas M Van Mieghem DOI: https://doi.org/10.15420/cfr.2018.41.2

Bidirectional Relationship Between Cancer and Heart Failure: Old and New Issues in Cardio-oncology

106

Edoardo Bertero, Pietro Ameri and Christoph Maack DOI: https://doi.org/10.15420/cfr.2019.1.2

Heart Failure and Cancer: Mechanisms of Old and New Cardiotoxic Drugs in Cancer Patients

112

Alessandra Cuomo, Alessio Rodolico, Amalia Galdieri, Michele Russo, Giacomo Campi, Riccardo Franco, Dalila Bruno, Luisa Aran, Antonio Carannante, Umberto Attanasio, Carlo G Tocchetti, Gilda Varricchi and Valentina Mercurio DOI: https://doi.org/10.15420/cfr.2018.32.2

Diet, the Gut Microbiome and Heart Failure

119

Sivadasanpillai Harikrishnan DOI: https://doi.org/10.15420/cfr.2018.39.2

Foreword

Andrew JS Coats is the inaugural Joint Academic Vice-President of Monash University, Australia and the University of Warwick, UK and Director of the Monash Warwick Alliance

Giuseppe Rosano is Professor of Pharmacology, Director of the Centre of Clinical and Experimental Medicine at the IRCCS San Raffaele, Italy and Professor of Cardiology and Consultant Cardiologist (Hon) at St George's University of London, UK

t is with great pleasure that we introduce to you, our readers, to volume 5, issue 2 of Cardiac Failure Review. This issue we are focusing on clinical syndromes and the impact and therapy of selected comorbidities commonly seen in the heart failure (HF) patient.

Stolfo and Savarese take another look at the landmark trials of angiotensin-converting enzyme (ACE) inhibitors in HF from the perspective of the more elderly patient. It is well known that patients enrolled in randomised clinical trials do not accurately reflect real-world HF patients, especially with regard to age. A relative lack of evidence, combined with a heightened risk of side-effects and polypharmacy in the elderly, with the risk of more adverse drug interactions, often leads to relative under-treatment of older patients. Despite uniform guideline recommendations for first-line ACE inhibitor use in HF with reduced ejection fraction (HFrEF) patients, irrespective of age, there is persistent evidence of underuse of these agents in the elderly. The mean age of patients with HF is increasing, exceeding 75 years in most series, yet the mean age in HFrEF trials is over a decade younger. In large registry analyses, about 20% of patients aged >80 years have been shown not to receive ACE inhibitors/angiotensin receptor blockers (ARBs). Older adults are at higher risk of cardiovascular events, and thus may potentially benefit from HF medications even more than younger patients. The authors review the major reasons for underuse of these agents in the elderly, including chronic kidney disease, hyperkalemia and drops in systolic blood pressure. They believe that careful monitoring, modification of diuretic dosages and the use of potassium binders may prevent or correct these features being the reason for underuse of ACE inhibitors or ARBs. They remind us that in the Euro Heart Failure Survey II the use of these agents was associated with improved outcome in octogenarians even after adjustment for confounding factors They also investigated the association between renin–angiotensin–aldosterone system inhibitor use and outcomes (i.e. all-cause mortality, all-cause mortality or HF hospitalisation) in the SwedeHF registry, which includes one of the largest cohorts of HFrEF older patients worldwide. Of 6,710 HFrEF patients aged >80 years and through the technique of propensity score matching, they reached the conclusion that even in these older HF patients, survival could be significantly improved with active therapy and only nine patients would need to be treated to save one life in 1 year. These findings should be interpreted as hypothesis generating for future prospective trials. Papadimitriou and colleagues then offer us an unusual perspective on our usual approach to care in HF, that of what they call ‘symptombased HF management’. First, they question the reliability, accuracy and reproducibility of the symptom-based classification which we almost all use, the New York Heart Association (NYHA) class, arguing instead for more objective measures of activity tolerance, such as the 6-minute walk test or cardiopulmonary exercise testing, despite practical limitations in some patients. Rather like our first paper, they review how common undertreatment of HF is in the community, with the Change the Management of Patients with Heart Failure trial revealing in real-life conditions that only 1% of patients were receiving all guideline-directed medical therapy at target doses. They argue for treating HF more aggressively at earlier stages and rigorously, even in more advanced stages, based on parameters more objective than the NYHA class. They conclude that “ongoing and future clinical trials will provide the data necessary to advance this treatment strategy among healthcare professionals and patients as a significant culture change”. Yet we all know how difficult true culture change can prove to be. Iacovoni and colleagues then review the treatment of patients following hospitalisation for acute decompensated HF, one of the largest areas of HF where treatment trials have failed so consistently. They argue that the high burden and cost of early rehospitalisation after discharge should be avoided, and in addition, that it has a negative influence on subsequent survival. They argue for a targeted yet more aggressive

DOI: https://doi.org/10.15420/cfr.2019.14.1

Access at: www.CFRjournal.com

Foreword

approach to HF drug therapy during hospitalisation and in the immediate post-discharge period, and that if implemented consistently, this could improve HF outcomes over the longer term. Stewart and colleagues review the evidence for seasonal peaks in the incidence of and hospitalisations for HF. They present a model of ‘seasonal flexibility’ to explain the spectrum of individual responses to climatic conditions. They argue (and apologies for the oversimplification) that the way a society adapts and responds to climatic variations may be more important than extremes of weather experienced per se. Later in the issue, Brahmbhatt and Cowie review recent trials of telemonitoring in HF care. Telemonitoring with the use of audio, video and other telecommunication technologies to monitor patient status at a distance has advanced significantly in recent years. This field is large and ever changing, and of course each trial depends both on what is studied and the background care in the control group. Approaches can vary from structured telephone support, standalone home devices – which can measure blood pressure, heart rate, weight and oxygen saturation – implantable electronic devices and most recently, ‘wearable’ technologies, including patches, watches or textiles that can monitor certain functions, including ECG, body temperature, blood sugar concentration and body posture. Cross and colleagues review hospice use in HF patients, arguing that hospice care options are significantly underutilised in this setting. Defining hospice care as “team-based palliative care typically reserved for those with a life expectancy of 6 months or less”, they review disease, policy, clinical and other factors which affect the use of hospice care in HF. They also list seven recommendations for the optimisation of hospice care for HF. Lastly, we have excellent summaries on important comorbidities in HF, aortic valve disease, cancer and the effect of anti-cancer drugs and the emerging field of study of the effect of diet on the gut microbiome and how this could affect the condition of the HF patient.

Access at: www.CFRjournal.com

Clinical Practice

Use of Renin–Angiotensin–Aldosterone System Inhibitors in Older Patients with Heart Failure and Reduced Ejection Fraction Davide Stolfo 1,2 and Gianluigi Savarese 1 1. Division of Cardiology, Department of Medicine, Karolinska Institutet, Stockholm, Sweden; 2. Division of Cardiology, Cardiovascular Department, Azienda Sanitaria Universitaria Integrata di Trieste, Trieste, Italy

Abstract Patients enrolled in randomised clinical trials may not be representative of the real-world population of people with heart failure (HF). Older patients are frequently excluded and this limits the strength of evidence which supports the use of specific HF treatments in this patient group. Lack of evidence together with fear of adverse effects, drug interactions and lower tolerance may lead to the undertreatment of older patients and a less favourable outcome. Renin–angiotensin–aldosterone system (RAAS) inhibitors are the cornerstone of treatment for patients with HF with reduced ejection fraction (HFrEF), but despite the class I recommendation for all patients regardless of age in the guidelines, there are signs that RAAS inhibitors are underused among older patients. Large registrybased studies suggest that RAAS inhibitors may be at least as effective in older patients as younger ones, but these findings need to be confirmed by randomised clinical trials.

Keywords Clinical trials, evidence-based treatment, older patients, heart failure, reduced ejection fraction, renin–angiotensin–aldosterone system inhibitors Disclosure: GS has received research grants from Boehringer Ingelheim, Merck Sharp & Dohme, AstraZeneca, Vifor Pharma and Novartis; and honoraria from Vifor Pharma, Servier, Società Prodotti Antibiotici (SPA), AstraZeneca and Roche. DS has no conflicts of interest to declare. Received: 15 February 2019 Accepted: 19 April 2019 Citation: Cardiac Failure Review 2019;5(2):70–3. DOI: https://doi.org/10.15420/cfr.2019.6.2 Correspondence: Gianluigi Savarese, Department of Medicine, Cardiology Unit, Karolinska Institutet, Norrbacka S1:02, 171 76 Stockholm, Sweden. E: gianluigi.savarese@ki.se Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

Heart failure (HF) is a major and growing public health problem with high morbidity, mortality and costs.1 Due to the ageing the population, the mean age of patients with HF is increasing and exceeds 70 years in most developed countries. HF prevalence rises with age and exceeds 10% in people over 80.2 Older patients are more frail and have a higher risk of cardiovascular events. They also have a lower tolerance to medications and a higher occurrence of adverse effects and drug interactions, which may lead to undertreatment and an impaired prognosis.3 Moreover, the effects of evidence-based treatments for HF in terms of outcome have been poorly tested in older patients, and this group is largely under-represented in randomised clinical trials for HF.4,5

Renin–Angiotensin–Aldosterone System Inhibitor Use in Older People Activation of the renin–angiotensin–aldosterone system (RAAS) is a key feature of HF.6 Targeting the RAAS is a cornerstone of the medical management of HF with reduced ejection fraction (HFrEF). Indeed angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been shown to reduce mortality and morbidity in people with HFrEF.7–12 Although older patients represent a substantial HF subpopulation, mean age in HFrEF trials of RAAS inhibitors is 65 years (Table 1).

Access at: www.CFRjournal.com

Several reasons may explain the low recruitment of older patients in trials: • Older patients are less likely to be referred to cardiology care which prevents their enrolment in trials and registries. • Age is often featured in inclusion/exclusion criterion. • Age-related co-morbidities, such as chronic kidney disease, may be included in the exclusion criteria.13 In real-world clinical practice, there are major concerns about the underuse and under-prescription of RAAS inhibitors in older adults. In large registry analyses, about 20% of patients aged >80 years have been shown not to receive RAAS inhibitors.14–16 Renal function, perceived risk of dyskalemia, higher chance of drug interactions and side-effects, lower levels of referrals to specialist care and lower expectations of benefits due to a lack of evidence from trials are some of the potential explanations for the reluctance to use RAAS inhibitors in older people compared with younger HFrEF patients. According to the current HFrEF guidelines, RAAS inhibitors are recommended regardless of age.17 Indeed, older adults are at higher risk of cardiovascular events and thus may potentially benefit from HF medications even more than younger patients. However, there is poor evidence to support this.

Renin–Angiotensin–Aldosterone System Inhibitors in the Elderly Table 1: Summary of Landmark Heart Failure Trials on Renin–Angiotensin–Aldosterone System Inhibitors Trial

Year

Study Treatment

Patients (n)

Age (years)

Key Age-related

CONSENSUS10

1987

Enalapril

253

71, RAASI 70, no RAASI

–

SOLVD21

1991

Enalapril

2,569

Age <80 EF ≤35%

Val-HeFT12

2002

Valsartan

5,010

62±11, RAASI 67±10, no RAASI

EF ≤40%

CHARM-Alternative20

2003

Candesartan

2,028

66±11

EF ≤40% 23% of the study population <75 years

Inclusion Criteria

EF = ejection fraction; RAASI = renin–angiotensin–aldosterone system inhibitor.

Figure 1: Prognosis in Patients with Heart Failure with Reduced Ejection Fraction on Renin–Angiotensin–Aldosterone System Inhibitor Versus Those Not Receiving This Treatment A 1.00 0.75 0.50

Survival probability

0.25

HR 0.78; 95% CI [0.72–0.86]

HR 0.86; 95% CI [0.79–0.94] 1-year ARR 8%; NNT 12

1-year ARR 11%; NNT 9 0

Composite outcome

Survival free of HF hospitalisation 0.25 0.50 0.75 1.00

Overall mortality

Time (years)

HR 0.81; 95% CI [0.71–0.91]

1.00 0.75

Overall – RAASI yes

Matched – RAASI no

Matched – RAASI yes

0.50

Overall – RAASI no

HR 0.85; 95% CI [0.76–0.94] 1-year ARR 7%; NNT 14

1-year ARR 6%; NNT 17

0.25

0.75

Survival free of HF hospitalisation

1.00

Time (years)

0.50 0.25

Survival probability

Time (years)

The Kaplan–Meier curves for time to all-cause mortality and time to all-cause mortality/heart failure hospitalisation in renin–angiotensin–aldosterone system inhibitor versus non-renin– angiotensin–aldosterone system inhibitor users in the matched and overall cohorts with age >80 years (A) and ≤80 years (B; positive control analysis). ARR = absolute risk reduction; HF = heart failure; NNT = number needed to treat; RAASI = renin–angiotensin–aldosterone system inhibitor. Source: Savarese et al. 2018.15 Reproduced with permission from Oxford University Press.

Impaired Renal Function, Hyperkalemia and Hypotension Chronic kidney disease, hyperkalemia and drops in systolic blood pressure due to medications are probably the main reasons for the underuse or underdosage of RAAS inhibitors. Despite the protective effect of RAAS inhibitors on the incidence and progression of renal failure, patients with severe chronic kidney disease have been excluded from trials.7,18–21 Chronic kidney disease is a deterrent for RAAS inhibitor prescription in clinical practice.22–24 In a previous dedicated analysis from the Swedish Heart Failure Registry (SwedeHF), including 85,291 patients, focusing on chronic kidney disease, only 66% (n=2410) of patients with HFrEF and eGFR <30 mL/min/1.73m2

C A R D I A C FA I L U R E R E V I E W

were treated with RAAS inhibitors versus 93% of patients with normal renal function.25 Age was independently associated with renal failure but a propensity score matching analysis showed a similar benefit in patients with eGFR <30 mL/min/1.73m2 compared with patients without renal failure, supporting RAAS inhibitor use in HFrEF patients regardless of renal function.25 Hyperkalemia has been reported as a main determinant of RAAS inhibitor discontinuation in the inpatient setting in the Get With the Guidelines – Heart Failure (GWTG-HF) registry.26 In a large US database (with more than 205,000 patients), nearly 60% of HF patients who discontinued RAAS inhibitors due to hyperkalemia experienced an adverse outcome – progression of chronic kidney disease, stroke, acute MI or coronary artery

Clinical Practice revascularisation or death – compared with 52% of patients on submaximal doses and 44% of patients on target doses. Additionally, patients who discontinued medication had a twofold higher risk of mortality than those on tailored treatment.27 In the SwedeHF study, age was not an independent predictor of hyperkalemia.28 Hypotension is also a frequent reason for underdosing and underuse of RAAS inhibitors.29 Older people are more likely to experience hypotension and subsequent syncope. Careful monitoring, modifications in diuretic strategies and the use of potassium binders may prevent or correct these episodes, avoiding the withdrawal of lifesaving therapies. In case of temporary discontinuation, reinitiation or uptitration of therapy should be attempted as soon as safely possible.

Renin–Angiotensin–Aldosterone System Inhibitors and Outcomes in Older Patients Little randomised data are available on RAAS inhibitor use in older people. A meta-analysis of four HFrEF randomised trials showed ACEIs improved survival in patients aged ≤75 years, but not in those aged >75 years. However, there was no significant interaction between treatment and age and the small sample size of the older subgroup limited the power of the analysis.30 Conversely, small observational studies have reported better survival associated with the use of RAAS inhibitors in older versus younger patients.31,32 In the Euro Heart Failure Survey II, the use of RAAS inhibitors was associated with improved outcome in people in their 80s, even after adjustment for confounding factors.16 A similar conclusion was found by the US National Heart Care project, with the oldest patients (over 85 years) potentially benefiting even more.23 No specific data comparing the efficacy of ACEIs versus ARBs in older patients are available. However, data from meta-analyses as well as comparative trials suggest an advantage of ACEIs over ARBs in terms of cardiovascular mortality but not HF hospital admissions.33–35 Moreover, HF management remains a synergistic approach combining therapeutic regimens. The concomitant use of RAAS inhibitors and beta-blockers is by far the most effective strategy.36 Hence, delays in the initiation of the second drug should be avoided and, according to former comparative studies, beta-blockers may be initiated alone in case of worsening renal function or dyskalemia after introduction of RAAS inhibitors.37,38 We investigated the association between RAAS inhibitor use and outcomes (i.e. all-cause mortality; the composite of all-cause mortality and HF hospitalisation) in the SwedeHF, which includes one of the largest cohorts of older patients with HFrEF worldwide.15 Of 6,710 HFrEF patients aged >80 years enrolled between 2000 and 2012, 20% were not receiving RAAS inhibitors. After propensity score matching, 1-year and 3-year survival were significantly improved in treated (60% and 32%, respectively) versus untreated patients (49% and 26%). The absolute risk reduction was 11% and nine patients needed treatment to save one life in 1 year. Thus, over a median follow-up of 1.4 years, RAAS inhibitor use was associated with a 22% reduction in risk of all-cause death, which is comparable to what we observed in patients aged <80 years that were used as positive control and in randomised clinical trials testing RAAS inhibitors

2. 3.

oger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and R stroke statistics – 2012 update: a report from the American Heart Association. Circulation 2012;125:188–97. https://doi.org/ 10.1161/CIR.0b013e3182456d46; PMID: 22215894. Braunwald E. Heart failure. JACC Heart Fail 2013;1:1–20. https:// doi.org/10.1016/j.jchf.2012.10.002; PMID: 24621794. Pocock SJ, Wang D, Pfeffer MA, et al. Predictors of mortality

(Figure 1).10,12,20,21,39 This finding may suggest that similar results could be replicated in a trial setting. The greater absolute risk reduction observed in our registry analysis in patients aged >80 versus ≤80 years, together with the low proportion of elderly patients receiving >50% of the target dose of RAAS inhibitors (i.e. 53% of our elderly population), may suggest a greater benefit in terms of mortality risk reduction in older versus younger patients receiving RAAS inhibitors. Use of RAAS inhibitors was also associated with a 14% reduction in risk of all-cause mortality or HF hospitalisation (absolute risk reduction 8%, and 12 patients needed to be treated to prevent an event in one year) (Figure 1). Notably, the use of RAAS inhibitors was not associated with increased risk of syncope, which is one of the most important concerns in older patients receiving therapies that lower blood pressure. Based on the results of the Prospective Comparison of ARNI with ACEI to Determine Impact on Global Mortality and morbidity in Heart Failure (PARADIGM-HF) trial, it is now recommended that sacubitril–valsartan replace RAAS inhibitors in patients with HFrEF that remains symptomatic despite optimal medical therapy.17 Impact on outcome, safety profile and cost-effectiveness of this drug in older adults are still poorly known. Among the 8,399 patients recruited in the PARADIGM-HF trial, only 1,563 were >75 years old. In their analysis, Jhund et al found similar beneficial effects from sacubitril/ valsartan across the age spectrum. Hypotension, renal impairment and hyperkalemia increased with age in both treatment groups, but the differences between treatment (i.e. more hypotension but less renal impairment and hyperkalemia with sacubitril/valsartan) were consistent regardless of age.40

Unsolved Issues and Future Directions Older patients represent a majority in the HF population and largely differ from younger patients who are more commonly enrolled in randomised trials. The greater burden of cardiac and non-cardiac comorbidities, frailty and the disease progression expose them to a worse prognosis. The ageing of the population and the increasing prevalence of HF have determined an increasing demand on healthcare resources, leading to a dramatic impact on financial costs. There is a growing mismatch between the characteristics of patients included in clinical trials and those regularly seen in daily practice. Therefore, the medical community should dedicate more efforts toward implementing treatment strategies among older patients with HF. A stricter adhesion to the current evidence-based recommendations and a structured followup in dedicated HF clinics with an integrated multispecialty management may be the key to improving outcome in older patients with HF. Although the limited enrolment of older adults in randomised trials may limit the generalisability of trials’ results in the real-world for older people, increasing evidence from large, unselected registry populations suggests that RAAS inhibitors may be at least as effective in older patients as in younger patients with HFrEF.15,23 However, these findings may be interpreted as a hypothesis which generates randomised trials that investigate this specific issue.

and morbidity in patients with chronic heart failure. Eur Heart J 2006;27:65–75. https://doi.org/10.1093/eurheartj/ehi555; PMID: 16219658. Akita K, Kohno T, Kohsaka S, et al. Current use of guidelinebased medical therapy in elderly patients admitted with acute heart failure with reduced ejection fraction and its impact on event-free survival. Int J Cardiol 2017;235:162–8. https://doi.

org/10.1016/j.ijcard.2017.02.070; PMID: 28259550. Savarese G, Carrero JJ, Pitt B, et al. Factors associated with underuse of mineralocorticoid receptor antagonists in heart failure with reduced ejection fraction: an analysis of 11 215 patients from the Swedish Heart Failure Registry. Eur J Heart Fail 2018;20:1326–34. https://doi.org/10.1002/ejhf.1182; PMID: 29578280.

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Renin–Angiotensin–Aldosterone System Inhibitors in the Elderly 6.

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Lam CS, Lund LH. Microvascular endothelial dysfunction in heart failure with preserved ejection fraction. Heart 2016;102:257–9. https://doi.org/10.1136/heartjnl-2015-308852; PMID: 27655221. CONSENSUS Trial Study Group. Effects of enalapril on mortality in severe congestive heart failure. Results of the Cooperative North Scandinavian Enalapril Survival Study (CONSENSUS). N Engl J Med 1987;316:1429–35. https://doi. org/10.1056/NEJM198706043162301; PMID: 2883575. SOLVD Investigators, Yusuf S, Pitt B, et al. Effect of enalapril on mortality and the development of heart failure in asymptomatic patients with reduced left ventricular ejection fractions. N Engl J Med 1992;327:685–91. https://doi. org/10.1056/NEJM199209033271003; PMID: 1463530. Garg R, Yusuf S. Overview of randomized trials of angiotensinconverting enzyme inhibitors on mortality and morbidity in patients with heart failure. Collaborative Group on ACE Inhibitor Trials. JAMA 1995;273:1450–6. https://doi.org/10.1001/ jama.1995.03520420066040; PMID: 7654275. Swedberg K, Kjekshus J. Effects of enalapril on mortality in severe congestive heart failure: results of the Cooperative North Scandinavian Enalapril Survival Study (CONSENSUS). Am J Cardiol 1988;62:60A–66A. https://doi.org/10.1016/S00029149(88)80087-0; PMID: 2839019. Young JB, Dunlap ME, Pfeffer MA, et al. Mortality and morbidity reduction with candesartan in patients with chronic heart failure and left ventricular systolic dysfunction: results of the CHARM low-left ventricular ejection fraction trials. Circulation 2004;110:2618–26. https://doi.org/10.1161/01. CIR.0000146819.43235.A9; PMID: 15492298. Cohn JN, Tognoni G, Valsartan Heart Failure Trial I. A randomized trial of the angiotensin-receptor blocker valsartan in chronic heart failure. New Engl J Med 2001;345:1667–75. https://doi.org/10.1056/NEJMoa010713; PMID: 11759645. Lazzarini V, Mentz RJ, Fiuzat M, et al. Heart failure in elderly patients: distinctive features and unresolved issues. Eur J Heart Fail 2013;15:717–23. https://doi.org/10.1093/eurjhf/hft028; PMID: 23429975. Forman DE, Cannon CP, Hernandez AF, et al. Influence of age on the management of heart failure: findings from Get With the Guidelines-Heart Failure (GWTG-HF). Am Heart J 2009;157:1010–7. https://doi.org/10.1016/j.ahj.2009.03.010; PMID: 19464411. Savarese G, Dahlstrom U, Vasko P, et al. Association between renin-angiotensin system inhibitor use and mortality/ morbidity in elderly patients with heart failure with reduced ejection fraction: a prospective propensity score-matched cohort study. Eur Heart J 2018;39:4257–65. https://doi. org/10.1093/eurheartj/ehy621; PMID: 30351407. Komajda M, Hanon O, Hochadel M, et al. Contemporary management of octogenarians hospitalized for heart failure in Europe: Euro Heart Failure Survey II. Eur Heart J 2009;30:478–86. https://doi.org/10.1093/eurheartj/ehn539; PMID: 19106198. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail 2016;18:891–975. https://doi.org/10.1002/ejhf.592; PMID: 27207191.

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18. H eart Outcomes Prevention Evaluation Study Investigators. Effects of ramipril on cardiovascular and microvascular outcomes in people with diabetes mellitus: results of the HOPE study and MICRO-HOPE substudy. Heart Outcomes Prevention Evaluation Study Investigators. Lancet 2000;355:253–9. https://doi.org/10.1016/S01406736(99)12323-7; PMID: 10675071. 19. Brenner BM, Cooper ME, de Zeeuw D, et al. Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med 2001;345:861–9. https://doi.org/10.1056/NEJMoa011161; PMID: 11565518. 20. Granger CB, McMurray JJ, Yusuf S, et al. Effects of candesartan in patients with chronic heart failure and reduced leftventricular systolic function intolerant to angiotensinconverting-enzyme inhibitors: the CHARM-Alternative trial. Lancet 2003;362:772–6. https://doi.org/10.1016/S01406736(03)14284-5; PMID: 13678870. 21. SOLVD Investigators, Yusuf S, Pitt B, et al. Effect of enalapril on survival in patients with reduced left ventricular ejection fractions and congestive heart failure. N Engl J Med 1991;325:293–302. https://doi.org/10.1056/ NEJM199108013250501; PMID: 2057034. 22. Heywood JT, Fonarow GC, Yancy CW, et al. Influence of renal function on the use of guideline-recommended therapies for patients with heart failure. Am J Cardiol 2010;105:1140–6. https://doi.org/10.1016/j.amjcard.2009.12.016; PMID: 20381667. 23. Masoudi FA, Rathore SS, Wang Y, et al. National patterns of use and effectiveness of angiotensin-converting enzyme inhibitors in older patients with heart failure and left ventricular systolic dysfunction. Circulation 2004;110:724–31. https://doi.org/10.1161/01.CIR.0000138934.28340.ED; PMID: 15289383. 24. McAlister FA, Ezekowitz J, Tonelli M, Armstrong PW. Renal insufficiency and heart failure: prognostic and therapeutic implications from a prospective cohort study. Circulation 2004;109:1004–9. https://doi.org/10.1161/01. CIR.0000116764.53225.A9; PMID: 14769700. 25. Edner M, Benson L, Dahlstrom U, Lund LH. Association between renin-angiotensin system antagonist use and mortality in heart failure with severe renal insufficiency: a prospective propensity score-matched cohort study. Eur Heart J 2015;36:2318–26. https://doi.org/10.1093/eurheartj/ehv268; PMID: 26069212. 26. Gilstrap LG, Fonarow GC, Desai AS, et al. Initiation, continuation, or withdrawal of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers and outcomes in patients hospitalized with heart failure with reduced ejection fraction. J Am Heart Assoc 2017;6:pii: e004675. https://doi. org/10.1161/JAHA.116.004675; PMID: 28189999. 27. Epstein M, Reaven NL, Funk SE, et al. Evaluation of the treatment gap between clinical guidelines and the utilization of renin-angiotensin-aldosterone system inhibitors. Am J Manage Care 2015;21:S212–20. PMID: 26619183. 28. Savarese G, Xu H, Trevisan M, et al. Incidence, predictors, and outcome associations of dyskalemia in heart failure with preserved, mid-range, and reduced ejection fraction. JACC Heart Fail 2019;7:65–76. https://doi.org/10.1016/j. jchf.2018.10.003; PMID: 30553905. 29. Maggioni AP, Dahlstrom U, Filippatos G, et al. EURObservational Research Programme: regional differences and 1-year follow-up results of the Heart Failure Pilot Survey

(ESC-HF Pilot). Eur J Heart Fail 2013;15:808–17. https://doi. org/10.1093/eurjhf/hft050; PMID: 23537547. 30. F lather MD, Yusuf S, Kober L, et al. Long-term ACE-inhibitor therapy in patients with heart failure or left-ventricular dysfunction: a systematic overview of data from individual patients. ACE-Inhibitor Myocardial Infarction Collaborative Group. Lancet 2000;355:1575–81. https://doi.org/10.1016/ S0140-6736(00)02212-1; PMID: 10821360. 31. Ludvigsson JF, Andersson E, Ekbom A, et al. External review and validation of the Swedish national inpatient register. BMC Public Health 2011;11:450. https://doi.org/10.1186/1471-245811-450; PMID: 21658213. 32. Ahmed A, Centor RM, Weaver MT, Perry GJ. A propensity score analysis of the impact of angiotensin-converting enzyme inhibitors on long-term survival of older adults with heart failure and perceived contraindications. Am Heart J 2005;149:737–43. https://doi.org/10.1016/j.ahj.2004.06.030; PMID: 15990761. 33. Dickstein K, Kjekshus J. Effects of losartan and captopril on mortality and morbidity in high-risk patients after acute myocardial infarction: the OPTIMAAL randomised trial. Optimal Trial in Myocardial Infarction with Angiotensin II Antagonist Losartan. Lancet 2002;360:752-60. https://doi. org/10.1016/S0140-6736(02)09895-1; PMID: 12241832. 34. Heran BS, Musini VM, Bassett K, et al. Angiotensin receptor blockers for heart failure. Cochrane Database Syst Rev 2012:CD003040. https://doi.org/10.1002/14651858.CD003040. pub2; PMID: 12241832. 35. Pitt B, Poole-Wilson PA, Segal R, et al. Effect of losartan compared with captopril on mortality in patients with symptomatic heart failure: randomised trial – the Losartan Heart Failure Survival Study ELITE II. Lancet 2000;355:1582–7. https://doi.org/10.1016/S0140-6736(00)02213-3; PMID: 10821361. 36. Komajda M, Lapuerta P, Hermans N, et al. Adherence to guidelines is a predictor of outcome in chronic heart failure: the MAHLER survey. Eur Heart J 2005;26:1653–9. https://doi. org/10.1093/eurheartj/ehi251; PMID: 15827061. 37. Remme WJ, Riegger G, Hildebrandt P, et al. The benefits of early combination treatment of carvedilol and an ACE-inhibitor in mild heart failure and left ventricular systolic dysfunction. The carvedilol and ACE-inhibitor remodelling mild heart failure evaluation trial (CARMEN). Cardiovasc Drugs Ther 2004;18:57–66. https://doi.org/10.1023/ B:CARD.0000025756.32499.6f; PMID: 15115904. 38. Willenheimer R, van Veldhuisen DJ, Silke B, et al. Effect on survival and hospitalization of initiating treatment for chronic heart failure with bisoprolol followed by enalapril, as compared with the opposite sequence: results of the randomized Cardiac Insufficiency Bisoprolol Study (CIBIS) III. Circulation 2005;112:2426–35. https://doi.org/10.1161/ CIRCULATIONAHA.105.582320; PMID: 16143696. 39. Packer M, Poole-Wilson PA, Armstrong PW, et al. Comparative effects of low and high doses of the angiotensin-converting enzyme inhibitor, lisinopril, on morbidity and mortality in chronic heart failure. ATLAS Study Group. Circulation 1999;100:2312–8. https://doi.org/10.1161/01.CIR.100.23.2312; PMID: 10587334. 40. Jhund PS, Fu M, Bayram E, et al. Efficacy and safety of LCZ696 (sacubitril-valsartan) according to age: insights from PARADIGM-HF. Eur Heart J 2015;36:2576–84. https://doi. org/10.1093/eurheartj/ehv330; PMID: 26231885.

Clinical Practice

The Limitations of Symptom-based Heart Failure Management Lampros Papadimitriou, Charles K Moore, Javed Butler and Robert C Long University of Mississippi Medical Center, Jackson, MS, US

Abstract Heart failure (HF) has emerged as a global epidemic and it affects about 6 million adults in the US. HF medical treatment, as recommended in guidelines, significantly improves survival and quality of life; however, the mortality burden of HF remains high. For decades, treatment has been guided, mainly by symptoms, leading to undertreatment in a range of settings. Current evidence emphasises the unfavourable outcomes of HF even in early stages or in patients who achieve reverse remodeling and remission or recovery under optimised treatment. This should stimulate efforts towards a more objective, rigorous management, covering the entire spectrum of mild, moderate and severe HF.

Keywords Heart failure, symptoms, New York Heart Association, functional classification, undertreatment, guideline-directed medical therapy Disclosure: LP and RCL have no conflicts of interest to declare. CKM has received speaking honoraria from Novartis, JB has received research support from the National Institutes of Health and the EU and is a consultant to Amgen, Astra Zeneca, Bayer, Boehringer Ingelheim, CardioCell, Gilead Sciences, Merck, Novartis, Relypsa and Z Pharma. Received: 20 January 2019 Accepted: 11 April 2019 Citation: Cardiac Failure Review 2019;5(2):74–7. DOI: https://doi.org/10.15420/cfr.2019.3.2 Correspondence: Lampros Papadimitriou, Department of Medicine, University of Mississippi Medical Center, 2500 N State St, CV 201, Jackson, 39216, MS, US. E: lpapadimitriou@umc.edu Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

Heart failure (HF) is a global epidemic which affects about 6 million adults in the US. It is projected that by 2030 the total cost of HF will reach US$70 billion. Despite the development of novel drugs and devices, the mortality burden of HF remains high, with one in three patients dying within 1 year of hospitalisation for HF and 40–50% within 5 years of diagnosis.1 Patients with HF are divided into functional class based on the New York Heart Association (NYHA) classification. NYHA class I–IV refers to the severity of symptoms, with class I patients being asymptomatic with ordinary activity and class II and III patients being symptomatic with ordinary or less than ordinary activity, respectively. HF subjects who develop symptoms at rest or with physical activity can be classified as class IV functional status. This symptomatic classification has been a major entry criterion for the clinical trials that support current HF treatment guidelines.

Outcomes of HF Patients with Reduced Ejection Fraction Based on Functional Classification Even patients with asymptomatic early stages of HF, without symptoms, have evidence of ongoing adaptive and maladaptive pathways.2 Accordingly, patients with NYHA class I and II still have a relatively high morbidity and mortality burden. In a subanalysis of the Digitalis Investigational Group trial, when 1,863 subjects with NYHA I and II were matched to the same number of subjects with NYHA III and IV, the mortality rates were 34% versus 42%, and all-cause hospitalisations were 66% versus 71%, respectively.3 This shows that patients with a worse functional status have a higher mortality burden and this is behind the reasoning for symptom-driven therapy. However, it also

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reveals the significant poor outcomes for people who are supposedly less ill, which implies the need for an equally intensively treatment for all patients with HF, irrespective of symptoms, since most of the approved medications have been proven to reduce mortality (and/or morbidity) for the entire range of HF functional status. It is known that patients with HF, irrespective of ejection fraction and symptomatology, all have increased mortality rates. The most thorough studies investigating the actual cause of death in HF involved ICD or cardiac resynchronisation therapy (CRT). In one study from New Zealand involving almost 400 patients with HF with reduced ejection fraction (HFrEF), the 5-year all-cause mortality rate was 6%, while the relevant sudden arrhythmic death rate only 0.3%.4 In a more inclusive population of HF with reduced, preserved or recovered ejection, with or without implantable devices, and a mean follow-up of 4.5 years, 40% of the population (1,057 patients in the total population) died with 13.9%, 29.6% and 34.4% of the deaths deemed to be due to sudden cardiac death (SCD), worsening of HF or non-cardiovascular causes, respectively.5 In the largest trial to date in HFrEF, the Prospective Comparison of Angiotensin Receptor-Neprilysin inhibitor with Angiotensin Converting Enzyme Inhibitor to Determine Impact on Global Mortality and Morbidity in Heart Failure study (PARADIGM-HF; n=8442), 81% of deaths had a cardiovascular (CV) aetiology of which 45% were SCD and 26% due to HF.6 SCD comprises a greater proportion of the CV deaths in patients with milder HF symptoms. Clinical trial data have generally demonstrated that neurohumoral antagonism, which is a guidelinedirected medical therapy (GDMT) for HF, is able to reduce both the SCD rate and deaths due to the progression of HF.

The Limitations of Symptom-based Heart Failure Management Reliability of Classification One of the first limitations to a symptom-driven treatment strategy is the lack of accuracy and reproducibility of symptom classification which is currently based on a doctor’s consultation. When two cardiologists were asked to characterise the NYHA class of patients with mild to moderate symptoms, there was a low concordance of only 54–56%.7,8 Others have suggested that we should use selfreported NYHA classification, allowing the patient to determine their classification, but a study reported a poor correlation compared with classifications from physicians.9 Implementation of more objective measures of activity tolerance, such as the 6-minute walk test (6MWT), or cardiopulmonary exercise test – which is currently the gold standard – could address this issue but can be difficult to obtain routinely. A large meta-analysis has demonstrated a large heterogeneity between 6MWT distance and NYHA class. It also showed that the NYHA classification system was better able to distinguish functional capacity between class III and IV than between I and II.10 In another study with 145 subjects, only a 42% agreement was found between the NYHA classification and the more advanced and accurate VO2 max levels in cardiopulmonary exercise testing, while in a retrospective analysis from the Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness (ESCAPE) trial, no clear association was found.11,12 Taking a patient’s medical history in a more standardised fashion or using a specific questionnaire might help improve accuracy and reliability, but it cannot be ignored that the perception of symptoms is influenced by multiple factors that are not necessarily related to HF. Therefore, newer technology in the form of novel sensors and activity monitors, which provide real-time continuous activity information, might be a better measure, but they need to be validated in well-designed clinical trials.

Guideline Recommendations The latest American College of Cardiology/American Heart Association HF guidelines suggest that angiotensin converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARBs), beta-blockers, ICDs and cardiac resynchronisation therapy (CRT) play a substantial role in the management of people with HF with structural heart disease with prior or current symptoms; stage C as defined by the inclusion criteria of the trials that established their efficacy.13 It should be noted that there is scant evidence regarding the use of beta-blockers and ARBs in patients with NYHA class I HF. In the African-American Heart Failure Trial (A-HeFT) the combination of isosorbide dinitrate and hydralazine was only tested in patients with NYHA class III/IV, showing a significant reduction in the composite endpoint of all-cause mortality or first HF hospitalisation.14 Mineralocorticoid receptor antagonists (MRAs) are indicated for NYHA class II-IV, and angiotensin receptor/neprilysin inhibitors (ARNIs) for only classes II to III, despite the evidence showing beneficial pathophysiological effects of the former in NYHA class I patients and a mortality benefit better than any other evidence-based therapy available today for the latter (Table 1).15,16 In the current era of complicated healthcare logistics, and while awaiting the results on efficacy and safety of sacubitril/valsartan from the Entresto™ (LCZ696) In Advanced Heart Failure (LIFE Study), more studies into cost-effectiveness of these treatments in populations with certain characteristics should be initiated to justify the use of this or any other expensive therapeutic strategy.

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Table 1: Approved Treatments Based on NYHA Classes and Relevant Clinical Trials, According to the Latest Heart Failure Guidelines NYHA Class

Main Clinical Trials

I–IV

CONSENSUS29 SOLVD30

ARBs

I–IV

Val-HeFT31 CHARM-Alternative32 VALIANT33 (Class I only) RESOLVD34 STRETCH35

Beta-blockers

I–IV

CAPRICORN36 (Class I only) COMET37 MERIT-HF38

ARNI

II–III

PARADIGM-HF16

MRAs

II–IV

RALES39 EMPHASIS-H40 EPHESUS41

Hydralazine nitrates

III–IV

A-HeFT14

Ivabradine

II–III

SHIFT42 BEAUTIFUL43

I–IV

MADIT44 MADIT II45 SCD-HeFT46 MUSTT47 DINAMIT48

I–IV

CARE-HF49 COMPANION50 MIRACLE51 MADIT-CRT52 REVERSE53

ACEI

ICD

CRT

ACC = American College of Cardiology; ACEI = angiotensin-converting enzyme inhibitors; AHA = American Heart Association; ARBs = angiotensin receptor blockers; ARNI = angiotensin receptor/neprilysin inhibitors; CRT = cardiac resynchronisation therapy; HFSA = Heart Failure Society of America; MRA = mineralocorticoid receptor antagonist; NYHA = New York Heart Association.

Undertreatment of Heart Failure Beyond the fallibility of the symptomatic assessment of HF, it is clear that symptomatic HF patients are undertreated. Providers may falsely believe that patients with milder symptoms have low morbidity and mortality and that patients with advanced disease may be ‘beyond help’.17 Recent data from the Change the Management of Patients with Heart Failure (CHAMP-HF) trial reveal the extent of undertreatment of HF. In real life conditions, only 1% of patients were receiving all GDMT at target doses, while 27%, 33% and 67% were not prescribed with ACEI/ARB/ARNI, beta-blocker or MRA respectively.18 It is known that the underuse of indicated medication classes, as well as the lack of uptitration of these agents, leads to worse outcomes.19,20 GDMT and advanced therapies have proven beneficial effects on a cellular and myocardial level, even in subjects with advanced HF.21,22 However, since rejuvenative therapies, such as stem cells, have failed to offer sustained long-term benefits, the current therapeutic options are able to modify the underlying pathophysiology only in the absence of scar and fibrosis. Some people with dysfunctional and viable myocardium amenable to reverse remodelling. A small study of people with ischaemic HF showed that 19% and 60% of patients with NYHA I or II, respectively, had dysfunctional but viable myocardium, based on cardiac MRI with

Clinical Practice Figure 1: Natural Course of Stage C Heart Failure

Remission

• Progression of disease • New insults • Undertreatment • No treatment

• Proper treatment • Lack of insults

NYHA I

III

Death

Recovery

gadolinium imaging.23 Proper medical management and control of risk factors that alter contractility, preload and/or afterload, could potentially delay progression or even cause regression of the disease and lead to remission or recovery (Figure 1). Based on the findings of CHAMP-HF, NYHA class IV was associated with less than optimal GDMT, potentially due to the belief of physicians that treatment was futile, along with higher levels of medication intolerance. However, all approved HF medications, except for ARNI, have reduced morbidity and mortality in this HF patient population. Additionally, some of these patients are candidates for mechanical circulatory support (MCS) devices to further improve the quality and quantity of life. A minority of this MCS population may achieve remission of their HF, allowing later explantation of the device.24 There are two unanswered questions regarding this strategy: how to recognise viable and dysfunctional myocardium, which has been challenging even when using cardiac MRI, considered to be the most sensitive and reliable method; and how to differentiate the myocardium from being in real recovery or temporary remission. There is a need for further research into these issues which could be assisted with the use of novel emerging biomarkers. Modern HF therapeutic strategies prolong survival by inducing reverse remodelling of the ventricle. It has been uncertain whether GDMT should be continued in patients with significant improvement in left ventricular ejection fraction. In these patients, it could be argued that we would be able to discontinue most of their HF mediations, or even treat them based on their minimal symptoms. Other mostly

enjamin EJ, Blaha MJ, Chiuve SE, et al. Heart disease and B stroke statistics 2017 update: a report from the American Heart Association. Circulation 2017;135:e146–e603. https://doi. org/10.1161/CIR.0000000000000485; PMID: 28122885. Karabulut A, Kaplan A, Aslan C, et al. The association between NT-proBNP levels, functional capacity and stage in patients with heart failure. Acta Cardiol 2005;60:631–8. https://doi. org/10.2143/AC.60.6.2004936; PMID: 16385925. Ahmed A. A propensity matched study of New York Heart Association class and natural history end points in heart failure. Am J Cardiol 2007;99:549–53. https://doi.org/10.1016/j. amjcard.2006.08.065; PMID: 17293201. Looi KL, Sidhu K, Cooper L, et al. Long-term outcomes of

retrospective studies suggested medical therapy be continued in this population, with the exception of people with peripartum cardiomyopathy.25,26 However, the recently published TRED-HF provides the first evidence from a randomised clinical trial, suggesting that even in the absence of symptoms in this population, the residual activity of pathophysiological mechanisms require the continuation of GDMT to prevent relapse.27 HF is a chronic disease with a similar, if not worse, prognosis than other serious and life-threatening conditions, such as cancer or chronic kidney disease. Patients with HF are treated by multiple healthcare professionals, including cardiologists, hospital doctors and generalists. This is entirely different from care for the aforementioned diseases, which are treated only by specialists, regardless of the stage of the disease or the intensity of reported symptoms. This is of particular importance when inpatient management is involved. HF hospitalisation is a significant event in the physical course of HF, being an extremely negative prognostic factor. At the same time, it is a unique opportunity to initiate and establish an effective therapeutic plan. Only patients with more severe disease that does not respond to treatment are seen by cardiologists, which confirms the misconception that HF has a ‘benign’ disease course, especially among subjects whose symptoms quickly improve.28 Guideline treatment recommendations are based on the enrollment criteria of the relevant clinical research. Current trends in the design of HF clinical trials should expand the evidence base to include a broader range of HF patients. Inclusion criteria and endpoints using objective parameters, such as biomarkers and imaging indices, rely less on subjective symptoms. Enrolling older patients with significant kidney insufficiency, who in the past have been excluded, is a move in the right direction. Obtaining more objective measures is especially true in the trials being conducted for the treatment of HFpEF, for which we still do not have a satisfactory evidence-based treatment strategy. This could have a significant effect on daily practice, by making beneficial medications available to a larger number of patients, faster than in the past. The problem of undertreating HF persists despite the availability of multiple potent therapeutic strategies. However, for the first time after many years, the scientific community has intensified the discussion with supporting evidence. We are transitioning slowly to a new paradigm for treating HF aggressively at earlier stages and rigorously even at the more advanced stages, based on more objective parameters than symptoms alone. All patients should be treated intensively, irrespective of their functional status, to prevent disease progression and maximise the likelihood of HF remission and/or myocardial recovery. Ongoing and future clinical trials will provide the data necessary to advance this treatment strategy among healthcare professionals and patients as a significant culture change.

heart failure patients who received primary prevention implantable cardioverter-defibrillator: An observational study. J Arrhythmia 2018;34:46–54. https://doi.org/10.1002/joa3.12027; PMID: 29721113. Lupon J, Diez-Lopez C, de Antonio M, et al. Recovered heart failure with reduced ejection fraction and outcomes: a prospective study. Eur J Heart Fail 2017;19:1615–23. https://doi. org/10.1002/ejhf.824; PMID: 28387002. Desai AS, McMurray JJ, Packer M, et al. Effect of the angiotensin-receptor-neprilysin inhibitor LCZ696 compared with enalapril on mode of death in heart failure patients. Eur Heart J 2015;36:1990–7. https://doi.org/10.1093/eurheartj/ ehv186; PMID: 26022006.

aphael C, Briscoe C, Davies J, et al. Limitations of the New R York Heart Association functional classification system and self-reported walking distances in chronic heart failure. Heart 2007;93:476–82. https://doi.org/10.1136/hrt.2006.089656; PMID: 17005715. Goldman L, Hashimoto B, Cook EF, Loscalzo A. Comparative reproducibility and validity of systems for assessing cardiovascular functional class: advantages of a new specific activity scale. Circulation 1981;64:1227–34. https://doi. org/10.1161/01.CIR.64.6.1227; PMID: 7296795. Goode KM, Nabb S, Cleland JG, Clark AL. A comparison of patient and physician-rated New York Heart Association class in a community-based heart failure clinic. J Card Fail

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The Limitations of Symptom-based Heart Failure Management 2008;14:379–87. https://doi.org/10.1016/j.cardfail.2008.01.014; PMID: 18514929. 10. Y ap J, Lim F, Gao F, et al. Correlation of the New York Heart Association classification and the 6-minute walk distance: a systematic review. Clin Cardiol 2015;38:621–8. https://doi. org/10.1002/clc.22468; PMID: 26442458. 11. Rostagno C, Galanti G, Comeglio M, et al. Comparison of different methods of functional evaluation in patients with chronic heart failure. Eur J Heart Fail 2000;2:273–80. https://doi. org/10.1016/S1388-9842(00)00091-X; PMID: 10938488. 12. Guglin M, Patel T, Darbinyan N. Symptoms in heart failure correlate poorly with objective haemodynamic parameters. Int J Clin Pract 2012;66(12):1224–1229. https://doi.org/10.1111/ j.1742-1241.2012.03003.x; PMID: 23163503. 13. Yancy CW, Jessup M, Bozkurt B, et al. 2017 ACC/AHA/ HFSA focused update of the 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Failure Society of America. J Am Coll Cardiol 2017;70:776–803. https://doi. org/10.1016/j.jacc.2017.04.025; PMID: 28461007. 14. Taylor AL, Ziesche S, Yancy CW, et al. Early and sustained benefit on event-free survival and heart failure hospitalization from fixed-dose combination of isosorbide dinitrate/ hydralazine: consistency across subgroups in the AfricanAmerican Heart Failure Trial. Circulation 2007;115:1747–53. https://doi.org/10.1161/CIRCULATIONAHA.106.644013; PMID: 17372175. 15. Vizzardi E, D’Aloia A, Giubbini R et al. Effect of spironolactone on left ventricular ejection fraction and volumes in patients with class I or II heart failure. Am J Cardiol 2010;106:1292–6. https://doi.org/10.1016/j.amjcard.2010.06.052; PMID: 21029826. 16. McMurray JJ, Packer M, Desai AS, et al. Angiotensin-neprilysin inhibition versus enalapril in heart failure. N Engl J Med 2014;371:993–1004. https://doi.org/10.1056/NEJMoa1409077; PMID: 25176015. 17. Butler J, Gheorghiade M, Metra M. Moving away from symptoms-based heart failure treatment: misperceptions and real risks for patients with heart failure. Eur J Heart Fail 2016:350–2. https://doi.org/10.1002/ejhf.507; PMID: 26991352. 18. Greene SJ, Butler J, Albert NM, et al. Medical therapy for heart failure with reduced ejection fraction: The CHAMPHF Registry. J Am Coll Cardiol 2018;72:351–66. https://doi. org/10.1016/j.jacc.2018.04.070; PMID: 30025570. 19. Gislason GH, Rasmussen JN, Abildstrom SZ et al. Persistent use of evidence-based pharmacotherapy in heart failure is associated with improved outcomes. Circulation 2007;116:737– 44. https://doi.org/10.1161/CIRCULATIONAHA.106.669101; PMID: 17646585. 20. Ouwerkerk W, Voors AA, Anker SD, et al. Determinants and clinical outcome of uptitration of ACE-inhibitors and beta-blockers in patients with heart failure: a prospective European study. Eur Heart J 2017;38:1883–90. https://doi. org/10.1093/eurheartj/ehx026; PMID: 28329163. 21. Mann DL, Barger PM, Burkhoff D. Myocardial recovery and the failing heart: myth, magic, or molecular target? J Am Coll Cardiol 2012;60:2465–72. https://doi.org/10.1016/j.jacc.2012.06.062; PMID: 23158527. 22. Martens P, Beliën H, Dupont M, et al. The reverse remodeling response to sacubitril/valsartan therapy in heart failure with reduced ejection fraction. Cardiovasc Ther 2018;36:e12435. https://doi.org/10.1111/1755-5922.12435; PMID: 29771478. 23. Bourantas CV, Nikitin NP, Loh HP, et al. Prevalence of scarred and dysfunctional myocardium in patients with heart failure of ischaemic origin: A cardiovascular magnetic resonance study. J Cardiovasc Magn Reson 2012;13:53–17. https://doi. org/10.1186/1532-429X-13-53; PMID: 21936915. 24. Jaiswal A, Le Jemtel TH, Samson R, Mancini D. Sustained cardiac recovery hinges on timing and natural history of underlying condition. Am J Med Sci 2018;356:47–55. https://doi.

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org/10.1016/j.amjms.2018.02.008; PMID: 30049330. 25. A mos AM, Jaber WA, Russell SD. Improved outcomes in peripartum cardiomyopathy with contemporary. Am Heart J 2006;152:509–13. https://doi.org/10.1016/j.ahj.2006.02.008; PMID: 16923422. 26. Hopper I, Samuel R, Hayward C, et al. Can medications be safely withdrawn in patients with stable chronic heart failure? Systematic review and meta-analysis. J Card Fail 2014;20:522–32. https://doi.org/10.1016/j.cardfail.2014.04.013; PMID: 24747201. 27. Halliday BP, Wassall R, Lota AS, et al. Withdrawal of pharmacological treatment for heart failure in patients with recovered dilated cardiomyopathy (TRED-HF): an open-label, pilot, randomised trial. Lancet 2018;93:61–73. doi: 10.1016/ S0140-6736(18)32484-X; PMID: 30429050. 28. Uthamalingam S, Kandala J, Selvaraj V, et al. Outcomes of patients with acute decompensated heart failure managed by cardiologists versus noncardiologists. Am J Cardiol 2015;115:466–71. https://doi.org/10.1016/j. amjcard.2014.11.034; PMID: 25637324. 29. Swedberg K, Kjekshus J. Effects of enalapril on mortality in severe congestive heart failure. Results of the Cooperative North Scandinavian Enalapril Survival Study (CONSENSUS). N Engl J Med 1987;316:1429–35. https://doi.org/10.1056/ NEJM198706043162301; PMID: 2839019. 30. Yusuf S, Pitt B, Davis CE, et al. Effect of enalapril on survival in patients with reduced left ventricular ejection fractions and congestive heart failure. N Engl J Med 1991;325:293–302. https://doi.org/10.1056/NEJM199108013250501; PMID: 2057034. 31. Maggioni AP, Anand I, Gottlieb SO, et al. Effects of valsartan on morbidity and mortality in patients with heart failure not receiving angiotensin-converting enzyme inhibitors. J Am Coll Cardiol 2002;40:1414–21. https://doi.org/10.1016/S07351097(02)02304-5; PMID: 12392830. 32. Granger CB, McMurray JJ, Yusuf S, et al. Effects of candesartan in patients with chronic heart failure and reduced leftventricular systolic function intolerant to angiotensinconverting-enzyme inhibitors: the CHARM-Alternative trial. Lancet 2003;362:772–6. https://doi.org/10.1016/S01406736(03)14284-5; PMID: 13678870. 33. Pfeffer MA, McMurray JJ, Velazquez EJ et al. Valsartan, captopril, or both in myocardial infarction complicated by heart failure, left ventricular dysfunction, or both. N Engl J Med 2003;349:1893–906. https://doi.org/10.1056/NEJMoa032292; PMID: 14610160. 34. McKelvie RS, Yusuf S, Pericak D, et al. Comparison of candesartan, enalapril, and their combination in congestive heart failure: randomized evaluation of strategies for left ventricular dysfunction (RESOLVD) pilot study. The RESOLVD Pilot Study Investigators. Circulation 1999;100:1056–64. https:// doi.org/10.1161/01.CIR.100.10.1056; PMID: 10477530. 35. Riegger GA, Bouzo H, Petr P, et al. Improvement in exercise tolerance and symptoms of congestive heart failure during treatment with candesartan cilexetil. Circulation 1999;100:2224–30. https://doi.org/10.1161/01. CIR.100.22.2224; PMID: 10577995. 36. Dargie HJ. Effect of carvedilol on outcome after myocardial infarction in patients with left-ventricular dysfunction: the CAPRICORN randomised trial. Lancet 2001;357:1385–90. https://doi.org/10.1016/S0140-6736(00)04560-8; PMID: 11356434. 37. Poole-Wilson PA, Swedberg K, Cleland JG, et al. Comparison of carvedilol and metoprolol on clinical outcomes in patients with chronic heart failure in the Carvedilol Or Metoprolol European Trial (COMET): randomised controlled trial. Lancet 2003;362:7–13. https://doi.org/10.1016/S0140-6736(03)138007; PMID: 12853193. 38. MERIT HF Investigators. Effect of metoprolol CR/XL in chronic heart failure: Metoprolol CR/XL Randomised Intervention Trial in Congestive Heart Failure (MERIT-HF). Lancet 1999;353:2001–7.

https://doi.org/10.1016/S0140-6736(99)04440-2; PMID: 10376614. 39. P itt B, Zannad F, Remme WJ, et al. The effect of spironolactone on morbidity and mortality in patients with severe heart failure. N Engl J Med 1999;341:709–17. https://doi.org/10.1056/ NEJM199909023411001; PMId: 10471456. 40. Zannad F, McMurray JJ, Krum H, et al. Eplerenone in patients with systolic heart failure and mild symptoms. N Engl J Med 2011;364:11–21. https://doi.org/10.1056/NEJMoa1009492; PMID: 21073363. 41. Pitt B, Remme W, Zannad F, et al. Eplerenone, a selective aldosterone blocker, in patients with left ventricular dysfunction after myocardial infarction. N Engl J Med 2003;348:1309–21. https://doi.org/10.1056/NEJMoa030207; PMID: 12668699. 42. Swedberg K, Komajda M, Bohm M, et al. Ivabradine and outcomes in chronic heart failure (SHIFT): a randomised placebo-controlled study. Lancet 2010; 376:875–85. https://doi.org/10.1016/S0140-6736(10)61198-1; PMID: 20801500. 43. Fox K, Ford I, Steg PG, et al. Ivabradine for patients with stable coronary artery disease and left-ventricular systolic dysfunction (BEAUTIFUL): a randomised, double-blind, placebo-controlled trial. Lancet 2008;372:807–16. https://doi. org/10.1016/S0140-6736(08)61170-8; PMID: 18757088. 44. Moss AJ, Hall WJ, Cannom DS, et al. Improved survival with an implanted defibrillator in patients with coronary disease at high risk for ventricular arrhythmia. N Engl J Med 1996;335:1933-40. https://doi.org/10.1056/ NEJM199612263352601; PMID: 8960472. 45. Moss AJ, Zareba W, Hall WJ, et al. Prophylactic implantation of a defibrillator in patients with myocardial infarction and reduced ejection fraction. N Engl J Med 2002;346:877–83. https://doi.org/10.1056/NEJMoa013474; PMID: 11907286. 46. Bardy GH, Lee KL, Mark DB, et al. Amiodarone or an implantable cardioverter-defibrillator for congestive heart failure. N Engl J Med 2005;352:225–37. https://doi.org/10.1056/ NEJMoa043399; PMID: 15659722. 47. Buxton AE, Lee KL, Fisher JD, et al. A randomized study of the prevention of sudden death in patients with coronary artery disease. N Engl J Med 1999;341:1882–90. https://doi.org/10.1056/NEJM199912163412503; PMID: 10601507. 48. Hohnloser SH, Kuck KH, Dorian P, et al. Prophylactic use of an implantable cardioverter-defibrillator after acute myocardial infarction. N Engl J Med 2004;351:2481–8. https://doi.org/10.1056/NEJMoa041489; PMID: 15590950. 49. Cleland JG, Daubert JC, Erdmann E, et al. The effect of cardiac resynchronization on morbidity and mortality in heart failure. N Engl J Med 2005;352:1539–49. https://doi.org/10.1056/ NEJMoa050496; PMID: 15753115. 50. Bristow MR, Saxon LA, Boehmer J, et al. Cardiacresynchronization therapy with or without an implantable defibrillator in advanced chronic heart failure. N Engl J Med 2004;350:2140–50. https://doi.org/10.1056/NEJMoa032423; PMID: 15152059. 51. Abraham WT, Fisher WG, Smith AL, et al. Cardiac resynchronization in chronic heart failure. N Engl J Med 2002;346:1845–53. https://doi.org/10.1056/NEJMoa013168; PMID: 12063368. 52. Moss AJ, Hall WJ, Cannom DS, et al. Cardiac-resynchronization therapy for the prevention of heart-failure events. N Engl J Med 2009;361:1329–38. https://doi.org/10.1056/NEJMoa0906431; PMID: 19723701. 53. Linde C, Abraham WT, Gold MR, et al. Randomized trial of cardiac resynchronization in mildly symptomatic heart failure patients and in asymptomatic patients with left ventricular dysfunction and previous heart failure symptoms. J Am Coll Cardiol 2008;52:1834–43. https://doi.org/10.1016/j. jacc.2008.08.027; PMID: 19038680.

Clinical Practice

Treating Patients Following Hospitalisation for Acute Decompensated Heart Failure: An Insight into Reducing Early Rehospitalisations Attilio Iacovoni, 1 Emilia D’Elia, 1 Mauro Gori, 1 Fabrizio Oliva, 2 Ferdinando Luca Lorini 3 and Michele Senni 1 1. Cardiovascular Department, ASST Papa Giovanni XXIII, Bergamo, Italy; 2. Cardiovascular Department, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy; 3. Emergency and Intensive Care Department, ASST Papa Giovanni XXIII, Bergamo, Italy

Abstract Heart failure (HF) is a pandemic syndrome characterised by raised morbidity and mortality. An acute HF event requiring hospitalisation is associated with a poor prognosis, in both the short and the long term. Moreover, early rehospitalisation after discharge negatively affects HF management and survival rates. Cardiovascular and non-cardiovascular conditions combine to increase rates of HF hospital readmission at 30 days. A tailored approach for HF pharmacotherapy while the patient is in hospital and immediately after discharge could be useful in reducing early adverse events that cause rehospitalisation and, consequently, prevent worsening HF and readmission during the vulnerable phase after discharge.

Keywords Acute heart failure, drug management, rehospitalisation, worsening heart failure Disclosure: The authors have no conflicts of interest to declare Received: 30 December 2018 Accepted: 19 April 2019 Citation: Cardiac Failure Review 2019;5(2):78–82. DOI: https://doi.org/10.15420/cfr.2018.46.2 Correspondence: Michele Senni, Dipartimento Cardiovascolare, Azienda Ospedaliera Papa Giovanni XXIII, Bergamo, Italy. E: msenni@asst-pg23.it Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

Heart failure (HF) is a pandemic, chronic degenerative disease estimated to affect 38 million people worldwide, a number expected to increase with the ageing of the population.1 As a syndrome, it is associated with high mortality and morbidity, and consistently requires increasing resources. HF is the most frequent cause of hospitalisation in patients aged over 65 years, and hospitalised patients have a much worse prognosis than those who are stable at home.2–5 Although therapies can significantly improve symptoms and clinical condition, mortality and rehospitalisation rates remain as high as 10% within 30 days in Europe and are almost 25% in Medicare beneficiaries in the US. Such readmissions are often considered to be a marker of poor healthcare and have become a benchmark for reimbursement and an indicator of hospital quality.6,7 In spite of investments in this field, reductions in the major adverse events have not been achieved, and the 30 days after discharge is a critical, delicate period.8,9

an acute event, only 17–35% of rehospitalisations are due to HF exacerbation; most admissions of people with HF are related to noncardiovascular (CV) causes, such as renal disorders, arrhythmias, sepsis and pulmonary disease.11 Due to the heterogeneity of readmission triggers, a focus on prevention strategies to reduce CV and non-CV causes of 30-day rehospitalisation are needed, and measures to predict readmission should be highlighted and promoted among both consultant physicians and community care providers. This article provides an overview of HF therapy in the acute phase after hospitalisation. Table 1 shows some of most important clinical trials on HF drugs effect after discharge.

Medical Therapy Following Hospitalisation for Acute Decompensated Heart Failure

Heart Failure Rehospitalisation: An Unsolved Problem

International guidelines of the American College of Cardiology and the European Society of Cardiology (ESC) underline the importance of starting and continuing with HF medications, such as angiotensinconverting enzyme inhibitors (ACEIs), angiotensin-receptor blockers (ARBs), beta-blockers (BBs) and mineralocorticoid receptor antagonists (MRAs), during an episode of acute HF and after discharge.12,13 These medications are considered the mainstay of chronic HF therapy, and their use is recommended as class I indication in these patients.

Recent observations from clinical practice have shown length of stay and in-hospital and 30-day mortality for patients with HF have reduced, but the readmission rate at 30 days after hospitalisation for HF is higher.10 While congestion is the primary cause of HF relapse, and subclinical congestion develops days or even weeks before

Despite strong evidence for the benefits of these drugs, their use by clinicians is not always routine, especially after an episode of acute decompensated HF. Data from the Get With the Guidelines-Heart Failure (GWTG-HF) registry showed that, of patients already receiving

In this article, we will consider treating patients after hospitalisation for acute HF, focusing on the vulnerable period just after discharge from hospital and on the therapeutic interventions found to reduce readmissions.

Access at: www.CFRjournal.com

Treatment Following Hospitalisation for Acute Decompensated Heart Failure Table 1: Trials on Drug Management After Discharge Therapy

Study

Year

No. patients

Type of study

ACE-ARBs

OPTIMIZE-HF21

2007

5,791

Registry

JCAHO-HF

2008

2,958

Retrospective analysis of healthcare database

GWTG-HF14

2017

16,052

Retrospective analysis of healthcare database

OPTIME-CHF20

2003

212

Post-hoc analysis of trial

IMPACT-HF

2004

363

Open-label randomised trial

OPTIMIZE-HF21

2007

5,791

Registry

ESCAPE22

2006

432

Post-hoc analysis of trial

COMET

2007

752

Post-hoc analysis of trial

MRA

COACH29

2014

297

Post-hoc analysis of trial

Ivabradine

ETHIC-AHF37

2016

Randomised study

ARNI

PIONEER-HF

2018

882

Randomised study

In press

~1,000

Open-label trial

41,42

TRANSITION43,44

ACE = angiotensin-converting enzyme; ARB = angiotensin receptor blocker; ARNI = angiotensin receptor–neprylisin inhibitor; BB = beta-blocker; MRA = mineralocorticoid receptor antagonist.

medications for chronic HF at the time of hospitalisation, 88.5% of those taking ACEIs, 91.6% of those on BBs and 71.9 % of those taking MRAs continued to take them from admission through discharge.14 MRAs were the first medications to be discontinued during hospitalisation (in 28% of patients), followed by ACEIs (13%) and BBs (2.6%). A multivariate analysis of predictors of evidence-based medication use at discharge showed that the most significant variables were younger age and taking medications on admission.14 Furthermore, an analysis of the prospective, multicentre, observational ESC-HF Long-Term Registry in Europe showed a significant increase in the rate of prescription of all HF medications at discharge compared to the period before admission.15

Angiotensin-converting Enzyme Inhibitor or Angiotensin Receptor Blocker Previous studies have shown conflicting results regarding continuation of ACEIs/ARBs during an episode of acute HF. Fonarow et al. analysed data from the Organized Program To Initiate Lifesaving Treatment In Hospitalized Patients With Heart Failure (OPTIMIZE-HF) registry and found that in patients with HF with reduced ejection fraction (HFrEF) the prescription of ACEI/ARBs at discharge was associated with a significant lowering of risk only for the composite endpoint of death and rehospitalisation at 60–90 days, and no difference in overall mortality was observed.16 On the contrary, the analysis of the Joint Commission on Accreditation of Healthcare Organizations Heart Failure (JCAHO-HF) study showed that ACEI/ARB therapy was associated with improved 1-year survival after HF hospitalisation.17 In addition, a recent sub-analysis of the GWTG-HF registry showed that 30-day mortality was 3.5% for patients continuing ACEIs/ARBs, while it was 8.8% for patients discontinuing (p<0.001). Moreover, the 30-day readmission rate was lowest among patients still on therapy at discharge. The same benefits persisted at 1 year (mortality 28.2% for patients continuing on ACEIs/ARBs, compared to 41.6% for patients off therapy; p<0001).18

Beta-blockers There is only one randomised trial that investigated the effect of predischarge carvedilol initiation in patients stabilised after an episode of acute HF, the Initiation Management Predischarge: Process for

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Assessment of Carvedilol Therapy in Heart Failure (IMPACT-HF) study. The results showed pre-discharge initiation of carvedilol is safe, well tolerated and has a good short-term compliance.19 A retrospective analysis of the Outcomes of the Prospective Trial of Intravenous Milrinone for Exacerbations of Chronic Heart Failure (OPTIME-CHF) study reported that, of 212 people treated with BB at the time of the admission for decompensated HF, the 47 patients who permanently stopped BB had a worse outcome.20 Results of the OPTIMIZE-HF study registry showed that patients discharged with BBs had a lower risk of death from any cause at 60–90 days than discharged without it (HR 0.46; p<0.006).21 Similarly, in a post-hoc analysis of the Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization (ESCAPE) trial, patients discharged on BB therapy had a significantly lower 180-day death or rehospitalisation rates. This association remained significant when data were adjusted for propensity to use BB at discharge and covariates associated with death or rehospitalisation (OR 0.51; 95% CI [0.27–0.97]; p<0.01).22 Moreover, in a post-hoc analysis of the Carvedilol or Metoprolol European Trial (COMET), patients were subdivided into three groups: those who received the same dose before and after HF hospitalisation; those who had a dose reduction of at least one level at the visit following discharge from hospital; and those who were taken off the study drug. The results of the analysis found that 1- and 2-year cumulative mortality rates were significantly higher in patients withdrawn from the study medication or those with a reduced dosage than to those maintained on the same dose, independent of the type of BB used. The result remained significant in a multivariable model (HR 1.30; 95% CI [1.02–1.66]; p=0.0318).23

Mineralocorticoid Receptor Antagonist Few studies have analysed the effect of MRAs in this clinical scenario. In an observational analysis of 43,625 patients admitted with HF and discharged home, Albert et al. found that only 33% of those who were eligible to be treated with an MRA actually received one.24 Curtis et al. investigated data from the GWTG-HF study linked with Medicare claims to examine adherence and persistence in the use of MRAs among Medicare beneficiaries for whom this therapy had been indicated.25 They observed that only one in five eligible patients was prescribed an MRA at discharge; moreover, eligible patients without a prescription at discharge seldom started therapy as outpatients. All these analyses showed the use of MRAs is extremely low in patients with acute HF, although this medication is strongly recommended, especially in those

Clinical Practice with advanced HF. Moreover, data on continuation of MRA in Medicare beneficiaries hospitalised for acute HF showed it improved the 60-day survival rate.26 In the Japanese Cardiac Registry of Heart Failure in Cardiology (JCARE-CARD) study, Hamaguchi et al. investigated the effect of spironolactone on survival and hospitalisation among hospitalised patients with systolic HF.27 They noticed that use of spironolactone was associated with a significant reduction of all-cause death (adjusted HR 0.612; p=0.02) and cardiac death (adjusted HR 0.524; p=0.013), while no effect was found for hospitalisation.

to BBs alone in a randomised trial including 71 patients with acute HFrEF and sinus rhythm with HR >70 BPM. HR at 1 and 4 months after discharge was significantly lower in the beta-blockers plus ivabradine group, and there were significant improvements in LVEF and natriuretic peptides, but no differences in clinical events at 4 months.37 Therefore, it has been suggested that ivabradine could be given in addition to BB therapy to improve HR control in patients with acute HF.38 However, evidence is still sparse, and the safety and efficacy of ivabradine needs to be confirmed by other clinical trials.

In the Comparative Effectiveness of Therapies for Heart Failure (COMPARE-HF) registry, Hernandez et al. analysed the clinical effectiveness of newly initiated aldosterone antagonist therapy among older patients hospitalised with HFrEF. The result of the study showed that the use of aldosterone was not associated with reduced risk of mortality at 3 years after discharge (p=0.32), even though readmissions for HF were lower among treated patients at 3 years (p=0.02).28 The use of aldosterone was associated with higher risk of hospitalisation at 30 days and 1 year due to hyperkalemia. In addition, results from the Co-ordinating Study Evaluating Outcome of Advising and Counselling in Heart Failure (COACH) biomarker study showed that patients who remained on spironolactone treatment had a lower 30-day mortality.29

Angiotensin Receptor–Neprilysin Inhibitors in the Transition Phase

Diuretics Diuretics are considered only a symptomatic therapy in patients with chronic HF, since their effects are mostly aimed at reducing congestion and they have no impact on survival and on rehospitalisation. One small, randomised, open-label study examined the differences on clinical outcomes between furosemide and torsemide in patients admitted to the hospital for an episode of acute HF.30 The results suggested that patients treated with torsemide were less likely to be readmitted for HF and for all CV causes versus those taking furosemide. An analysis from the Efficacy of Vasopressin Antagonism in Heart Failure: Outcome Study with Tolvaptan (EVEREST) trial showed that patients responsive to diuretic therapy and those with haemoconcentration were both at lower risk for early post-discharge adverse events.31 Moreover, an analysis from the Diuretic Strategies in Patients with Acute Decompensated Heart Failure (DOSE-AHF) study reinforced these results, showing improved clinical outcomes at 60 days for patients with adequate loss of weight, fluid removal and natriuretic peptide reduction after treatment during HF hospitalisation.32

Digoxin Digoxin has been extensively evaluated by the Digitalis Investigation Group (DIG) trial, which shows it reduces all-cause and HF hospitalisations.33 However, its role and effect in acute HF was investigated only in a registry based on the Alabama Heart Failure Project, in which 8,049 patients hospitalised with a primary diagnosis of HF were observed for 30 days after discharge. In this study, digoxin seemed effective in reducing 30-day, all-cause readmission only in patients with a left ventricular ejection fraction (LVEF) <45% (HR 0.63; 95% CI [0.47–0.83].34

Ivabradine In a small cohort of patients admitted for acute HFrEF with a heart rate (HR) >70 BPM and no need for inotropic treatment, ivabradine significantly reduced HR and was associated with improved NYHA class and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels.35 Similar results were obtained in a retrospective analysis on 29 patients.36 In addition, the effects of ivabradine and BBs were compared

Angiotensin receptor–neprilysin inibithors (ARNIs) are a novel HF treatment. This innovative therapy has been investigated in a multicentre prospective randomised study, the Prospective comparison of ARNI with ACEI to Determine Impact on Global Mortality and morbidity in Heart Failure (PARADIGM-HF) trial, which compared sacubitril/valsartan with enalapril in patients with chronic HF, reduced ejection fracture (EF; <40%), and a New York Heart Association (NYHA) II–IV classification.39 The primary results of this study showed a significant decrease in both cardiovascular mortality and HF hospitalisation with ARNIs with respect to enalapril. The study was interrupted prematurely at 27 months of follow-up because the primary endpoint occurred in 914 patients (21.8%) in the sacubitril/ valsartan group versus 1,117 patients (26.5%) in the enalapril group, reflecting a 20% reduction in the composite of CV death or HF hospitalisation in the former. In addition, sacubitril/valsartan reduced both the time to first hospitalisation for HF, and the cumulative burden of HF hospitalisation. Based on these excellent data, the use of ARNIs has gained a class I indication in patients with chronic HFrEF able to tolerate ACEI/ARB therapy in recent ESC guidelines.13 Desai et al. investigated the effect of ARNIs on the rates of all-cause 30-day readmission after an HF hospitalisation.40 They analysed all patients who survived after the first HF admission. A total of 1,450 patients were investigated, including 675 (16.1%) assigned to sacubitril/valsartan and 775 (18.4%) assigned to enalapril. The results showed that the use of ARNIs had a significant effect on reducing the rate of readmission for any cause or for HF at 30 and 60 days. The safety and efficacy of sacubitril/valsartan compared to enalapril among patients hospitalised for acute HF were investigated in a randomised study, Comparison of sacubitril/ valsartaN versus Enalapril on Effect on NT-pRoBNP in patients stabilised from an acute Heart Failure episode (PIONEER-HF). The results showed no differences in renal dysfunction, hyperkalemia, symptomatic hypotension and angioedema between the two treatment arms. Noteworthy, the reduction in the NT-proBNP concentration was significantly greater in the sacubitril/valsartan group than in the enalapril group.41 In summary, sacubitril/valsartan was recognised to be more effective than enalapril among stabilised patients hospitalised for acute HF in reducing natriuretic peptides and the composite of rehospitalisation for HF or CV death.42 Based on these promising results, the Pre-discharge and posTdischarge tReatment initiation with sacubitril/valsartan in heArt failure patieNtS with reduced ejectIon fracTion hospItalised for an acute decOmpensation eveNt (TRANSITION) study aimed to investigate the effects and tolerability of ARNIs in patients stabilised after hospitalisation for acute HF, regardless of whether they received it while in hospital or after discharge.43 TRANSITION involved 1,002 randomised patients, of

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Treatment Following Hospitalisation for Acute Decompensated Heart Failure whom 287 (29%) had new-onset HF with reduced EF, and 243 (24%) were ACEI/ARB naive. Pre-admission use of BBs and MRAs was lower than in PARADIGM-HF; moreover, TRANSITION patients were older, more likely to be female and have worse renal function, and a higher proportion of them had AF and diabetes. At 10 weeks after randomisation, 45% of patients in the pre-discharge arm and 50.4% of patients in the post-discharge arm achieved the target dose of 200 mg sacubitril/ valsartan twice daily (relative risk ratio [RRR] 0.893; 95% CI [0.783–1.019]; p=0.092). More than 85% of patients achieved and maintained any dose of sacubitril/valsartan for at least 2 weeks leading to week 10 after randomisation in both groups (86.4% of those who started it before discharge initiation and 88.8% of those who began it after discharge; RRR 0.973; 95% CI [0.929–1.020]; p=0.262). Mortality rates were low in both treatment arms (p=0.258) and none of the deaths was attributed to the study treatment. Therefore, the TRANSITION preliminary results demonstrated the safety and tolerability of starting sacubitril/valsartan in stabilised HFrEF patients shortly after an acute HF event.44

Medical Therapy Following Hospitalisation for Acute Decompensated Heart Failure in Advanced Heart Failure Continuous and intermittent infusion of intravenous inotropes have been used in different clinical scenarios of advanced HF and end-stage HF (eHF).45,46 Different inotropes have been investigated, but most of these trials were based at one centre, so enrolled a limited number of patients.47 Moreover, the majority of these studies have several statistical limitations, such as being a retrospective analysis or not using a randomised, placebo-control methodology. Levosimendan is a calcium sensitiser and potassium channel opener with inotrope and vasodilatory effects, and it is the most promising inotrope tested in advanced HF trials.48 Among these, only three studies have investigated its role in reducing acute HF hospitalisations: the Intermittent Intravenous Levosimendan in Ambulatory Advanced Chronic Heart Failure Patients (LION–HEART) study, the Long-Term Intermittent Administration of Levosimendan in Patients With Advanced Heart Failure (LAICA) study and the Relevant-HF REpetitive LEVosimendan in AdvaNced refracTory Heart Failure (RELEVANT-HF) registry.49–51 In the LION-HEART study, 69 patients were randomised to either levosimendan (n=48) or placebo (n=21) administered in an ambulatory setting. The primary endpoint was change in NT-proBNP from baseline, and the secondary endpoint was a reduction in the combined incidence of all-cause mortality and hospitalisation. Both were significant in favour of levosimendan, in particular hospitalisations for HF, at 22.9% versus 66.7% in the placebo group (HR 0.25; 95% CI [0.11–0.55]; p=0.001). In the LAICA study, 97 patients (levosimendan, n=70; placebo, n=27) were randomly assigned to receive infusions once every 30 days in addition to optimal standard HF therapy.50 The primary endpoint was the incidence of admission for advanced HF or HF worsening. No significant differences were observed, but there were fewer admissions for advanced HF and lower mortality rates in the levosimendan group (6.6% versus 22.2% for placebo; p=0.0439). In the RELEVANT-HF registry, 185 ambulatory patients were treated in a hospital or outpatient setting with specifically tailored intermittent levosimendan therapy.51 The study showed a significant reduction in the number and duration of HF-related hospitalisations and in total days in hospital.

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Based on the results of these studies, repetitive infusion of levosimendan in advanced HF seems promising and an effective way to reduce HF hospitalisations.52

Unsolved Problem: Drug Underutilisation After Discharge Obstacles limiting the correct, early prescription of an optimised medical therapy for acute HF at discharge are mainly related to drug adverse effects in patients who are still fragile. The introduction and maintenance of an optimal medical treatment may be challenging, as the time available to test the drugs may be short, and the patient may have several comorbidities preventing a correct dosage of the drug from being used. Potential factors that could lead a clinician to underutilise or discontinue HF drugs include symptomatic hypotension, worsening renal function, angioedema, electrolyte disturbance and a period of tissue hypoperfusion. The ESC guidelines recommend patients admitted to hospital for acute HF should receive evidence-based, oral medication for at least 24 hours before discharge to reduce the possibility of drug discontinuation.13 Nonetheless, randomised trials substantiating a benefit for starting the patient on medication before versus after discharge are lacking. Data from the GREAT registry, including 19,980 patients with acute HF with both reduced and preserved ejection fraction HFpEF, showed that BBs and ACEIs/ARBs at discharge led to a reduction in 90-day mortality, and had a better impact on overall long-term survival.53 Interestingly, only in patients with HFpEF was a positive association found between oral MRA at discharge and 90-day mortality. It may be that the failure of MRA to show a beneficial effect in patients with HFrEF could be related to a higher rate discontinuation because of hyperkalemia, which is a common adverse effect, especially in elderly patients taking diuretics. As comorbidities are typical in patients with HFpEF, a tailored approach to treat both cardiac and non-cardiac comorbidities could help physicians in maintaining a good uptitration of HF drug, as treating these includes controlling blood pressure, monitoring heart rate and heart rhythm, lowering glycaemic and lipid profiles, and favouring a healthy lifestyle.

Multidisciplinary Disease Management Program After Discharge To ensure better drug adherence after HF hospitalisation, a multidisciplinary disease management programme should be established and encouraged on a large scale. The key elements of a multidisciplinary programme include hospital HF physicians, specialised HF nurses, a well-structured network between primary care and tertiary centres, and regional HF outpatient clinics. Usually, specialised HF nurses are responsible for programme coordination, which involves home visits, optimising treatment, early recognition of worsening HF and facilitating patient empowerment.54 Such programmes, consequently, improve patient wellbeing, reduce hospitalisations and increase overall survival rate.

Conclusion Rehospitalisation after an acute HF event is one of the main issues affecting patients’ short- and long-term prognosis. The first 30 days after discharge are a delicate period, where both cardiologists and community care providers should work together to reduce exacerbation of the disease. A proper use of HF drugs during hospitalisation and just after discharge should be promoted and emphasised by international guidelines to improve HF management and patient quality of life.

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PMID: 27100325. 37. H idalgo FJ, Anguita M, Castillo JC, et al. Effect of early treatment with ivabradine combined with beta-blockers versus beta-blockers alone in patients hospitalised with heart failure and reduced left ventricular ejection fraction (ETHIC-AHF): a randomised study. Int J Cardiol 2016;217:7–11. https://doi.org/10.1016/j.ijcard.2016.04.136; PMID: 27167103. 38. Oliva F, Sormani P, Contri R, et al. Heart rate as a prognostic marker and therapeutic target in acute and chronic heart failure. Int J Cardiol 2018;253:97–104. https://doi.org/10.1016/j. ijcard.2017.09.191; PMID: 29249470. 39. McMurray JJ, Packer M, Desai AS, et al. Angiotensin-neprilysin inhibition versus enalapril in heart failure. N Engl J Med 2014;371:993–1004. https://doi.org/10.1056/NEJMoa1409077; PMID: 25176015. 40. Desai AS, Claggett BL, Packer M et al; PARADIGM-HF Investigators. Influence of sacubitril/valsartan (LCZ696. on 30-day readmission after heart failure hospitalization. J Am Coll Cardiol 2016;68:241–8. https://doi.org/10.1016/j. jacc.2016.04.047; PMID:2 7417000. 41. Velazquez EJ, Morrow DA, DeVore AD, et al. Angiotensinneprilysin inhibition in acute decompensated heart failure. N Engl J Med 2018;380:539–48. https://doi.org/10.1056/ NEJMoa1812851; PMID: 30415601. 42. Morrow DA, Velasquez EJ, DeVore AD, et al. Clinical outcomes in patients with acute decompensated heart failure randomly assigned to sacubitril/valsartan or enalapril in the PIONEER-HF Trial. Circulation 2019. https://doi.org/10.1161/ CIRCULATIONAHA.118.039331; PMID: 30955360; epub ahead of press. 43. Pascual-Figal D, Wachter R, Senni M. Rationale and design of TRANSITION: a randomized trial of pre-discharge vs. post-discharge initiation of sacubitril/valsartan. ESC Heart Fail 2018;5:327–36. https://doi.org/10.1002/ehf2.12246; PMID: 29239515. 44. Wachter R, Senni M, Belohlavek, et al. Initiation of sacubitril/ valsartan in hospitalized patients with heart failure with reduced ejection fraction after hemodynamic stabilization: primary results of the TRANSITION study. Poster presented at ESC Congress 2018, Munich, 25–29 August 2018. Eur Heart J 2018;39(Suppl 1):ehy564.P886. https://doi.org/10.1093/ eurheartj/ehy564.P886. 45. Ginwalla M, Tofovic DS. Current status of inotropes in heart failure. Heart Fail Clin 2018;14:601–16. https://doi.org/10.1016/j. hfc.2018.06.010; PMID: 30266368. 46. Mortara A, Oliva F, Metra M, et al. Treatment with inotropes and related prognosis in acute heart failure: contemporary data from the Italian Network on Heart Failure (IN-HF) Outcome Registry. J Heart Lung Transplant 2014;33:1056–65. https://doi.org/10.1016/j.healun.2014.05.015; PMID: 25049067. 47. Francis GS, Bartos JA, Adatya S. Inotropes. J Am Coll Cardiol 2014; 63:2069–78. https://doi.org/10.1016/j.jacc.2014.01.016; PMID: 24530672. 48. Pölzl G, Allipour Birgani S, Comín-Colet J, et al. Repetitive levosimendan infusions for patients with advanced chronic heart failure in the vulnerable post-discharge period. ESC Heart Fail 2019;6:174–81. https://doi.org/10.1002/ehf2.12366; PMID: 30378288. 49. Comin-Colet J, Manito N, Segovia-Cubero J, et al. Efficacy and safety of intermittent intravenous outpatient administration of levosimendan in patients with advanced heart failure: the LION-HEART multicentre randomised trial. Eur J Heart Fail 2018;20:1128–36. https://doi.org/10.1002/ejhf.1145; PMID: 29405611. 50. García-González MJ. Efficacy and security of intermittent repeated levosimendan administration in patients with advanced heart failure: a randomized, double-blind, placebo controlled multicentre trial: LAICA study. Presented at Heart Failure Congress, 21 May 2016, Florence, Italy. 51. Oliva F, Perna E, Marini M, et al. Scheduled intermittent inotropes for ambulatory advanced heart failure. The RELEVANT-HF multicentre collaboration. Int J Cardiol 2018;272;255–79. https://doi.org/10.1016/j.ijcard.2018.08.048; PMID: 30131229. 52. Oliva F, Comin-Colet J, Fedele F, et al. Repetitive levosimendan treatment in the management of advanced heart failure. Eur Heart J Suppl 2018;20 (Suppl I):I11–20. https://doi.org/10.1093/ eurheartj/suy040; PMID: 30555280. 53. Gayat E, Arrigo M, Littnerova S, et al. GREAT Network. Heart failure oral therapies at discharge are associated with better outcome in acute heart failure: a propensity-score matched study. Eur J Heart Fail 2017;18:613 https://doi.org/10.1002/ ejhf.932; PMID: 28849606. 54. McDonagh TA, Blue L, Clark AL, et al. European Society of Cardiology Heart Failure Association Standards for delivering heart failure care. Eur J Heart Fail 2011;13:235-41; https://doi. org/10.1093/eurjhf/hfq221; PMID: 21159794.

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Clinical Practice

Winter Peaks in Heart Failure: An Inevitable or Preventable Consequence of Seasonal Vulnerability? Simon Stewart, 1 Trine T Moholdt, 2 Louise M Burrell, 3 Karen Sliwa, 1,4 Ana O Mocumbi, 5 John JV McMurray, 6 Ashley K Keates 4 and John A Hawley 4 1. Hatter Institute for Cardiovascular Research in Africa, University of Cape Town, Cape Town, South Africa; 2. Norwegian University of Science and Technology, Trondheim, Norway; 3. Austin Health/University of Melbourne, Melbourne, Australia; 4. Australian Catholic University, Melbourne, Australia; 5. Mozambique Institute for Health Education and Research, Maputo, Mozambique; 6. University of Glasgow, Glasgow, Scotland

Abstract Climate change is a major contributor to annual winter peaks in cardiovascular events across the globe. However, given the paradoxical observation that cardiovascular seasonality is observed in relatively mild as well as cold climates, global warming may not be as positive for the syndrome of heart failure (HF) as some predict. In this article, we present our Model of Seasonal Flexibility to explain the spectrum of individual responses to climatic conditions. We have identified distinctive phenotypes of resilience and vulnerability to explain why winter peaks in HF occur. Moreover, we identify how better identification of climatic vulnerability and the use of multifaceted interventions focusing on modifiable bio-behavioural factors may improve HF outcomes.

Keywords Cardiovascular seasonality, seasonal flexibility, physiological and behaviour changes, prediction, prevention, heart failure, risk Disclosure: The authors have no conflicts of interest to declare. Received: 21 November 2018 Accepted: 12 March 2019 Citation: Cardiac Failure Review 2019;5(2):83–5. DOI: https://doi.org/10.15420/cfr.2018.40.2 Correspondence: Simon Stewart, 4th floor, Chris Barnard Building, Faculty of Health Sciences University of Cape Town, Observatory, South Africa. E: simon.stewart@uct.ac.za Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

There is universal acknowledgement that climate change and extreme weather events pose an increasing threat to global health.1,2 Precisely how this will affect patterns of disease is open to conjecture. For example, while it is predicted that increasingly warmer temperatures and more intense heat waves will provoke more cardiovascular, respiratory and renal events, a corollary reduction in cardiorespiratory events related to cold weather is also predicted.1 As with any threat to human health, it is the most vulnerable who will bear the brunt of increasingly unstable climatic conditions. Such vulnerability can be immediately identified in low-to-middle income countries (LMIC), which have limited resources and flexibility to respond to emerging health threats.3 However, despite better capacity to control living conditions, high-income countries (HIC) are unlikely to be immune to the effects of climate change. Indeed, it has been suggested that seasonal variations – predominantly winter peaks in morbidity and mortality in the growing population of older patients who have heart failure (HF) syndrome in HICs – will increase with global warming.4 In the absence of a framework to understand and predict inherent vulnerability to seasonal change and acute weather events, there is a vacuum in clinical research and expert guidelines focusing on the detection and prevention of seasonality in HF. It is on this basis that we propose a bio-behavioural model of resilience that identifies those most vulnerable to patterns of seasonality and climate change.

A Historical Perspective of Climatic Vulnerability Adverse human responses to climatic conditions have long been recognised. Remarkably though, the impact of seasonal change and acute weather events on people with cardiovascular disease (CVD) is largely described as an epidemiological phenomenon.4 Accordingly, population cohort studies typically describe marked peaks in cardiovascular-related morbidity and mortality during the winter months with troughs during the summer months and less predictable peaks in event rates during or immediately following extreme or unseasonal weather events including heat-waves.4 People with preexisting conditions such as HF and common comorbid metabolic and respiratory diseases are most likely to experience a seasonal event.4 As we try to adapt to the current era of rapid climate change, it has been observed that the extent of seasonality in those affected by HF and other cardiovascular disease (including ischaemic heart disease, stroke and AF) is not precisely correlated with climatic extremes and therefore confined to cold climates.5,6 Indeed, there is convincing evidence that cardiovascular-related deaths linked to seasonality occur more frequently in milder climates.4 As we will explain, this paradox suggests that seasonality is not entirely dependent on periodic exposure to environmental provocations such as cold extremes, but also depends on how an individual or society modulates their exposure and physiological response to that provocation.

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Clinical Practice Figure 1: Spectrum of Individual Resilience to Seasonal Change and Acute Weather Events: A Cardiovascular Perspective

Resilent People who are at increased risk of cardiovascular-related morbidityy and mortality in response to seasonal or acute climatic change

Vulnerable Modulators

Physiological

Behavioral Decisions Thermoregulatory control Tobacco use Energy intake/composition Physical activity levels Alcohol consumption

Physiological Traits Haemodynamic profile Cardiovascular fitness Mental health Vascular function Body composition Vitamin D levels

Behavioural

Modulators Modifiable Socioeconomic resources Clinical management Physical environment Seasonal awareness Non-modifiable Age Sex Extent of disease

Seasonal Flexibility in Cardiovascular Disease = air pollution

= infectious disease

Figure 2: Phenotypes of Vulnerability and Flexibility to Seasonal/Weather Provocations Vulnerable Physiological State • Poor cardiorespiratory fitness • Reduced HR variability • Hypertension • Hypercoagulable state • Vascular dysfunction • Metabolic disease • Depression and/or seasonal affective disorder • Impaired cognition • Vitamin D deficiency • Arrhythmia Behavioural Decisions • Poor thermoregulatory control • High energy intake/ poor diet • Excessive alcohol consumption • Low physical activity levels • Tobacco use

Resilent Physiological State • Optimal cardiorespiratory fitness • Sufficient HR variability • Normal blood pressure range • Normal platelet function • Good psychological wellbeing • Normal vascular function • Normal weight • Sufficient vitamin D levels Behavioural Decisions • Good thermoregulatory control • Meeting recommended activity levels • Non-excessive alcohol consumption • Normal energy intake/ poor diet • No tobacco use

Risk of cardiovascular-related morbidity and mortality in response to seasonal and/or acute climatic changes = socioeconomic resources = knowledge/awareness

= clinical management

= exercise

Understanding Seasonal Vulnerability Organisms adapt to seasonal variation and abrupt changes in climatic conditions to prolong their longevity and ensure survival. Migratory birds adjust their behavioural and/or physiological responses to winter

= winter/cold-snaps

= summer/heatwaves

conditions, resulting in a winter phenotype characterised by increased storage of fat and tolerance to cold and changes in dietary patterns during the summer months.7 As humans have steadily migrated to diverse and harsh climates, we have also become ‘seasonally flexible’ to survive, albeit with an increasing capacity to enhance thermoregulatory control through clothing, housing and technology. Maintenance of optimal health, including thermoregulation, depends on autonomous and voluntary, physiological and behavioural changes to modulate the potential adverse impact of rapid or prolonged changes in environmental conditions. Human physiological studies demonstrate our inherent capacity for blunted shivering and vasoconstrictor responses to prolonged cold exposure, as well as adaptations to warmer environments.8,9 It is reasonable to assume, therefore, that individuals who are routinely exposed to the cold of winter in higher latitude countries have developed more resilient, bio-behavioural responses over time.

A Model of Seasonal Flexibility We have developed an interdisciplinary model to explain a spectrum of resilience to predictable (seasonal change) and unpredictable (extreme weather events) fluctuations in climatic conditions (Figure 1). This model proposes a combination of physiological and behavioural factors reflecting physical and cultural adaptations specific to the surrounding environment/climate many of which are reflected in distinctive cultural practices that contribute to an individual’s cardiovascular-specific and broader response to ambient climatic conditions. These factors, along with the roles of infectious diseases, pollution and mental health, contribute to a spectrum of risk for a cardiovascular event, ranging from resilience to vulnerability. 10 This model has particular relevance to understanding the pattern of disease associated with:

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Winter Peaks in Heart Failure • The increasing number of older people who survive an acute cardiac event and subsequently develop HF and multimorbidity in HICs. • The increasing number of younger people in LMICs at risk of developing HF secondary to infectious causes and/or hypertension.11

Identifying Vulnerable People It is feasible to phenotype people based on their seasonal flexibility. Figure 2 shows the polar opposites of a highly vulnerable phenotype versus a resilient one; the former being readily identifiable in most HF cohorts. We also propose that the key modulators (Figure 1), including financial resources, seasonal awareness, treatment and cardiorespiratory fitness, are critical in characterising these phenotypes. While this model presupposes that most people categorised as resilient will be younger and free from CVD, it also embraces the potential for those with pre-existing disease, including HF, to develop or regain seasonal resilience.

Promoting Resilience to Seasonal Change and Extreme Weather Events There is evidence to support the notion that promoting seasonal resilience improves health outcomes. For example, a study from 2007 examined people’s ability to adapt to winter in 50 cities in

orld Health Organization. COP24 Special report: Health & W Climate Change. Geneva: WHO, 2018. Available at: https:// www.who.int/globalchange/publications/COP24-reporthealth-climate-change/en/ (accessed 18 March 2019). Vestergaard LS, Nielsen J, Krause TG, et al. Excess all-cause and influenza-attributable mortality in Europe, December 2016 to February 2017. Euro Surveill 2017;22:pii30506. https:// doi.org/10.2807/1560-7917.ES.2017.22.14.30506; PMID: 28424146. Kruk ME, Kelley E, Syed SB, et al. Measure quality of healthcare services: what is known and where are the gaps. Bull World Health Organ 2017;95:389–A. https://doi.org/10.2471/ BLT.17.195099; PMID: 28603302. Stewart S, Keates AK, Redfern A, McMurray JJV. Seasonal variations in cardiovascular disease. Nat Rev Cardiol 2017;14:654–64. https://doi.org/10.1038/nrcardio.2017.76; PMID: 28518176. Eurowinter Group. Cold exposure and winter mortality from ischaemic heart disease, cerebrovascular disease, respiratory

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America, suggested central heating may reduce seasonal mortality.12 Moreover, clinical recommendations for large-scale vaccination programmes against influenza and pneumococcus are largely based on winter peaks in concurrent respiratory illnesses among patients with HF.4 In HICs, there is scope to run public health campaigns advising whole communities to prepare for seasonal change and acute weather events, along with individual alerts and subsidies for heating and cooling in vulnerable groups. However, reflecting current expert guidelines, beyond singular strategies addressing some of the components highlighted by our model, there is a lack of studies focusing on the complex profile and needs of vulnerable people to attenuate the effects of seasonality.13

Conclusion In a global environment of rapid and extreme climatic events, more populations will be exposed to conditions they are not readily adapted to from a bio-behavioural perspective. Contrary to current predictions, this may mean a paradoxical increase in the seasonal cycle of events with greater winter peaks in acute decompensation and sudden cardiac death among a growing patient population with HF linked to cold exposure, even as overall global temperatures rise.1 Further research is required to determine the feasibility of characterising seasonal vulnerability in HIC and LMIC settings and to develop cost-effective strategies to promote resilience against the provocations of climate change.

disease, and all causes in warm and cold regions of Europe. Lancet 1997;349:1341–6. https://doi.org/10.1016/S01406736(96)12338-2; PMID: 9149695. Phung D, Thai PK, Guo Y, et al. Ambient temperature and risk of cardiovascular hospitalization: An updated systematic review and meta-analysis. Sci Total Environ 2016; 550:1084–102. https://doi.org/10.1016/j.scitotenv.2016.01.154; PMID: 26871555. Liknes ET, Swanson DL. Phenotypic flexibility of body composition associated with seasonal acclimatization in passerine birds. Journal of Thermal Biology 2011;36:363–70. https://doi.org/10.1016/j.jtherbio.2011.06.010. Castellani JW, Young AJ. Human physiological responses to cold exposure: acute responses and acclimatization to prolonged exposure. Auton Neurosci Basic Clin 2016;196: 63–74. https://doi.org/10.1016/j.autneu.2016.02.009; PMID: 26924539. Hanna EG, Tait PW. Limitations to thermoregulation and acclimatization challenge human adaptation to

global warming. Int J Environ Res Public Health 2015;12:8034–74. https://doi.org/10.3390/ijerph120708034; PMID: 26184272. 10. M arti-Soler H, Gubelmann C, Aeschbacher S, et al. Seasonality of cardiovascular risk factors: an analysis including over 230,000 participants in 15 countries. Heart 2014;100:1517–23. https://doi.org/10.1136/heartjnl-2014-305623; PMID: 24879630. 11. Keates AK, Mocumbi AO, Ntsekhe M, et al. Cardiovascular disease in Africa: epidemiological profile and challenges. Nat Rev Cardiol 2017;14:273–93. https://doi.org/10.1038/ nrcardio.2017.19; PMID: 28230175. 12. Medina-Ramón M, Schwartz J. Temperature, temperature extremes, and mortality: a study of acclimatisation and effect modification in 50 US cities. Occup Environ Med 2007;64:827–33. https://doi.org/10.1136/oem.2007.033175; PMID: 17600037. 13. Chalabi Z, Hajat S, Wilkinson P, et al. Evaluation of the cold weather plan for England: modelling of cost-effectiveness. Public Health 2016;137:13–9. https://doi.org/10.1016/j.puhe. 2015.11.001; PMID: 26715322.

Clinical Practice

Remote Management of Heart Failure: An Overview of Telemonitoring Technologies Darshan H Brahmbhatt and Martin R Cowie Imperial College London, London, UK

Abstract Technological advances have enabled increasingly sophisticated attempts to remotely monitor heart failure. This should allow earlier identification of decompensation, better adherence to lifestyle changes and medication and interventions (such as diuretic dosage changes) that reduce the need for hospitalisation. This review discusses telemonitoring approaches in heart failure, and the evidence for their impact. It is not difficult to collect data remotely, but converting more data into better decision-making that improves the outcome of care is challenging. Policy-makers and technology companies are enthusiastic about the potential of digital technologies to transform healthcare and bring expertise to the patient, rather than the other way round, but guideline writers are not yet convinced, due to the lack of consistent findings in randomised trials.

Keywords Remote monitoring, telemonitoring, heart failure, disease management, cardiac implantable electronic devices Disclosure: MRC has received honoraria and grants from Abbott, Medtronic and Boston Scientific. DHB has received travel support from Abbott and Biotronik, and honoraria, travel support and a grant from Boston Scientific. Received: 22 January 2019 Accepted: 22 February 2019 Citation: Cardiac Failure Review 2019;5(2):86–92. DOI: https://doi.org/10.15420/cfr.2019.5.3 Correspondence: Martin R Cowie, Clinical Cardiology, National Heart and Lung Institute, Imperial College London, Dovehouse Street, London SW3 6LY, UK. E: m.cowie@imperial.ac.uk Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

Heart failure (HF) is increasing in prevalence globally, and is associated with considerable ill health, healthcare costs and mortality. Prevalence increases steeply with age, and the average age of a person admitted to hospital with decompensation in developed countries such as the UK is in the high 70s.1 Comorbidity is the rule, with half of hospitalised patients having at least five comorbidities.2,3 Frailty is common and, even when HF is diagnosed in the community, almost 10% of patients are admitted as an emergency with worsening symptoms within 1 year.4 In-hospital mortality is in the range of 5–10% in most series, and emergency readmission within 1 month is as high as 25% in some studies.5 Length of stay varies between 7 and 11 days in most developed countries, and the overall economic impact on health budgets is therefore substantial. In European and North American countries, approximately 2% of the healthcare budget is spent on HF.6 In the US, projections suggest that, by 2030, the total cost of HF will increase by almost 130% to US$70 billion annually.7 Much attention has focused on identifying decompensation of the HF syndrome before there is a need for emergency hospital admission. International guidelines recommend disease management programmes with education and support for individuals and families who wish to become more skilled in self-monitoring and management.8–10 The hope is that more intensive monitoring in the community can identify decompensation early, support adherence to lifestyle and medication, and prompt intervention (such as changes to diuretic dosage) in those who are no longer euvolaemic.

Access at: www.CFRjournal.com

Technological advances in the past three decades have allowed increasingly sophisticated attempts to remotely monitor and manage the HF syndrome. Simple, telephone-call based, remote assessment by a HF nurse specialist, standalone home-based systems, implanted devices (such as cardiac resynchronisation therapy and ICDs) and now wearable technologies have opened up a world of possibilities. It is not difficult to collect data remotely, but it has been a challenge to find a way to integrate such potentially continuous data streams into systems of care, and to convert more data into better decision-making that improves the outcome or experience of care. Policy-makers and technology companies are enthusiastic about the potential of digital technologies to transform the healthcare system into a more personalised, responsive and effective process that brings the expertise to the patient, rather than the other way round.11 The field is rapidly changing, as are the technologies that can be used, and regulators, reimbursement authorities and healthcare professionals often struggle to assess the value of the technologies. Medical guideline writers are sceptical and are lukewarm in their current recommendations (Table 1), on the basis that there is a lack of large-scale, randomised trials that show a consistent effect of the introduction of remote monitoring (RM). This article briefly discusses a variety of telemonitoring approaches that have been used in HF management, and the evidence for their impact.

Telemonitoring Technologies in Heart Failure Table 1: Guidelines on Remote Monitoring in Heart Failure European Society of Cardiology (2016):8 “Telemedicine in HF, which is also termed remote patient management, has variable clinical trial results. Several meta-analyses suggest clinical benefits, but numerous prospectively initiated clinical trials including >3700 patients have not confirmed this.” • Monitoring of pulmonary artery pressures using a wireless implantable haemodynamic monitoring system (CardioMems) may be considered in symptomatic patients with HF with previous HF hospitalisation in order to reduce the risk of recurrent HF hospitalisation. (Class IIb, level B.) • Multiparameter monitoring based on ICD (IN-TIME approach) may be considered in symptomatic patients with HFrEF (LVEF≤35%) in order to improve clinical outcomes. (Class IIb, level B.) American College of Cardiology Foundation/American Heart Association Guideline (2013):9 Systems of Care to Promote Care Coordination for Patients With Chronic HF “The quality of evidence is mixed for specific components of HF clinical management interventions, such as home-based care, disease management, and remote telemonitoring programs… Overall, very few specific interventions have been consistently identified and successfully applied in clinical practice.” Evidence Gaps and Future Research Directions “What is critically needed is an evidence base that clearly identifies best processes of care, especially in the transition from hospital to home.” Heart Failure Society of America White Paper (2018):10 “Based on available evidence, routine use of external remote patient management devices is not recommended. Implanted devices that monitor pulmonary arterial pressure and/or other parameters may be beneficial in selected patients or when used in structured programs, but the value of these devices in routine care requires further study. Future research is also warranted to better understand the cost-effectiveness of these devices.” HF = heart failure; HFrEF = heart failure with reduced ejection fraction; LVEF = left ventricular ejection fraction, IN-TIME = INfluence of Home Monitoring on The clinical Management of heart failurE patients with impaired left ventricular function.

Figure 1: Schema for Remote Monitoring

Telephone support Discussion within heart failure team No action

Patient trained in use of technology

Delegation of decision-making Patientinitiated transmissions

Patient

Consent for data transfer Either automatic or patient initiated transmission

Standalone system

Proprietary manufacturer server (cloud-based)

Action taken in line with local protocol, or with decision support tool

Implantable haemodynamic monitor

Monitoring of therapeutic cardiac device

Governance of data handling and storage

Advice to alter treatment, reiterate lifestyle advice

Clinician logs onto server, to review data trends and alerts

Clinical management policies

Reviewing clinician

Education and training in remote monitoring technology Integration of documentation into medical records

Consider clinic or general practice review

Arrange emergency admission

Boxes show key considerations for a remote monitoring clinical service. Arrows indicate the actions taken.

What is Telemonitoring? Telemonitoring or RM encompasses the use of audio, video and other telecommunication technologies to monitor patient status at a distance.12 Examples include: • Structured telephone support for patients from the HF team, typically provided by HF specialist nurses as part of a disease management programme or a post-discharge service. • Standalone devices for use at home which can measure, e.g. blood pressure, heart rate, weight and oxygen saturation (often supplemented by automated questions on a variety of symptoms). Trends in these data or movement of any one variable outside preset limits may be used by the HF team to trigger a variety of actions, including a telephone call or clinic review for further assessment, or recommendations on lifestyle and medication

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changes, or even urgent admission to hospital (Figure 1). • Cardiac implantable electronic devices, which can provide useful physiological data to aid HF management, either as a dedicated implant to monitor haemodynamics, or a part of the wealth of physiological data recorded by devices such as pacemakers and ICDs, implanted primarily for therapeutic purposes. • Most recently, a range of wearable technologies, including patches, watches or textiles that can monitor, e.g. ECG, body temperature, blood glucose concentration and body posture.

Evidence for the Benefit of Telemonitoring Technologies Telephone Support This was one of the earliest methods of RM to be adopted. Patients were called by a member of the HF team to discuss their symptoms

Clinical Practice Figure 2: Impact of Structured Telephone Support on All-cause Mortality on Meta-analysis STS Study or subgroup Angermann 2012 (INH) Baker 2011 Barth 2001 Bento 2009 Capomolla 2004 Chaudhry 2010 (Tele-HF) Cleland 2005 (Struct Tele) (TENS-HMS) DeBusk 2004 DeWalt 2006 Domingues 2011 Golbreath 2004 Gattis 1999 (PHARM) GESICA 2005 (DIAL) Krum 2013 (CHAT) Laramee 2003 Mortara 2009 (Struct Tele) (HHH) Rainville 1999 Riegel 2002 Riegel 2006 Sisk 2006 Tsuyuki 2004 Wakefield 2008

32 0 0 0 5 92 27 21 3 8 54 3 116 17 13 7 1 16 6 22 16 25

Risk ratio

Usual care

Events Total 352 303 17 20 67 826 173 228 62 57 710 90 760 188 141 94 19 130 70 203 140 99

4,749 Total (95% Cl) 484 Total events Heterogeneity: chi-squared=13.56, d.f.=20 (p=0.85); I2=0% Test for overall effect: Z=2.38 (p=0.02)

Events Total 52 2 0 1 7 94 20 29 4 13 39 5 122 16 15 9 4 32 8 22 12 11

Risk ratio

Weight M-H, fixed, 95% Cl

363 302 17 20 66 827 85 234 65 63 359 91 758 217 146 160 19 228 65 203 136 49

0.3% 1.3% 17.8% 5.1% 5.4% 0.7% 2.3% 9.8% 0.9% 23.2% 2.85% 2.8% 1.3% 0.8% 4.4% 1.6% 4.2% 2.3% 2.8%

0.63 [0.42, 0.96] 0.20 [0.01, 4.13] Not estimable 0.33 [0.01, 7.72] 0.70 [0.24, 2.11] 0.98 [0.75, 1.28] 0.66 [0.40, 1.11] 0.74 [0.44, 1.26] 0.79 [0.18, 3.37] 0.68 [0.30, 1.52] 0.70 [0.47, 1.04] 0.61 [0.15, 2.46] 0.95 [0.75, 1.20] 1.23 [0.64, 2.36] 0.90 [0.44, 1.82] 1.32 [0.51, 3.44] 0.25 [0.03, 2.04] 0.88 [0.50, 1.54] 0.70 [0.26, 1.90] 1.00 [0.57, 1.75] 1.30 [0.64, 2.64] 1.12 [0 .60, 2.09]

4,473

100.0%

0.87 [0.77, 0.98]

9.7% 0.5%

M-H, fixed, 95% Cl

517 0.01

0.1 Favours STS

100

Favours usual care

M-H = Mantel Haenszel; STS = structured telephone support. Source: Inglis et al. 2017.14 Reproduced with permission from BMJ Publishing Group.

and review their compliance with lifestyle measures and drug treatment. Patients could be asked to weigh themselves, which they then verbally reported, or identify when their weight had increased over a set level and contact the HF team for advice. These approaches have become a standard part of disease management programmes, based on the evidence from many relatively small studies showing such programmes reduce all-cause mortality and HF (but not all-cause) hospitalisation rates compared with usual care (Figure 2).13,14 However, one of the largest randomised trials of telephone-based HF monitoring (Tele-HF) in the US does not support such an approach.15 In this study, 1,653 patients were randomised to usual care or a telephone-based interactive voice-response system (Tel-Assurance™, Pharos Innovations), which patients dialled into and were then asked to respond to questions about their symptoms and weight, with the results reviewed by their clinician. There was no significant difference in the primary endpoint of death or hospitalisation within 180 days of enrolment, which occurred in 51.5% and 52.3% of patients respectively (p=0.75). It was also noted that 14% of patients randomised to the intervention never used it and, by the final week of the study, only half of them were still using the system three times per week as instructed. As is often the case with telemonitoring technologies, the initial results from a single highly engaged centre – the initial pilot study showed a 44% decrease in hospitalisation – could not be reproduced when the system was expanded into a much larger, multicentre programme. Nevertheless, telephone support for patients in a HF programme remains central to many services, but is generally targeted at more unstable patients, those who have recently returned home after an admission for HF or who live at some considerable distance from the HF service.

Standalone Telemonitoring Systems Standalone systems allow patients, usually in their own homes, to send noninvasively measured data to their healthcare team, by either telephony-based systems or the internet. In many countries, internet access is wireless, and may be via mobile telecommunication networks. The HF team review the data on a regular basis (usually looking for trends over several days) or can be sent an alert if any variable falls outside a preset limit. Action based on the data can be taken at the healthcare professional’s discretion, or there may be a local guideline or protocol that has to be followed.16 One of the earliest randomised studies was the Trans-European Network – Home-Care Management System study (TEN-HMS).17 This study recruited 426 patients with HF with reduced ejection fraction (HFrEF) from across Europe, and randomised them in a 2:2:1 ratio to home telemonitoring with a standalone system, nurse telephone support or usual care. The primary outcome of days lost to death or hospitalisation was not different between the groups, but there was a reduction in the length of hospital stay for the home telemonitoring group and lower mortality in the telephone support and telemonitoring patients compared to usual care. Meta-analysis with other (small) studies suggested mortality benefit and a reduction in HF (but not allcause) hospitalisation (Figure 3).14 The first Telemedical Interventional Monitoring in HF (TIM-HF) study with centralised RM run from a telemonitoring centre in Berlin failed to demonstrate any improvement in outcomes in 710 patients randomised and followed up for a minimum of 12 months.18 However, the larger, follow-on randomised study in 1,571 patients (which required patients to have had a HF hospitalisation in the 12 months preceding enrolment and no evidence of major depression), using a wireless system with a digital tablet to send daily transmissions of

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Telemonitoring Technologies in Heart Failure Figure 3: Impact of Noninvasive Telemonitoring on All-cause Mortality on Meta-analysis

Study or subgroup Antonicelli 2008 Balk 2008 Biannic 2012 (SEDIC) Blum 2014 (MCCD) Cleland 2005 (Telemon) (TENS-HMS) De Lusignan 2001 Dendale 2012 (TEMA-HF1) Giordano 2009 Goldberg 2003 (WHARF) Koehler 2011 (TIM-HF) Lyngå 2012 (WISH) Mortara 2009 (Telemon) (HHH) Seto 2012 Soran 2008 Villani 2014 (ICAROS) Vuorinen 2014 Woodend 2008 Total (95% CI)

Usual care Telemonitoring Events Total Events Total Weight 3 9 8 49 28 2 4 21 11 54 5 8 3 11 5 0 5

28 101 45 104 168 10 80 230 138 354 166 101 50 160 40 47 62

5 8 14 45 20 3 14 32 26 55 8 9 0 17 9 0 4

1,884

226 Total events Heterogeneity: chi-squared=19.70, d.f.=15 (p=0.18); I2= 24% Test for overall effect: Z=2.77 (p=0.006)

29 113 45 102 85 10 80 230 142 356 153 160 50 155 40 47 59 1,856

Risk ratio M-H, fixed, 95% Cl

0.62 [0.16, 2.36] 1.8% 1.26 (0.50, 3.14] 2.8% 0.57 [0.27, 1.23] 5.1% 1.07 [0.79, 1.44] 16.6% 0.71 [0.42, 1.18] 9.7% 0.67 [0.14, 3.17] 1.1% 0.29 [0.10, 0.83] 5.1% 0.66 [0.39, 1.10] 11.7% 0.44 [0.22, 0.85] 9.4% 0.99 [0.70, 1.39] 20.0% 0.58 [0.19, 1.72] 3.0% 1.41 [0.56, 3.53] 2.5% 0.2% 7.00 [0.37, 132.10] 0.63 [0.30, 1.29] 6.3% 0.56 [0.20, 1.51] 3.35% Not estimable 1.19 [0.34, 4.22] 1.5% 100.0%

0.80 [0.68,0.94]

269 0.005 0.1 1 10 Favours telemonitoring Favours usual care

200

M-H = Mantel Haenszel. Source: Inglis et al. 2017.14 Reproduced with permission from BMJ Publishing Group.

weight, blood pressure, heart rate, ECG, oxygen saturation and health status questionnaire, reported a borderline statistically significant reduction of just under 7 days in the number of days lost due to unplanned cardiovascular hospital admissions or death compared to the control group (17.8 versus 24.2 days per year, p=0·046).19 There was also a significant decrease in the secondary endpoint of all-cause mortality, but not cardiovascular mortality.

the use of intrathoracic impedance as a marker of HF deterioration. Of the 33 patients who had the device implanted, 10 patients had 25 hospitalisations over the course of 21 months’ follow-up.25 Retrospective review of the impedance data showed a decrease in the 2 weeks preceding HF hospitalisation, well in advance of the symptoms. There was also an increase in intrathoracic impedance as patients underwent diuresis.

Outside this centralised 24/7 telemonitoring service in Germany, other large randomised trials have failed to show benefit. In a study in academic centres in California, an RM approach combined with intensive coaching of patients did not show any improvement in mortality or hospitalisation over a 6-month period.20

This early promise was not confirmed with subsequent larger trials of the technology. Using an alert system to identify when the Optivol score had increased above a predefined threshold that suggested HF deterioration, the Diagnostic Outcome Trial in Heart Failure (DOT-HF) study randomised 335 patients to management with physician and patient access to alerts, or not. The alert arm saw a 79% increase (p=0.02) in the HF hospitalisation rate.26 Overall, the specificity of the alert system was not acceptable, particularly in the early period after implantation, leading to a high false positive rate and increased hospital admission by the physicians caring for the patients.27

In the UK, the Whole System Demonstrator project involved the remote exchange of data between 3,230 patients with diabetes, chronic obstructive pulmonary disease or HF in 179 general practices over 1 year in three areas in England. After adjustment for baseline differences, there was a statistically significant reduction in mortality and length of stay for those hospitalised, but no difference in emergency admission rates for those remotely monitored.21 Overall savings to the healthcare system were small (geometric mean £242 per patient) and cost-effectiveness was poor.22

Remote Monitoring Through Therapeutic Cardiac Implantable Electronic Devices The past decade has seen a revolution in the use of remote monitoring of therapeutic devices, such as pacemakers and defibrillators. RM is now standard in many centres for device function and safety reasons.23,24 For patients with HF, remote monitoring offers the additional possibility of detecting decompensation earlier. One of the first intrathoracic technologies developed was Optivol™ (Medtronic), a measure of intrathoracic impedance that is undertaken by direct measurement between the RV lead and pulse generator of the device. The Medtronic Impedance Diagnostics in Heart Failure Trial (Mid-HEFT) was a prospective, observational study investigating

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Further improvements in the positive predictive value of monitoring have been achieved by adding further parameters into algorithms that incorporate intrathoracic impedance. The Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure (PARTNERS HF) and Integrated Diagnostic for Heart Failure (TRIAGE-HF) trials have shown promise in identifying which patients are at risk of hospitalisation.28,29 To date, the Remote Management of Heart Failure Using Implantable Electronic Devices study (REM-HF) is the largest prospective randomised clinical trial conducted on RM through implanted devices.30 In this trial, 1,650 patients with HF who had an implanted cardiac device were randomised to active weekly review of remote monitoring data or usual care across nine UK hospitals, with an average follow-up of 2.8 years. The primary outcome of death or hospitalisation from cardiovascular causes was the same in the RM group (42.4%) and the control group (40.8%) of patients (p=0.87), despite considerable extra activity being triggered by the remotely collected data.

Clinical Practice Figure 4: Meta-analysis of Effect of Implantable Haemodynamic Monitoring on Heart Failure Hospitalisation

2,700 patients, is under way to test whether HeartLogic alert-based management can improve mortality and morbidity from HF when used in more routine care (NCT03237858).

COMPASS_FEAS (n=32)

Remote Monitoring Through Implantable Haemodynamic Monitors Implantable devices offer an opportunity to assess disturbances in haemodynamic parameters promptly, rather than relying on the measurement of less direct measures of HF decompensation which may take longer to become abnormal. Left ventricular filling pressure may be the best measure of the control of the HF syndrome, and several technologies have been developed to measure this directly or indirectly. The aim is to then optimise therapy to maintain filling pressure within an optimal range. Meta-analysis of published studies suggests benefit in preventing hospitalisation (Figure 4).33

HOMEOSTASIS (n=40) CHAMPION (n=550) COMPASS (n=274) REDUCE-HF (n=400) Average – random effects Average – fixed effects 0.0

0.5

1.0

1.5

2.0

HR Using a random effect model, the reduction is 38% (HR 0.62, 95% CI [0.50–0.78], p<0.001) and 37% (HR 0.63, 95% CI [0.54–0.73] p<0.001) using a fixed-effects model. Source: Adamson et al. 2016.33 Reproduced with permission from John Wiley and Sons.

Thus far, only the INfluence of Home Monitoring on The clinIcal Management of heart failurE patients with impaired left ventricular function (IN-TIME) study has provided prospective randomised data of benefit in clinical outcomes for remote monitoring of implanted devices.31 For this study, 664 patients were randomly assigned to multiparameter RM in addition to standard care or standard care alone. The composite clinical score, which incorporated all-cause death, HF hospitalisation, change in New York Heart Association (NYHA) class, and change in patient global self-assessment, was better in the RM population, largely driven by a lower death rate in the RM group (estimated 1 year mortality 2.7% versus 6.8% (HR 0.37; 95% CI [0.16–0.83], p=0.012). The difference in results between REM-HF (UK) and IN-TIME (Europe, Israel and Australia) are as yet unexplained, but may be down to different healthcare settings, lower symptom severity, devolved rather than centralised monitoring of the data and weekly remote monitoring, rather than daily review and intervention in REM-HF compared with IN-TIME. It is likely that the impact of RM is highly context dependent, with the processes that support decision-making on remote data being as important as the data and the monitoring tools themselves. One solution that combines multiparametric RM with complex data processing is the HeartLogic™ algorithm (Boston Scientific). Developed in 900 patients as part of the Multisensor Chronic Evaluations in Ambulatory Heart Failure Patients (MultiSENSE) study, this algorithm incorporates heart sounds, respiratory rate, heart rate, activity levels and intrathoracic impedance to generate a ‘HeartLogic’ score.32 The algorithm uses the patient as their own control, calculating changes from baseline, which removes the need for the clinician to assess the different data streams for all patients. Using a preset threshold provides a 70% sensitivity for identifying a HF event (e.g. one that requires HF hospitalisation or IV therapy) with an unexplained alert rate of 1.5 per patient-year. The alert gives a median lead time before a HF event of 34 days, with 90% of patients being alerted 2 weeks before an event. The Multiple Cardiac Sensors for the Management of Heart Failure (MANAGE-HF) trial, a large, multicentre outcome study recruiting

The Chronicle™ implantable haemodynamic monitor (Medtronic) was designed as a subcutaneous device with a transvenous sensor, much like a pacing lead, that could be deployed in the right ventricular (RV) outflow track, measuring RV pressures to estimate pulmonary artery diastolic pressures, alongside recording heart rate, temperature and physical activity. The subcutaneous device transmitted information intermittently to a home monitor, which would upload the information to a remote server for clinicians to review. The Chronicle Offers Management to Patients with Advanced Signs and Symptoms of Heart Failure (COMPASS-HF) study randomised 274 patients who had the device implanted to receive optimal medical care guided by the device (n=134) or a control group with optimal care alone (n=140).34 While the device met the safety endpoints at 6 months, the reduction in the primary composite outcome of HF-related hospitalisations, emergency-department visits or urgent clinic visits was non-significant at 21% (p=0.33). On the basis on these results, the Food and Drug Administration’s Circulatory System Devices Panel voted against approving the Chronicle device. The CardioMEMS™ HF System (Abbott Vascular) has Food and Drug Administration approval and a CE mark, and has been implanted in more than 10,000 patients with HF worldwide. The CardioMEMS device is a pulmonary artery wireless microelectromechanical sensor that is implanted using transcatheter techniques and fluoroscopic guidance. The device is permanent and becomes covered with endothelium in the weeks after implantation. A patient electronics system (a pillowlike device) is used to collect daily pulmonary artery haemodynamic measurements, and the patient’s physician or nurse can access the data via a secure internet connection. The pivotal CardioMEMS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in NYHA Class III Heart Failure Patients (CHAMPION) trial demonstrated the effectiveness of patient management guided by such daily pulmonary artery pressure readings.35 In this trial, 550 patients with NYHA class III symptoms who had the sensor implanted were randomised to management guided by readings from the device (n=270) or a control group of standard care (n=280). There was a 33% (95% CI [20–45%]) decrease in HF hospitalisations over an average of 18 months of follow-up in the randomised phase of the study (p<0.0001).36 A number of studies assessing the utility of pulmonary artery haemodynamic measurements in a broader cohort of patients and in different healthcare settings are under way. The Hemodynamic-GUIDEd Management of Heart Failure (GUIDE-HF study) (NCT03387813) will

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Telemonitoring Technologies in Heart Failure enrol 3,600 patients with NYHA class II–IV symptoms in the US, and the CardioMEMS HF System OUS Post Market Study (NCT02954341) and the CardioMEMS European Monitoring Study for Heart Failure (MEMSHF) trial (NCT02693691) will recruit patients in Europe and Australia to investigate effectiveness in these populations outside the US. A further development in RM through implantable devices was a strategy that focused on empowering the patient in self-management, rather than relying on direct input from their HF clinical team after reviewing remotely collected data. The HeartPOD™ implantable sensor lead (St Jude Medical) allowed measurement of left atrial pressure (LAP) which was then visible to the patient, who could then alter their own treatments based on education delivered to them by the HF team. The Left Atrial Pressure Monitoring to Optimize Heart Failure Therapy (LAPTOP-HF) study planned to enrol 730 patients (with NYHA class III symptoms and HF hospitalisation in the past 12 months or elevated B-type natriuretic peptide levels) and randomise them to physiciandirected patient self-management based on LAP readings taken twice daily or to usual care.37 The trial was stopped prematurely after 486 patients had been recruited because of an excess of procedure-related complications related to the atrial transseptal puncture. At that point in time, there was a 41% decrease in annualised HF hospitalisations among the patients enrolled (p=0.005).38

Wearable Technologies The concept of multiple sensors contributing to an HF alert system is also the focus of the Wearable Congestive HF Management System (WCHFS, also known as SimpleSENSE), which incorporates various sensors in a wearable undergarment. The observational Nanowear Heart Failure Management Multi-sensor Algorithm (Nanosense) cohort study (NCT03719079) is recruiting patients with the aim of demonstrating which sensors are of diagnostic use in predicting HF deterioration. This may be the first of many wearables that are developed for remote monitoring of HF, alleviating the need for implants in patients who do not have defibrillators or pacemakers.39 There are many other mobile health (also called m-health) technologies in development for HF, but evidence on their benefits awaits robust assessment.40

Current Challenges and Future Technologies There is no difficulty in identifying technologies that can accurately measure a physiological variable, or record a patient report of symptoms or quality of life, and accurately transmit this back to the healthcare team. The problem has been in identifying which data point or points provide signal rather than just noise, and identifying when a healthcare team members (or patient themselves) should act. Artificial

National Institute of Cardiovascular Outcomes Research. National Audit of Cardiac Rhythm Management Devices. April 2015–March 2016. London: NICOR, 2017. Available at: www.nicor.org.uk/ wp-content/uploads/2019/02/crm-devices-national-auditreport-2015-16_v2.pdf (accessed 6 May 2019). Centers for Medicare & Medicaid Services. Chronic Conditions Among Medicare Beneficiaries. Chartbook: 2012 edition. Baltimore, MD: Centers for Medicare & Medicaid Services, 2012. Available at: https://www.cms.gov/Research-StatisticsData-and-Systems/Statistics-Trends-and-Reports/ChronicConditions/2012ChartBook.html (accessed 6 May 2019). Conrad N, Judge A, Tran J, et al. Temporal trends and patterns in heart failure incidence: a population-based study of 4 million individuals. Lancet 2018;391:572–80. https://doi. org/10.1016/S0140-6736(17)32520-5; PMID: 29174292. Bottle A, Kim D, Hayhoe B, et al. Frailty and comorbidity predict first hospitalisation after heart failure diagnosis in primary care: population-based observational study in

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intelligence may assist human intelligence in this process in the near future.41,42 The key question is how these technologies can be used to ensure better, timely decision-making, rather than just to generate a higher workload with more decisions and action to be taken. The huge range of technologies available and the lack of a consistent evidence base is a challenge to the healthcare system, including to those responsible for approving funding. The design of clinical studies to robustly assess impact on clinically important outcomes, patient experience, workflow and cost is evolving, as is the framework of regulators and reimbursement authorities. Challenges remain around what evidence is considered useful by the many stakeholders involved in the process of implementation of RM and other digital technologies into traditional healthcare settings. Supporting healthcare team members to deal with remotely collected data is essential: who is responsible for looking at the data? How often? What happens out of hours or at the weekend? How is data security maintained? Which patients should be offered which technology (if any), and at what stage in their disease pathway? Clinical guidelines are silent on these issues, and most studies provide scant detail on how the flow of data was integrated in the usual care pathway. In any case, without reimbursement, there is little incentive for a healthcare service to introduce RM, as it may just increase the non-contact workload while reducing income from face-to-face clinical reviews. Figure 1 shows a schema that illustrates some of the key issues that require discussion before a remote monitoring service is established. Very recently, key national and international organisations, as well as health policy-makers, have recognised the challenges around bringing digital technologies into the healthcare system.43 It is likely that only co-ordinated efforts from all the key stakeholders, including patients themselves, will allow the value of particular technologies to be established. However, the potential is enormous. If we look at how diabetes is managed, we can see a model where people living with the condition rarely have to seek professional assistance, and how their blood glucose concentrations can easily be incorporated into data platforms that can be accessed by patients, their carers and their healthcare professionals at any point in time and from anywhere there is internet access to the cloud-based server.44 For those requiring insulin, there are now patches that monitor blood glucose every few minutes, and wirelessly communicate with an insulin pump to help ensure stable blood glucose control.45 We are far from this situation for HF, which may intrinsically be a more complex syndrome but, undoubtedly, RM will find an important place for those living with HF and the professionals advising them.

England. Age Ageing 2019. https://doi.org/10.1093/ageing/ afy194; PMID: 30624588; epub ahead of press. Cowie MR, Anker SD, Cleland JG, et al. Improving care for patients with acute heart failure: Before, during and after hospitalisation. Oxford: Oxford PharmaGenesis, 2014. Available at: www. oxfordhealthpolicyforum.org/AHFreport (accessed 6 May 2019). Soundarraj D, Singh V, Satija V, Thakur RK. Containing the costs of heart failure management: a focus on reducing readmissions. Heart Fail Clin 2017;13:21–8. https://doi. org/10.1016/j.hfc.2016.07.002; PMID: 27886926. Benjamin EJ, Virani SS, Callaway CW, et al. Heart disease and stroke statistics – 2018 update. A report from the American Heart Association. Circulation 2018;137:e67–492. https://doi.org/10.1161/CIR.0000000000000558; PMID: 29386200. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of

acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association of the ESC. Eur Heart J 2016;14:37:2129–200. https://doi.org/10.1093/eurheartj/ ehw128; PMID: 27206819. 9. Yancy CW, Jessup M, Bozkurt B, et al. 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation 2013;128:e240–e327. https://doi.org/10.1161/ CIR.0b013e31829e8776; PMID: 23741058. 10. Dickinson MG, Allen LA, Albert NA, et al. Remote monitoring of patients with heart failure: a white paper from the Heart Failure Society of America scientific statements committee. J Card Fail 2018;24:682–94. https://doi.org/10.1016/j. cardfail.2018.08.011; PMID: 30308242. 11. Department of Health and Social Care. Policy paper. The future of healthcare: our vision for digital, data and

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33. A damson PB, Ginn G, Anker SD, et al. Remote haemodynamicguided care for patients with chronic heart failure: a metaanalysis of completed trials. Eur J Heart Fail 2017;19:426–33. https://doi.org/10.1002/ejhf.638; PMID: 27634736. 34. Bourge RC, Abraham WT, Adamson PB, et al. Randomized controlled trial of an implantable continuous hemodynamic monitor in patients with advanced heart failure: the COMPASS-HF study. J Am Coll Cardiol 2008;51:1073–9. https:// doi.org/10.1016/j.jacc.2007.10.061; PMID: 18342224. 35. Adamson PB, Abraham WT, Aaron M, et al. CHAMPION trial rationale and design: the long-term safety and clinical efficacy of a wireless pulmonary artery pressure monitoring system. J Card Fail 2011;17:3–10. https://doi.org/10.1016/j. cardfail.2010.08.002; PMID: 21187258. 36. Abraham WT, Stevenson LW, Bourge RC, et al. Sustained efficacy of pulmonary artery pressure to guide adjustment of chronic heart failure therapy: complete follow-up results from the CHAMPION randomised trial. Lancet 2016;387:453–61. https://doi.org/10.1016/S0140-6736(15)00723-0; PMID: 26560249. 37. Maurer MS, Adamson PB, Costanzo MR, et al. Rationale and design of the Left Atrial Pressure Monitoring to Optimize Heart Failure Therapy Study (LAPTOP-HF). J Card Fail 2015;21:479–88. https://doi.org/10.1016/j.cardfail.2015.04.012; PMID: 25921522. 38. Abraham WT, Adamson PB, Costanzo MR, et al. Hemodynamic monitoring in advanced heart failure: results from the LAPTOP-HF trial. J Card Fail 2016;22:940. https://doi. org/10.1016/j.cardfail.2016.09.012. 39. Bonato P. Advances in wearable technology and its medical applications. Conf Proc IEEE Eng Med Biol Soc 2010;2010:2021–4. https://doi.org/10.1109/IEMBS.2010.5628037; PMID: 21097220. 40. Cajita M, Gleason KT, Han HR. A systematic review of mHealth-based heart failure interventions. J Cardiovasc Nurs 2016;31:E10–22. https://doi.org/10.1097/ JCN.0000000000000305; PMID: 26544175. 41. Andrès E, Talha S, Zulfiqar AA, et al. Current research and new perspectives of telemedicine in chronic heart failure: narrative review and points of interest for the clinician. J Clin Med 2018;7:E544. https://doi.org/10.3390/jcm7120544; PMID: 30551588. 42. Bonderman D. Artificial intelligence in cardiology. Wien Klin Wochenschr 2017;129:866–8. https://doi.org/10.1007/s00508017-1275-y; PMID: 28980130. 43. WHO Regional Office for Europe. From Innovation to Implementation: eHealth in the WHO European Region. Denmark; WHO, 2016. Available at: www.euro.who.int/en/publications/ abstracts/from-innovation-to-implementation-ehealth-in-thewho-european-region-2016 (accessed 6 May 2019). 44. My Diabetes My Way. About us. Available at: https://www. mydiabetesmyway.scot.nhs.uk (accessed 6 May 2019). 45. Food and Drug Administration. Summary of safety and effectiveness data (SSED). OneTouch Vibe™ Plus system. Washington, DC: FDA, 2016. Available at: https://www. accessdata.fda.gov/cdrh_docs/pdf13/P130007S016B.pdf (accessed 6 May 2019).

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Hospice Use Among Patients with Heart Failure Sarah H Cross, 1 Arif H Kamal, 2,3 Donald H Taylor Jr 1,4,5 and Haider J Warraich 6 1. Sanford School of Public Policy, Duke University, Durham, NC, US; 2. Duke Cancer Institute, Durham, NC, US; 3. Duke Fuqua School of Business, Duke University, Durham, NC, US; 4. Margolis Center for Health Policy, Duke University, Durham, NC, US; 5. Duke Clinical Research Institute, Durham, NC, US; 6. Department of Medicine, Division of Cardiology, Duke University Medical Center, Durham, NC, US

Abstract Despite its many benefits, hospice care is underused for patients with heart failure. This paper discusses the factors contributing to this underuse and offers recommendations to optimise use for patients with heart failure and proposes metrics to optimise quality of hospice care for this patient group.

Keywords Heart failure, hospice, palliative care, end of life care Disclosure: DHT is a member of the board of the Carolinas Center for Hospice and Palliative Care. All other authors have no conflicts of interest to declare. Received: 17 January 2019 Accepted: 26 March 2019 Citation: Cardiac Failure Review 2019;5(2):93–8. DOI: https://doi.org/10.15420/cfr.2019.2.2 Correspondence: Haider J Warraich, 2301 Erwin Road, DUMC 3485, Durham, NC 27710, US. E: haider.warraich@duke.edu Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

Heart failure (HF) is estimated to affect 26 million people worldwide and is responsible for an annual global economic burden of US$108 billion.1,2 An ageing population and a reduction in mortality from other conditions such as acute MI are expected to result in an increased HF prevalence throughout much of the world.1,3–6 The prevalence of HF has particularly increased among those aged 85 years and older.7,8 HF is an especially burdensome disease both physically and psychosocially. Compared with those with other chronic illnesses, patients with HF have significantly more impairment in quality of life.9 According to the WHO, nearly 39% of adults needing palliative care at the end of life have cardiovascular disease.10 Exacerbations in symptoms and carers being unprepared for this are likely to contribute to HF being a leading cause of hospital readmissions.11–13 Hospice care can ameliorate distress at the end of life for patients with HF, yet it is underused in this population.14–17 Increasing the use of hospice care among this population should be a priority, although determining when a patient with HF should be referred to hospice care remains a challenge. In this paper we discuss the benefits of hospice care for people with HF, detail the factors contributing to the underuse of hospices among people with HF and offer recommendations to optimise hospice use.

Benefits of Hospice Care for Patients with Heart Failure Hospice care is team-based palliative care typically reserved for those with a life expectancy of 6 months or less. It can be provided to any patient with a life-limiting illness and combines medical care, pain management and emotional and spiritual support. While palliative care may be received alongside disease-directed treatment, hospice care focuses on comfort and quality of life when a cure is no longer possible. It is the model for high-quality patient-centred care for those facing a life-limiting illness.18 Hospice care is typically provided in the place where a patient lives – whether their own home or in a care home or

nursing home. Many countries also have inpatient hospice facilities that may be free-standing or located in a hospital; however, the structure of these services differs between countries. Patients receiving hospice care generally experience lower rates of hospitalisation, admission to intensive care and invasive procedures at the end of life.19 Additionally, hospice care often improves symptom distress, care quality, caregiver outcomes and patient and family satisfaction.20–24 Some researchers have found that hospice and palliative care is associated with longer survival in some HF patients.14,19,22,25 In the US, roughly one in four Medicare beneficiaries hospitalised for decompensated HF are readmitted within 30 days of discharge.26 Preventable hospital readmissions are estimated to cost the US healthcare system US$25 billion each year and place patients at greater risk of complications and infections.27 Similar rates of hospital readmissions with a similar burden have also been documented around the world.28,29 Four in 10 patients with HF in Greece were readmitted to hospital in less than a year, according to one study.30 Inadequate followup care is a major factor in hospital readmissions and hospice use has been associated with a lower risk of 30-day hospital readmission among patients with HF.31 Another line of research shows that hospice care leads to reduced medical costs while providing these well-established benefits for seriously ill patients.19,22,25,31 Although most research on the cost-effectiveness of hospice care has been conducted in the US, reduced costs from hospice use have also been documented in Israel. 32

Contributing Factors to Hospice Underuse in People with Heart Failure Despite the benefits of hospice care, patients face significant barriers to receiving timely referrals. In the UK, only 4% of patients with HF have received care from a hospice or palliative care team.33 Nearly one-third

Access at: www.CFRjournal.com

Clinical Practice Figure 1: Barriers to Hospice Use in Patients with Heart Failure

• • • •

Policy Factors • 6-month survival requirement • Low fixed daily payment rate • No concurrent care option

Disease Factors Unpredictable trajectory Symptom burden Frequent exacerbations Need for invasive palliative therapies

Clinical Factors • Difficult prognostication • Discomfort with palliative care • Lack of training in heart failure for hospice staff

Other Factors • Patients overestimate survival • Lack of research in palliative care in heart failure • Lack of integration of palliative care with cardiology

of American patients with HF receive hospice care at the time of death and those who do tend to enrol late in the course of their disease.34–37 In one study of hospitalised patients with HF, those discharged to hospice care had a median survival of 11 days and nearly one-quarter of patients died within 3 days.34 The short length of stay in hospices for many patients with HF is especially concerning, as this suggests that patients and their families may not receive the full benefit of the care. Multiple studies have found an association between family perception of a late referral to hospice and a poorer care experience for patients and family members.21,38–40 Patients with short lengths of stay in hospices are also less likely to receive care at home despite this being the preference of many.41,42 We have identified seven major themes that drive hospice underuse in HF.

rate of acute medical service use in the last 30 days before death among patients with HF compared with those with cancer.46,54,56 As a result, patients with HF have higher rates of hospital death compared with patients with other diseases.57 Depression is also highly prevalent among patients with HF.58 The high symptom severity of HF also contributes to caregiver burden. As patients with HF become unable to handle activities of daily living, carers – who are usually family members – provide vital support and care. These activities may include monitoring of wellbeing and changes in health status, supporting adherence to dietary restrictions, managing medication that frequently requires modification, ensuring safety and providing emotional support.59 As patients decline, carers increasingly provide more hands-on personal care such as dressing and bathing. Relatives and carers of patients with HF report high rates of depression and impaired qualify of life.60,61 Carers often lack clinical knowledge of the condition and its management and many feel unprepared to deal with exacerbations at home.62-64 According to one Swedish study, nearly one-third of partners of patients with HF reported perceiving a medium level of carer burden.65 Unpaid carers represent a ‘hidden’ lay palliative care workforce who are vulnerable, underserved and in great need of professional palliative care support.66

Geographic and Socioeconomic Disparities Social and cultural factors influence how care is used at the end of life. HF is a care-intensive disease and hospice care is unable to be given around the clock. Patients who lack familial carers or the money to pay carers may be less able to remain at home with hospice care. Median income has been inversely associated with lower odds of 30-day hospital readmission, suggesting that financial resources are essential for remaining at home.67 Multiple studies have found an association between low socioeconomic status and more aggressive medical care at the end of life, increased likelihood of dying in institutional settings and a lower likelihood of receiving hospice services.68–70

Disease Trajectory Despite the benefits of hospice care, patients face significant barriers to receiving timely referrals to that care stemming from the unique course of HF and the difficulty there is in providing an accurate prognosis (Figure 1). Patients with HF tend to experience a gradual decline punctuated by intermittent exacerbations that, when treated, can result in a near return to the patient’s pre-exacerbation status.43,44 As it is not possible to know which exacerbation will be fatal, death often seems unexpected.45 The fact that a patient’s prognosis is the predominant criterion used to indicate eligibility for hospice care makes it difficult to know when it is appropriate for patients with HF to be referred.46 Patients who experience a more rapid decline may better recognise their limited life expectancy and be more willing to shift from conventional to palliative care and be motivated to seek additional support.47–49 Advance care planning (ACP), which has been associated with increased hospice use, is critical given HF’s undulating disease course; however, most patients with HF lack advance directives.50,51 There is growing acceptance that provision of palliative care should be based on patient need and be given at any point in a patient’s illness, however, the disease trajectory of HF remains a barrier to hospice use by this population.

Symptom Burden that is Difficult to Manage at Home Some patients with HF experience more severe symptoms than patients with advanced cancer.52,53 Dyspnoea, fatigue and pain are particularly problematic and are likely to contribute to the higher

In many European countries, palliative care is funded through a mix of statutory funding, charities, private insurance and out-of-pocket payments.71 A high reliance on charitable giving results in a postcode lottery, with available services being determined by where one lives. Inpatient hospices are particularly reliant upon charitable income to cover costs. It is perhaps unsurprising then that inpatient hospice deaths in England are less likely in more deprived areas.72 Rural patients have poorer access to hospice and hospices in rural areas may be more likely to serve a smaller number of patients and to limit expensive services due to fear of financial risk.16,73,74

Late Referrals to Palliative Care and Hospice The European Society of Cardiology, American College of Cardiology (ACC) and American Heart Association (AHA) have called for palliative care to be integrated into the care of patients with advanced heart disease, yet patients with HF are often not referred to palliative care.75,76 A survey of Japanese Circulation Society-authorised cardiology training hospitals found that 42% of institutions had held a palliative care conference for patients with HF, but only 9% held them regularly.77 Sixty-one percent of surveyed hospitals reported rarely holding them.78 A study of people who had died in Veterans Affairs health facilities in the US found that less than half of those with cardiopulmonary failure received palliative care consultations.79 Another study involving 215 patients with either advanced cancer, chronic obstructive pulmonary disease or HF found that when a physician discussed hospice care

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Hospice Use Among Patients with Heart Failure there was a strong association with subsequent enrollment, however, only 7% of patients with HF enrolled compared with 46% of patients with cancer.80 In general, palliative care should be considered from diagnosis onward; however, it may be unwarranted for cardiologists to refer to palliative care specialists in early-stage HF as patients may be asymptomatic or sufficiently cared for with primary palliative care from their HF clinician.81,82 Patients with HF who may appear to be near death are often candidates for procedures such as left ventricular assist device or heart transplant. Hospice eligibility is less clear-cut for people with HF and may complicate referrals. Inaccuracy in HF prognostication is another impediment to palliative care and hospice referral. One study of physicians found that fewer than half of physicians accurately estimated survival in patients with HF.83 Palliative care needs assessments tools for HF, such as the Needs Assessment Tool: Progressive Disease–Heart Failure (NAT:PD-HF), have been validated and tested internationally.84,85 Although needs assessment tools may assist in the identification of palliative care needs for people with HF, a recent test of the feasibility of a Dutch NAT:PD-HF suggests that an instrument alone is likely to be unable to facilitate timely recognition of palliative care needs by professionals with limited palliative care training and expertise.85

Professional Factors Documentation of advance directives has been associated with lower costs, lower risk of in-hospital death, and greater hospice use in regions with higher levels of end of life spending; however, most hospitalised patients with HF do not have documented advance directives.50,86 Cardiologists have reported discomfort in discussing end of life care and many differ in their beliefs regarding whose responsibility these conversations are.87 Physicians also report feeling more uncomfortable discussing palliative care with people with HF than with patients who have lung cancer.83 Many cardiologists have also reported that time constraints are a barrier to their engagement in ACP. Advances in therapies and devices for the treatment of HF may complicate the work of hospice providers. Few hospices have training, policies or procedures or standardised care plans for managing patients with HF.16 Although one-third of Medicare patients with ICDs receive hospice care, most hospices lack protocols for ICD deactivation.88,89 In a UK study of palliative care professionals, 24% reported experiencing difficulties with ICD deactivation at the end of life and 83% of respondents reported ICD deactivation was seldom discussed by cardiologists before making a palliative care referral.90 ICDs do not improve symptoms and device discharge or complications may add to patient suffering.46 In addition to the prohibitive costs of inotropes and other IV drugs, many hospices will not provide IV treatments in the home setting. Hospices may not provide continuous positive airway pressure (CPAP) machines despite the fact that sleep-disordered breathing occurs in at least half of people with advanced HF.16,91 Many hospices lack the knowledge and expertise necessary for the management of HF. A study of hospice staff in North and South Carolina in the US found that most staff lacked experience and were uncomfortable when using inotropes, mainly because their hospice did not provide coverage of inotropes.92 In a focus group of HF palliative

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Table 1: Recommendations to Optimise Hospice Care for Heart Failure Increase flexibility in hospice enrollment by prognosis and need: given the difficulty in assessing prognosis, we recommend additional factors to determine hospice eligibility Early introduction of palliative care for HF patients: efforts to introduce palliative care earlier in the natural course of the disease should be made and tested Improved advance care planning: advance care planning for people with HF should incorporate features specific to them, such as ICD and LVAD status and iotropes in use Development of new care and payment models for hospice care: given limitations of current models for HF, new care and payment models should be tested and implemented Improve training of hospice staff in HF care: to increase comfort and competency, nursing staff should receive HF-specific training Additional intensive social and medical support at home: people with HF are at high risk of hospital admission, which should be addressed with additional support services at home Increase research in palliative care in HF: more funding from federal ad other sources should be directed towards testing and implementing HF-specific palliative care HF = heart failure; LVAD = left ventricular assist device.

care specialist nurses in Scotland and England, junior nurses reported their reluctance to accept patients with HF for hospice care and some hospices needed reassurance about their ability to meet the needs of patients with HF.93

Recommendations Improved Advance Care Planning and Earlier Palliative Care Integration Patients with HF and often their clinicians rarely realise the terminal nature of their disease.94 Little is known about communication and decision-making between clinicians and patients with HF, yet patientcentered communication is possible and essential.95 Clinicians must assist patients in developing a realistic assessment of their expected survival throughout the course of the disease that could assist decision-making related to advance care planning (Table 1).96 Given the shortage of palliative care specialists, cardiologists must become proficient in generalist palliative care skills.97 Experts recommend that palliative care be introduced into HF care by patients’ primary clinical teams, followed by palliative care consultation in selected patients.96 The ESC recommends that end of life care be considered for people with HF who: • Have progressive functional decline and dependence in most activities of daily living; • Experience severe HF symptoms with poor quality of life despite optimal pharmacological and non-pharmacological therapies; • Have frequent hospital admissions or other serious episodes of decompensation despite optimal treatment; • Have been ruled out of heart transplantation and mechanical circulatory support; • Patients experiencing cardiac cachexia; and • Those clinically judged to be near the end of life.98 Creative partnerships and collaboration between teams may be tailored to take advantage of the staffing and resources of particular healthcare systems and facilities. One Canadian institution found that embedding a palliative care team into the HF team resulted

Clinical Practice Table 2: Proposed Metrics to Assess Quality of Hospice Care for Heart Failure % of patients with length of stay <1 week

the needs of patients with HF might improve enrollment among this population.14 Particular metrics are needed to assess the quality of hospice care for patients with HF (Table 2).

% of patients able to access inotropes or other IV therapies % of patients with documentation of advance care planning % of patients readmitted to hospital Patient and family satisfaction scores % of cases where ICD and LVAD deactivation had been discussed Training in HF care for hospice staff Family surveys of bereavement services HF = heart failure; LVAD = left ventricular assist device.

in a significant increase in ACP documentation, a decrease in the use of emergency department visits and hospital readmissions, and high patient and family satisfaction.78 St Luke’s Hospice in England partnered with local NHS trusts to improve the management of care for patients with advanced HF. After the adoption of a trigger tool to identify patients who could benefit from palliative care, access to advance care planning and deaths outside the hospital increased.99

Increased Research into Palliative Care and Hospice in Heart Failure Insufficient funding for palliative care research has contributed to an inadequate evidence base for improving symptom management, communication skills, care coordination, and the development of care models.100 Less than 0.2% of the annual budget of the National Institutes of Health in the US has been spent on palliative care research.101,102 After the recognition of palliative care as a medical specialty, there has been an increase in palliative care research, however, a concerted effort to increase the evidence base in this field is needed.103 Most of the funding for palliative care research has been focused on oncology, resulting in limited funding sources for research into palliative care for people with HF.104,105 Chart reviews have indicated that only about 10% of patients with HF receive palliative care consultations and these tend to occur in the last month of life.106 Despite being the leading cause of death in the US, fewer than 19% of Medicare patients who died while receiving hospice care had a cardiac or cardiovascular diagnosis.18,107 Improving the evidence base is essential for the advancement of specialist palliative care and hospice use in HF.

Development of New Models of Hospice Care Innovative home-based programmes for HF management have been shown to reduce hospital readmissions, reduce costs and improve quality of life.108 It follows that hospice care may better meet the needs of patients with HF were hospice services designed with HP needs in mind. Indeed, research suggests that a hospice model tailored to

mbrosy AP, Fonarow GC, Butler J, et al. The global health A and economic burden of hospitalizations for heart failure: lessons learned from hospitalized heart failure registries. J Am Coll Cardiol 2014;63:1123–33. https://doi.org/10.1016/j. jacc.2013.11.053; PMID: 24491689. Cook C, Cole G, Asaria P, et al. The annual global economic burden of heart failure. Int J Cardiol 2014;171:368–76. https:// doi.org/10.1016/j.ijcard.2013.12.028; PMID: 24398230. Journath G, Hammar N, Elofsson S, et al. Time trends in incidence and mortality of acute myocardial infarction, and all-cause mortality following a cardiovascular prevention program in Sweden. PLoS One 2015;10:e0140201. https://doi. org/10.1371/journal.pone.0140201; PMID: 26580968. Roger VL, Weston SA, Redfield MM, et al. Trends in heart failure incidence and survival in a community-based population. JAMA 2004;292:344–50. https://doi.org/10.1001/ jama.292.3.344; PMID: 15265849.

Hospice staff must also be sufficiently trained to manage the needs of patients with HF. In response to the recognition of unmet palliative and end of life care needs among patients with HF, the British Heart Foundation funded HF nurses to receive training in palliative care and advanced communication skills. An evaluation of the programme indicated that patients and their carers reported improved service quality, better care coordination, reduced anxiety and improved ability to cope with illness and death.93 Being willing to forgo life-sustaining treatment does not identify patients with a greater need for hospice services and, therefore, hospice fails a test of fairness.109 In the US, other Medicare benefits are not subject to cost-based restrictions, rather they are determined by a medical need for diagnosis and treatment of an illness or injury and made through an evidence-based process.110 Advocates are pushing for a concurrent care model in which patients may receive supportive care services typically provided by a hospice while continuing to receive curative treatment. Hospice criteria based on patient need and functional status should be established.109,111 Australia uses a payment model for palliative care based on patient characteristics, with reimbursement determined by the patient’s performance status, phase of illness, care setting and age. Similar models are also being explored in England and Switzerland.71 Cardiology should join palliative care in advocating for the creation of new models of end of life care for patients with HF – including features that meet the unique physical and psychosocial needs of those with HF.

Conclusion Underuse of hospice care for people with HF is a significant public health problem. Despite differing social issues and healthcare systems, barriers to hospice use for patients with HF are remarkably similar in high-income countries. The increasing prevalence of HF demands improvements in how we meet the needs of patients nearing the end of life and their carers. With a growing shortage in the palliative care workforce, it is imperative that cardiologists develop comfort and proficiency in ACP and primary palliative care.112,113 Without patientcentred and disease-specific modifications, it is unlikely that hospice use will increase among patients with HF. Improving communication and developing trust must be priorities in improving end of life care for all. Innovative programmes and models of care may extend the reach of palliative and hospice care in institutions and in more remote geographic areas. Despite the challenges, there are actions we can take to increase hospice use among patients with HF.

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Low socioeconomic status is associated with more aggressive end-of-life care for workingage terminal cancer patients. Oncologist 2014;19:1241–8. https://doi.org/10.1634/theoncologist.2014-0152; PMID: 25342317. 69. Barclay JS, Kuchibhatla M, Tulsky JA, Johnson KS. Association of hospice patients’ income and care level with place of death. JAMA Intern Med 2013;173:450–6. https://doi. org/10.1001/jamainternmed.2013.2773; PMID: 23420383. 70. Hardy D, Chan W, Liu CC, et al. Racial disparities in length of stay in hospice care by tumor stage in a large elderly cohort with non-small cell lung cancer. Palliat Med 2012; 26:61–71. https://doi.org/10.1177/0269216311407693; PMID: 21606129. 71. Groeneveld EI, Cassel JB, Bausewein C, et al. Funding models in palliative care: lessons from international experience. Palliat Med 2017;31:296–305. https://doi. org/10.1177/0269216316689015; PMID: 28156188. 72. Sleeman KE, Davies JM, Verne J, et al. The changing demographics of inpatient hospice death: Population-based cross-sectional study in England, 1993–2012. Palliat Med 2016;30:45–53. https://doi.org/10.1177/0269216315585064; PMID: 25991729. 73. Teno JM, Plotzke M, Christian T, Gozalo P. Examining variation in hospice visits by professional staff in the last 2 days of life. JAMA Intern Med 2016;176:364–70. https://doi.org/10.1001/ jamainternmed.2015.7479; PMID: 26857275. 74. Lueckmann SL, Behmann M, Bisson S, Schneider N. ‘Good idea but not feasible’ – the views of decision makers and stakeholders towards strategies for better palliative care in Germany: a representative survey. BMC Palliat Care 2009;8:10. https://doi.org/10.1186/1472-684X-8-10; PMID: 19622177. 75. Jessup M, Abraham WT, Casey DE, et al. 2009 Focused update: ACCF/AHA Guidelines for the Diagnosis and Management of Heart Failure in Adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines: developed in collaboration with the International Society for Heart and Lung Transplantation. Circulation 2009;119:1977–2016. https://doi.org/10.1161/ CIRCULATIONAHA.109.192064; PMID: 19324967. 76. Hunt SA, Abraham WT, Chin MH, et al. 2009 Focused update incorporated into the ACC/AHA 2005 Guidelines for the Diagnosis and Management of Heart Failure in Adults: a report of the American College of Cardiology Foundation/ American Heart Association Task Force on Practice Guidelines Developed in Collaboration With the International Society for Heart and Lung Transplantation. J Am Coll Cardiol 2009;53:e1– e90. https://doi.org/10.1016/j.jacc.2008.11.013; PMID: 19358937. 77. Kuragaichi T, Kurozumi Y, Ohishi S, et al. Nationwide survey of palliative care for patients with heart failure in Japan. Circ J 2018;82:1336–43. https://doi.org/10.1253/circj.CJ-17-1305; PMID: 29526984. 78. Lewin WH, Cheung W, Horvath AN, et al. Supportive cardiology: moving palliative care upstream for patients living with advanced heart failure. J Palliat Med 2017;20:1112–9. https://doi.org/10.1089/jpm.2016.0317; PMID: 28472598. 79. Wachterman MW, Pilver C, Smith D, et al. Quality of end-oflife care provided to patients with different serious illnesses. JAMA Intern Med 2016;176:1095–102. https://doi.org/10.1001/ jamainternmed.2016.1200; PMID: 27367547. 80. Thomas JM, O’Leary JR, Fried TR. Understanding their options: determinants of hospice discussion for older persons with advanced illness. J Gen Intern Med 2009;24:923-8. https://doi. org/10.1007/s11606-009-1030-9; PMID: 19506972.

Clinical Practice 81. W orld Health Organization. Strengthening of palliative care as a component of integrated treatment throughout the life course. J Pain Palliat Care Pharmacother 2014;28:130–4. https://doi. org/10.3109/15360288.2014.911801; PMID: 24779434. 82. Gelfman LP, Kalman J, Goldstein NE. Engaging heart failure clinicians to increase palliative care referrals: overcoming barriers, improving techniques. J Palliat Med 2014;17:753–60. https://doi.org/10.1089/jpm.2013.0675; PMID: 24901674. 83. Warraich HJ, Allen LA, Mukamal KJ, et al. Accuracy of physician prognosis in heart failure and lung cancer: Comparison between physician estimates and model predicted survival. Palliat Med 2016;30:684–9. https://doi. org/10.1177/0269216315626048; PMID: 26769732. 84. Waller A, Girgis A, Davidson PM, et al. Facilitating needsbased support and palliative care for people with chronic heart failure: preliminary evidence for the acceptability, interrater reliability, and validity of a needs assessment tool. J Pain Symptom Manage 2013;45:912–25. https://doi.org/10.1016/j. jpainsymman.2012.05.009; PMID: 23017612. 85. Janssen DJ, Boyne J, Currow DC, et al. Timely recognition of palliative care needs of patients with advanced chronic heart failure: a pilot study of a Dutch translation of the Needs Assessment Tool: Progressive Disease – Heart Failure (NAT:PD-HF). Eur J Cardiovasc Nurs 2019:1474515119831510. https://doi.org/10.1177/1474515119831510; PMID: 30760021. 86. Nicholas LH, Langa KM, Iwashyna TJ, Weir DR. Regional variation in the association between advance directives and end-of-life Medicare expenditures. JAMA 2011;306:1447–53. https://doi.org/10.1001/jama.2011.1410; PMID: 21972306. 87. Dunlay SM, Foxen JL, Cole T, et al. A survey of clinician attitudes and self-reported practices regarding end-of-life care in heart failure. Palliat Med 2015;29:260–7. https://doi. org/10.1177/0269216314556565; PMID: 25488909. 88. Kramer DB, Reynolds MR, Normand SL, et al. Hospice use following implantable cardioverter-defibrillator implantation in older patients: results from the national cardiovascular data registry. Circulation 2016;133:2030–7. https://doi.org/10.1161/ CIRCULATIONAHA.115.020677; PMID: 27016104. 89. Goldstein N, Carlson M, Livote E, Kutner JS. Brief communication: management of implantable cardioverterdefibrillators in hospice: A nationwide survey. Ann Intern Med 2010;152:296–9. https://doi.org/10.7326/0003-4819-152-5201003020-00007; PMID: 20194235. 90. Cheang MH, Rose G, Cheung CC, Thomas M. Current challenges in palliative care provision for heart failure in the UK: a survey on the perspectives of palliative care professionals. Open Heart 2015;2:e000188; https://doi. org/10.1136/openhrt-2014-000188; PMID: 25628893.

91. K öhnlein T, Welte T, Tan LB, Elliott MW. Central sleep apnoea syndrome in patients with chronic heart disease: a critical review of the current literature. Thorax 2002;57:547–54. https://doi.org/10.1136/thorax.57.6.547; PMID: 12037232. 92. Warraich HJ, Taylor DH Jr, Casarett DJ, et al. Hospice care for heart failure: challenges faced by hospice staff in a predominantly rural setting. J Palliat Med 2019;21:7–8. https:// doi.org/10.1089/jpm.2018.0454; PMID: 30633700. 93. Rogers A. Role of the British Heart Foundation heart failure palliative care specialist nurse: A retrospective evaluation. London: British Heart Foundation, 2010. Available at: https://www.bhf.org. uk/informationsupport/publications/about-bhf/z812-roleof-the-bhf-heart-failure-palliative-care-specialist-nurse---aretrospective-evaluation (accessed 3 April 2019). 94. Browne S, Macdonald S, May CR, et al. Patient, carer and professional perspectives on barriers and facilitators to quality care in advanced heart failure. PLoS One 2014;9:e93288. https://doi.org/10.1371/journal.pone.0093288; PMID: 24676421. 95. Goodlin SJ, Quill TE, Arnold RM. Communication and decisionmaking about prognosis in heart failure care. J Card Fail 2008;14:106–13. https://doi.org/10.1016/j.cardfail.2007.10.022; PMID: 18325456. 96. Warraich HJ, Rogers JG, Dunlay SM, et al. Top ten tips for palliative care clinicians caring for heart failure patients. J Palliat Med 2018;21:1646–50. https://doi.org/10.1089/ jpm.2018.0453; PMID: 30311835. 97. Quill TE, Abernethy AP. Generalist plus specialist palliative care – creating a more sustainable model. N Engl J Med 2013;368:1173–5. https://doi.org/10.1056/NEJMp1215620; PMID: 23465068. 98. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC Guidelines for the Diagnosis and Treatment of Acute and Chronic Heart Failure. Rev Esp Cardiol (Engl Ed) 2016;69:1167. https://doi. org/10.1016/j.rec.2016.11.005; PMID: 27894487. 99. London: Hospice UK, 2017. Available at https://www. hospiceuk.org/docs/default-source/What-We-Offer/CareSupport-Programmes/heart-failure-and-hospice-care_web. pdf?sfvrsn=2 (accessed 4 April 2019). 100. Meier DE, Back AL, Berman A, et al. A national strategy for palliative care. Health Aff (Millwood) 2017;36:1265–73. https://doi. org/10.1377/hlthaff.2017.0164; PMID: 28679814. 101. Gelfman LP, Morrison RS. Research funding for palliative medicine. J Palliat Med 2008;11:36–43. https://doi.org/10.1089/ jpm.2006.0231; PMID: 18370891. 102. Gelfman LP, Du Q, Morrison RS. An update: NIH research funding for palliative medicine 2006 to 2010. J Palliat Med

2013;16:125–9. https://doi.org/10.1089/jpm.2012.0427; PMID: 23336358. 103. Abernethy AP, Aziz NM, Basch E, et al. A strategy to advance the evidence base in palliative medicine: formation of a palliative care research cooperative group. J Palliat Med 2010;13:1407–13. https://doi.org/10.1089/jpm.2010.0261; PMID: 21105763. 104. Teuteberg J, WG T. Palliative Care for Patients with Heart Failure. 2016. Available at: https://www.acc.org/latest-in-cardiology/ articles/2016/02/11/08/02/palliative-care-for-patients-withheart-failure. (accessed 3 April 2019) 105. Xie K, Gelfman L, Horton JR, Goldstein NE. State of research on palliative care in heart failure as evidenced by published literature, conference proceedings, and NIH funding. J Card Fail 2017;23:197–200. https://doi.org/10.1016/j. cardfail.2016.10.013; PMID: 27989871. 106. Bakitas M, Macmartin M, Trzepkowski K, et al. Palliative care consultations for heart failure patients: how many, when, and why? J Card Fail 2013;19:193–201. https://doi.org/10.1016/j. cardfail.2013.01.011; PMID: 23482081. 107. Heron M. Deaths: Leading Causes for 2016. Hyattsville, MD: National Center for Health Statistics, 2018. 108. Rich MW, Beckham V, Wittenberg C, et al. A multidisciplinary intervention to prevent the readmission of elderly patients with congestive heart failure. N Engl J Med 1995;333:1190–5. https://doi.org/10.1056/NEJM199511023331806; PMID: 7565975. 109. Fishman J, O’Dwyer P, Lu HL, et al. Race, treatment preferences, and hospice enrollment: eligibility criteria may exclude patients with the greatest needs for care. Cancer 2009;115:689–97. https://doi.org/10.1002/cncr.24046; PMID: 19107761. 110. Centers for Medicare and Medicaid Services. Medicare Coverage Determination Process. Available at: https://www.cms. gov/Medicare/Coverage/DeterminationProcess/index.html (accessed 3 April 2019) 111. US Centers for Medicare & Medicaid Services. Medicare Care Choices Model Enables Concurrent Palliative and Curative Care. J Pain Palliat Care Pharmacother 2015;29:401–403. https:// doi.org/10.3109/15360288.2015.1103358; PMID: 26654414. 112. Kamal AH, Bull JH, Swetz KM, et al. Future of the palliative care workforce: preview to an impending crisis. Am J Med 2017;130:113–4. https://doi.org/10.1016/j. amjmed.2016.08.046; PMID: 27687068. 113. Institute of Medicine. Dying in America: Improving Quality and Honoring Individual Preferences Near the End of Life. Washington, DC: National Academies Press, 2015. https://doi. org/10.17226/18748.

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Co-morbidities

Aortic Stenosis and Heart Failure: Disease Ascertainment and Statistical Considerations for Clinical Trials Ernest Spitzer, 1,2 Rebecca T Hahn, 3,4 Philippe Pibarot, 5 Ton de Vries, 2 Jeroen J Bax, 6 Martin B Leon 3,4 and Nicolas M Van Mieghem 1 1. Thoraxcenter, Erasmus University Medical Center, Rotterdam, the Netherlands; 2. Cardialysis, Clinical Trial Management and Core Laboratories, Rotterdam, the Netherlands; 3. New York Presbyterian Hospital/Columbia University Medical Center, New York, NY, US; 4. Cardiovascular Research Foundation, New York, NY, US; 5. Quebec Heart and Lung Institute, Laval University, Quebec, Canada; 6. Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands

Abstract Aortic stenosis is a progressive disease that develops over decades, and once symptomatic and untreated, is associated with poor survival. Transcatheter aortic valve replacement has evolved significantly in the past decade and has expanded its indication from surgically inoperable and high-risk patients to patients with intermediate risk. Assessment of heart failure-related outcomes include the use of functional assessments, disease-specific quality of life surveys and standardised ascertainment of events, such as hospitalisations. Multiple statistical approaches are currently being tested to account for recurrent events such as hospitalisations for heart failure or to combine binary and continuous outcomes, both intended to assess the holistic burden of the disease, as opposed to the traditional analysis of time to first event.

Keywords Aortic stenosis, heart failure, rehospitalisation, quality of life, clinical endpoints, randomised controlled trials, statistical analysis Disclosure: RTH is the Core Laboratories Director for multiple transcatheter aortic valve trials for which she receives no direct compensation from the industry. PP received funding from Edwards Lifesciences, Medtronic, V-Wave, and Cardiac Phoenix for echocardiography laboratory analyses with no personal compensation. MBL is a non-paid member of the advisory board of Edwards Lifesciences. NVM has received institutional grants from Edwards Lifesciences, Medtronic, Boston Scientific and Abbott. Received: 27 November 2018 Accepted: 17 March 2019 Citation: Cardiac Failure Review 2019;5(2):99–105. DOI: https://doi.org/10.15420/cfr.2018.41.2 Correspondence: Ernest Spitzer, Thoraxcenter, Erasmus University Medical Center, ‘s-Gravendijkwal 230, 3015 CE, Rotterdam, the Netherlands. E: ernest.spitzer@gmail.com Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

Symptomatic severe aortic stenosis (AS) is the most common indication for valvular interventions.1 AS is a degenerative and progressive disease that characteristically remains asymptomatic for decades but once symptoms occur, survival is severely compromised. Historical data have shown that the time from the onset of symptoms to death is about 2 years in patients who develop heart failure (HF) symptoms, 3 years in those who present with a syncope and 5 years in those presenting with angina.2 The Long-term follow-up of the Placement of Aortic Transcatheter Valves (PARTNER 1B) trial showed that two-thirds of inoperable patients who followed standard treatment did not survive beyond 2 years, while transcatheter aortic valve replacement (TAVR) halved mortality.3 Stages of cardiac damage in patients with severe AS have recently been defined (Figure 1).4 Stage 1 includes increased left ventricular mass, increased left ventricular filling pressures and systolic dysfunction defined as left ventricular ejection fraction (LVEF) <50%. Further stages relate to damage of the left atrium or mitral valve (stage 2), pulmonary vasculature or tricuspid valve (stage 3) and right ventricular damage (stage 4). Each stage is associated with an increased risk of mortality within 1 year, ranging from 4% at stage 0 (no damage) up to 25% at stage 4. Stage 1 patients, when compared with AS patients

without cardiac damage, show an increased mortality (9% versus 4%), hospitalisation rate (17% versus 7%) and stroke rate (6% versus 2%). Recent studies have called into question the traditional 50% LVEF cutoff, suggesting that in patients with AS, an ejection fraction of ≤60% may precede the onset of symptoms and may also predict progression of the disease.5 Thus, evaluation of the left ventricular systolic function is critical in the follow-up of patients with asymptomatic AS and early detection of dysfunction prompts the need for accelerated aortic valve replacement.1 Moreover, ascertainment of history of congestive HF may better characterise the prognosis of patients who are having a planned intervention. The impact of chronic HF and systolic dysfunction on treatment selection – TAVR versus surgical aortic valve replacement (SAVR) – merits further research.1 In this review, we summarise the prevalence of HF in patients included in clinical trials comparing TAVR with SAVR or medical treatment, as well as tools for assessment of the functional status, quality of life and clinical events during follow-up. We also discuss recent recommendations for broadening the definition of HF-related clinical events as well as statistical methods that not only increase the power of comparisons, but also may better capture the burden of the disease and effects of experimental therapies in the setting of clinical trials.

Access at: www.CFRjournal.com

Co-morbidities Figure 1: Stages of Cardiac Damage In Patients With Aortic Valve Stenosis

Ascertainment of Heart Failure-related Clinical Events at Follow-up All-cause and Cardiovascular Mortality

Stages of cardiac damage in patients with aortic valve stenosis Stage 4 Frequency: 8.7%

Right ventricular damage (≥moderate dysfunction ) Events at 1 year: death 24.5%; RH 26.7%; stroke 8.3%

Pulmonary vasculature and tricuspid damage Stage 3 (severe hypertension, ≥moderate regurgitation) Frequency: 24.9% Events at 1 year: death 21.3%; RH 21.1%; stroke 6.9% Stage 2 Frequency: 50.8% Stage 1 Frequency: 12.8% Stage 0 Frequency: 2.8%

Left atrial and mitral damage (increased volume, ≥moderate Events at 1 year: death 14.4%; RH 16.4%; stroke 8.8%

Left ventricular damage (increased mass, increased filling pressures, reduced ejection fraction) Events at 1 year: death 9.2%; RH 17%; stroke 6.4%

No cardiac damage Events at 1 year: death 4.4%; RH 6.7%; stroke 2.1%

Frequency of each stage and observed rates of events at 1 year are based on data from the PARTNER 2A and 2B trials.22,23 RH = rehospitalisation.

Cardiac imaging to assess LVEF, longitudinal strain, mitral regurgitation and hemodynamic parameters, such as pulmonary artery systolic pressure, as well as biomarkers, such as brain natriuretic peptide (BNP) and N-terminal pro-BNP (NT-proBNP), have been associated with HF symptoms and worsening symptoms, but detailed discussion of these is beyond the scope of this review.6

Prevalence of Heart Failure and Related Comorbidities HF is multifactorial in patients with severe AS and can be a consequence of the increased afterload and myocardial remodeling, with the contributory effect of cardiac damage characteristics of stages 2–4, or secondary to ischaemia.4 Characterising the aetiology requires interrogation and assessment of previous MI or coronary artery disease, status of coronary artery lesions (i.e. existence of lesions requiring intervention), atrial fibrillation and pulmonary hypertension. Defining prior congestive HF is not standardised and may range from ambulatory symptoms prior to hospitalisations for HF. In Table 1 we summarise the baseline characteristics of seven clinical trials, providing data for both the TAVR and control groups when available.7–13 Prior MI ranged from 5% in a study with an all-comers design to 31% in an extreme risk cohort;14 coronary artery disease affected two-thirds of patients and atrial fibrillation one-third.7–13 Remarkably, previous HF was captured only in three of the seven studies, and was highly prevalent (≥95%) in patients with intermediate, high or extreme risk.7–12 LVEF was reported in four of seven studies and mean values were always above the cut-off value accepted for normality (>50%). An ejection fraction <50% was seen in ~30–50% of patients with severe AS.7–9,12 The New York Heart Association (NYHA) functional class at baseline was used in all studies and reflected accurately the risk of the analysed cohorts. In an all-comers design,13 approximately half of the patients presented with NYHA class I or II (Table 1), while this number was less than 10% in cohorts with high or extreme risk.7,8,12 Likewise, NYHA class IV was present in up to half of patients at high surgical risk, while it was observed in <3% in the all-comers cohort.12,13 These findings underscore the value of NYHA class for characterising the baseline functional status of patients with severe AS. Although the reproducibility of this assessment has been criticised, its simplicity and availability make it a useful functional assessment.15 It is noteworthy that prior congestive HF should be better defined and standardised and consistently captured in cardiovascular trials.

100

TAVR has revolutionised the management of severe AS. This is largely due to continued improvement in transcatheter heart valves and implantation techniques. Efforts to expand its indication have targeted populations with progressively lower surgical risk.7–13 These combined factors resulted in a consistent decrease in overall rates of all-cause death at 1 year from 31% (n=179) in the inoperable cohort of the PARTNER IB trial treated with TAVR,8 to 7% (n=864) in the Surgical Replacement and Transcatheter Aortic Valve Implantation (SURTAVI) trial targeting patients with an intermediate risk, and 5% (n=145) in the all-comers Nordic Aortic Valve Intervention (NOTION) trial (Table 2).11,13 In cardiovascular research, all-cause mortality is considered the most robust and unbiased clinical endpoint (Figure 2).16 Nevertheless, it may lack specificity, and thus differentiation between cardiovascular and non-cardiovascular death is compulsory. Given the complexity in classifying events as cardiovascular or non-cardiovascular, the involvement of an independent clinical events committee is considered a quality marker when interpreting trial outcomes.16 It has been suggested that using cardiovascular death in composite primary endpoints instead of all-cause mortality, for example cardiovascular death and hospitalisations for HF, reduces statistical noise generated by non-cardiovascular fatal events that are generally not influenced by targeted cardiovascular interventions.17

Hospitalisation due to Heart Failure Although rehospitalisation due to HF is considered a less robust endpoint in clinical trials due to the lack of implementation of standardised definitions, it remains the most important outcome from patient prognosis and health economic perspectives. In three of the seven trials included in this review it was not reported, and definitions slightly varied when it was available.7,10,13 Frequently, it is difficult to distinguish between a hospitalisation due to aortic valve disease and/or complications of the valve procedure versus a hospitalisation due to HF. These are not always mutually exclusive and strict criteria should be applied to be able to adjudicate and report both. A standardised definition of hospitalisation due to HF is needed if meaningful comparison of rates among cardiovascular trials are to be made.16 The Standardised Data Collection for Cardiovascular Trials Initiative (SCTI), in collaboration with the Food and Drug Administration (FDA), the American College of Cardiology and the American Heart Association recommend a standardised definition for HF events, which include urgent, unscheduled outpatient office/ practice, emergency department visits and hospitalisations due to HF.18 HF hospitalisation occurs when a patient is admitted to the hospital with a primary diagnosis of HF, the length of stay is at least 24 hours (or extends over a calendar date), the patient exhibits at least one new or worsening symptom of HF, has objective evidence of new or worsening HF (at least two signs or one sign and one laboratory finding), and receives initiation or intensification of treatment specifically for HF. HF signs and symptoms, relevant changes in therapy, as well as laboratory findings – BNP or NT-proBNP, radiological evidence, noninvasive cardiac imaging, right heart catheterisation – are carefully defined in the SCTI document. The almost simultaneous publication of the Mitral Valve Academic Research Consortium consensus manuscript defines what qualifies as a hospitalisation (≥24 hour stay) with criteria for HF hospitalisation or rehospitalisation requiring signs, symptoms and/or laboratory evidence of worsening HF and administration of IV or mechanical HF therapies.19 They further sub-classify HF hospitalisation into primary (cardiac-related) and secondary (non-cardiac related).

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Severe Aortic Stenosis and Heart Failure Table 1: Baseline Characteristics in Patients Included in Clinical Trials Investigating Transcatheter Aortic Valve Replacement in Severe Aortic Stenosis Clinical Trial

PARTNER IB (Inoperable)8

CoreValve (Extreme Risk)10,14

PARTNER IA (High Risk)12

CoreValve (High Risk)7,14

PARTNER IIA (Intermediate Risk)9

SURTAVI (Intermediate Risk)11

NOTION (All-comers)13

TAVR

Standard therapy

TAVR

SAVR

TAVR

SAVR

TAVR

SAVR

TAVR

SAVR

TAVR

SAVR

Patients analysed

179

487

348

351

394

401

1,011

1,021

864

796

145

135

Age in years

Women (%)

Prior MI (%)

Prior PCI (%)

Prior CABG (%)

Coronary artery disease (%)

AF (%)

Significant mitral regurgitation (%)

Pulmonary hypertension (%)

Congestive heart failure (%)

LVEF (%)

54 ±13

51 ±14

55 ±14

53 ±14

53 ±13

56 ±11

55 ±12

LVEF <50% (%)

NYHA class*

I (%)

0.0

4.9

2.2

II (%)

7.7

5.8

8.2

5.6

5.4

14.2

13.2

22.2

24.1

39.8

41.8

46.5

52.2

III (%)

48.7

48.6

64.0

40.9

42.8

65.5

69.1

60.2

57.4

54.6

51.7

46.5

42.6

IV (%)

43.6

45.6

27.8

53.4

51.8

20.3

17.7

17.6

18.5

5.6

6.5

2.1

3.0

*Numbers were derived from frequency figures when numerical data were not available. CABG = coronary artery bypass grafting; LVEF = left ventricular ejection fraction; NYHA = New York Heart Association; PCI = percutaneous coronary intervention; TAVR = transcatheter aortic valve replacement; SAVR = surgical aortic valve replacement.

Table 2: Heart Failure-Related Events up to 1 Year of Follow-up in Clinical Trials Investigating Transcatheter Aortic Valve Replacement in Severe Aortic Stenosis PARTNER IB (Inoperable)8

CoreValve (Extreme Risk)10,14

PARTNER IA (High Risk)12

CoreValve (High Risk)7,14

PARTNER IIA (Intermediate Risk)9

SURTAVI (Intermediate Risk)11

NOTION (All-comers)13

TAVR

SAVR

TAVR

SAVR

Standard therapy

SAVR

Patients analysed

179

487

348

351

394

401

1011

1021

864

796

145

135

All-cause death

30.7

49.7

24.3

24.2

26.8

13.9

18.7

12.3

12.9

6.7

6.8

4.9

7.5

Cardiovascular death

19.6

41.9

18.3

14.3

7.1*

8.1*

4.8

5.5

4.3

7.5

Rehospitalisation

22.3

44.1

18.2

15.5

14.8

14.7

8.5

7.6

Change in % LVEF

0.0

−12.0

2.8

4.0

3.4

−0.3

2.1

NYHA class change† I (%)

24.25

1.13

42.75

36.12

33.88

48.00

44.00

55.09

58.33

70.70

68.20

62.40

79.40

II (%)

17.08

11.13

15.22

21.98

24.31

14.00

10.00

3.24

−2.31

−15.80

−14.90

−18.00

−37.60

III (%)

−34.34

−29.72

−58.70

−30.69

−35.78

−65.00

−61.00

−54.63

−52.31

−50.20

−49.10

−43.10

−38.80

IV (%)

−41.23

−38.96

−25.72

−51.98

−50.00

−13.00

−14.00

−16.67

−17.59

−4.50

−4.20

−1.40

−3.00

Death or missing at 1 year† (%)

34.25

56.42

26.45

24.57

27.59

16.00

22.00

12.96

13.89

7.00

6.80

4.90

7.50

KCCQ change at 1 year

27 (24–31)‡

29 (24–33)‡§

27 (22–32)‡

23 ±26

22 ±27

22 (20–24)‡§

22 (20–24)‡

21 ±22

*Only cardiac causes were included. †Numbers were derived from frequency figures when numerical data were not available. ‡Mean value (95% CI). §Numbers reflect the transfemoral cohort. KCCQ = Kansas City Cardiomyopathy Questionnaire; LVEF = left ventricular ejection fraction; NYHA = New York Heart Association; SAVR = surgical aortic valve replacement; TAVR = transcatheter aortic valve replacement.

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Co-morbidities Figure 2: Hierarchy of Clinical Trial Endpoints Related to Aortic Stenosis and Heart Failure

Aortic stenosis and heart failure related clinical trial endpoints All-cause death Cardiovascular death Cardiovascular hospitalisation Hospitalisation due to heart failure Worsening without hospitalisation

Most robust and unbiased clinical endpoint Increased specificity. Requires consistent approach for classification Should be classified as planned and unplanned. Requires additional standardisation Definitions vary among clinical trials. SCTI definitions are comprehensive and their use will increase consistency Outpatient intensification of therapy, emergency department visits

Kansas City Cardiomyopathy Questionnaire, Minnesota Living with Heart Failure Questionnaire, New York Heart Association Class EURQoL (EQ-5D), Health Utilities Index (HUI), Duke Generic-health Activity Status Index (DASI), 12- or 36-item short status measures form questionnaires (SF-12 or SF-36) Considered surrogate outcomes, they include left ventricular Imaging and volumes and function, haemodynamic parameters, biomarkers natriuretic peptides, such as BNP or NT-proBNP Disease-specific health measures

CEC = clinical events committee; SCTI = Standardized data Collection for Clinical Trials Initiative.

A recent sub-analysis of the Prospective Comparison of ARNI with ACEI to Determine the Impact of Global Mortality and Morbidity in Heart Failure (PARADIGM-HF) trial, a randomised, double-blind comparison of sacubitril/valsartan with enalapril in 8,399 patients with chronic HF, showed that patients hospitalised due to HF had a significantly increased risk of all-cause death (HR 5.0; 95% CI [4.4–5.7]) throughout the duration of the trial (27 months) in an adjusted analysis for randomised treatment, region and baseline covariates, when analysing hospitalisation for HF as the only event experienced as a time-updated covariate. 20 When this analysis was carried out for emergency department visits due to HF (without subsequent hospitalisation), the risk of all-cause death was three times higher than in patients without an event (HR 2.9; 95% CI [1.9–4.6]). The intensification of HF therapy as an outpatient was also evaluated, since many episodes of worsening HF are treated in the community with an increase in oral pharmacological therapy or the use of short-term IV therapy.20 When analysing this endpoint as the only event experienced as a time-updated covariate, the authors observed an increased risk of death (HR 4.2; 95% CI [3.3–5.3]), almost equivalent to that observed in patients hospitalised due to HF. These findings did not only clarify the prognostic role of HF events not linked to hospitalisation, but further showed that adding intensification of HF therapy and ED visits due to HF, the frequency of HF-related events doubled, suggesting that an extended composite endpoint would increase statistical power without compromising specificity, which is especially appealing for event-driven clinical trials. These data further support the implementation of SCTI-defined HF events.18

Health Status Measures The impact of transcatheter therapies for severe AS on functional capacity has been largely assessed by changes in NYHA class and, less frequently, by the use of validated disease-specific questionnaires such as the Kansas City Cardiomyopathy Questionnaire (KCCQ).7–13 When interpreting comparisons of cross-sectional measures, it is important to take into account that generally subjects will be not all be present for any specific follow-up time point, due to death,

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a missed appointment or patients lost to follow-up. Consequently, these comparisons will unequivocally exclude patients who are the most ill. Aortic valve replacement has significantly and consistently increased the number of patients classified as NYHA class I, ranging from a 24% increase relative to baseline in inoperable patients, to an 80% increase in all-comer populations at one-year follow-up.8,13 Likewise, the frequency of NYHA class III and IV has been reduced up to 65% and 50% respectively in high-risk cohorts (Table 2).7,12 The KCCQ is a 23-item, self-administered instrument that quantifies physical function, symptoms (frequency, severity and recent changes), social function, self-efficacy and knowledge and quality of life. The instrument provides a score from 0 to 100. It has shown an excellent correlation with NYHA class and each quartile is reflective of an increased risk of mortality in patients with HF. It has been validated for the assessment of prognosis and effects of therapies in severe AS.21 A recent sub-analysis of the PARTNER 2 trial evaluated changes in KCCQ at 1 month, 1 year and 2 years among patients at intermediate risk randomised to TAVR or SAVR.22 For this analysis the authors categorised changes in KCCQ as follows: death, worse (reduction from baseline >5 points), no change (change between −5 and <5 points), mildly improved (increase between 5 and <10 points), moderately improved (increase between 10 and <20 points), and substantially improved (increase ≥20 points). Overall, there was a similar increase in KCCQ at 1 year in the transfemoral TAVR group (22.1 points; 20.4–23.9) and in the SAVR group (22.1 points; 20.1–24.1), albeit an earlier benefit was observed in patients undergoing transfemoral TAVR. Moreover, the frequency of moderate or substantial improvement (≥10 points in KCCQ) was consistent among groups (71.1% in the TAVR group and 68% in the SAVR group). Similar findings have been reported in the trials included in this review.11,14,21–23 Other instruments of proven value for the assessment of health status are the disease-specific Minnesota Living with Heart Failure Questionnaire and generic health status measures such as the EuroQoL, Health Utilities Index, Duke Activity Status Index, 12- or 36-item short-form questionnaires (SF-12 or SF-36).15,24,25

Statistical Analysis of Heart Failure Endpoints Clinical primary endpoints in HF and AS trials are customarily analysed using a Kaplan–Meier analysis using the log-rank test and the treatment effect calculated with the Cox proportional hazards regression using one of several tests, such as the Wald test. These methods are well established and used in studies with regulatory approval studies.26 Primary endpoints in HF trials include, for example, all-cause death; all-cause death and hospitalisations for HF; and more recently cardiovascular death and hospitalisations for HF. Likewise, AS trials have used all-cause death or all-cause death and stroke. The time-to-first-event analysis allows the most intuitive presentation of results, but does not fully capture the burden of recurrent events, such as hospitalisations for HF, an issue that becomes more relevant when investigating patients with AS and impaired systolic function, as envisioned in the ongoing Transcatheter Aortic Valve Replacement to UNload the Left Ventricle in Patients With ADvanced Heart Failure (TAVR UNLOAD) trial.27 The high frequency of recurrent HF events is denoted in trials such as the PARADIGM HF, in which one-third of patients who were hospitalised once during follow-up were hospitalised at least for a second time throughout the duration of the trial, and one tenth were hospitalised three or more times.28 Similar distribution of recurrent events have been reported in drug and device intervention trials.29–33 Patients with more unplanned

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Severe Aortic Stenosis and Heart Failure Table 3: Statistical Methods for the Analysis of Recurrent Events used in Heart Failure Research Statistical Methods for the Analysis of Recurrent Events Used in Heart Failure Research Joint frailty model (JFM) (1998) Based on total time scale; semi-parametric or parametric; accounts for the dependence between recurrent events and death through a patientspecific frailty term; able to 1:1 model time-varying covariates; assumes a constant event rate and treatment effect over time (e.g. NCT01626079)

Time-to-event models These methods are extensions of the Cox proportional hazards model; preferred when censoring exists; all models except the join frailty model consider all events as a singleevent process; most are supported by standard statistical software.

Lin, Wei, Ying and Yang (LWYY) model (2000) Based on gap time; stratified Cox-based; recurrent events are assumed to be independent; semiparametric; terminal events are assumed to be recurrent events; does not incorporate competing risks or time-varying covariates into the analysis (e.g. NCT01920711) Prentice–Williams–Peterson (PWP) model (1981) Based on gap times or total time scale; stratified Cox-based; semi-parametric; terminal events are assumed to be recurrent events; incorporates the order of the events; conditional model; recurrent events risk can be influenced by previous events

Count models Compare counts of events in a given time; not preferred when the event rate is not constant over time or when there are timevarying effects

Cumulative incidence methods

Poisson regression (1837)* Assumes that the underlying event rate is the same in all subjects and that event counts follow the Poisson distribution (the mean and variance are equal); recurrent events are assumed to be independent; does not incorporate competing risk. Negative binomial regression (1714)* Assumes an association between recurrent events through a random effect term; does not incorporate competing risks; assumes a constant event rate and treatment effect over time; allows to sdjust the variance independently from the mean (e.g. NCT00531661) Gosh and Lin method (2001) Terminal events are handled as informative censoring (competing risk); non-parametric and semi-parametric; models the mean frequency function Nelson–Aelen estimator (1969) Terminal events are handled as independent censoring

Andersen-Gill (AG) model (1982) Based on gap times; semi-paramedic; recurrent events are assumed to be independent; terminal events are assumed to be recurrent events; does not incorporate: competing risks; can include time-varying covariates; robust variance (e.g. NCT0053166)

Generalised pairwise comparison methods

Wei, Lin and Weissfe/d (WLW) model (1989) Based on total time scale; stratified Cox-based; semi-parametric; recurrent events are assumed to be independent; unconditional marginal model; each event has its own stratum; ignores the order of the events; does not incorporate competing risks

Non-parametric ranked tests applied on composite endpoints allowing continuous, ordinal and censored events

O’Brien method (non-hierarchical) (1984) Compares multiple outcomes based on an overall rank for each subject and using a rank-sum or ANOVA test Finkelstein–Schoenfeld method (hierarchical) (1999) Compares binary and continuous outcomes in a hierarchy; may include functional assessments or imaging 1 parameters (e.g. NCT02661451; NCT01768702) Buyse method (hierarchical) (2010) Extension of the Wilcoxon–Mann–Whitney test Matched/unmatched Pocock method (Win ratio) (2012) For every pair, a ‘winner’ or a ‘loser’ is defined. The win ratio is defined by winners/losers (e.g. NCT00530894)

*Year of introduction of the distributions; all other years refer for first report for each method/model.

hospitalisations exhibit a worse quality of life and survival, thus, being able to analyse recurrent hospitalisations not only better characterises the disease but also increases statistical power to detect differences in treatment effects. Since the early 1980s, several statistical approaches to account for multiple hospitalisations have been introduced (Table 3), and recently a shift towards these more complex methods has been observed in trials enrolling patients with HF, aiming for efficiency and robustness.28,34–36 For instance, in the groundbreaking Cardiovascular Outcomes Assessment of the MitraClip Percutaneous Therapy for Heart Failure Patients with Functional Mitral Regurgitation (COAPT) trial, the chosen primary effectiveness endpoint was all hospitalisations for HF within 24 months of follow-up, including recurrent events in patients with more than one event, using the joint frailty model to account for correlated events and the competing risk of death.37 This is one of the available time-to-event approaches, which include the Wei, Lin and Weissfeld (WLW) method; the Lin, Wei, Ying and Yang (LWYY) model; the Prentice–Williams–Peterson model; and the Andersen–Gill

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model.28,38 The choice for the most appropriate statistical approach relates to: • The distribution of timing of subsequent events – HF rehospitalisations may not occur after similar intervals but in clusters where some patients will present multiple adjacent episodes and others no recurrences. • The within-patient correlation of subsequent events – it is known that hospitalisations beget more hospitalisations and worse prognosis, thus methods assuming independence of recurrent events may not be preferred for analysis of HF events. • Frequency of the recurrent and terminal events – where methods that analyse death as non-informative censoring or as a recurrent event may not be ideal for cohorts in which mortality is expected to be relatively high. A conservative approach is to include a method for a primary statistical analysis based on the study assumptions, and provide sensitivity analyses based on other methods for robustness.

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Co-morbidities Alternative approaches include the use of methods based on event rates, such as the Poisson regression and negative binomial regression. The latter allows for more flexibility but assuming a constant event rate over time and not analysing death as a competing risk, thus it may not be preferred in scenarios where fatal events account for a high proportion of the composite. Of interest in this situation is the Gosh and Lin cumulative incidence method, which handles fatal events as informative censoring.39 In a recent pre-specified sub-analysis of the PARADIGM-HF trial, the authors compared results of the analysis of recurrent hospitalisations using a cumulative incidence method, time-to-event models (WLW, LWYY and the joint frailty model) and the negative binomial model. All approaches provided similar estimates for the effect of the experimental therapy (sacubitril/valsartan) when compared with the traditional time-to-first-event analysis (log-rank test).28 The authors concluded that no single method can be recommended over another, and the preferred statistical approach for a specific trial should be discussed with regulatory agencies.26 It is noteworthy that the joint frailty and the LWYY methods offer advantages that have prompted their use in recent studies (Table 3).17,28,40 Generalised pairwise comparison (GPC) methods have been developed, which use non-parametric approaches to compare outcomes on the basis of pairs of subjects.41 Hierarchical GPC methods include the Finkelstein–Schoenfeld method, the unmatched Pocock method (or win ratio) and the Buyse method, among others.35,42,43

10.

11.

12.

13.

Baumgartner H, Falk V, Bax JJ, et al. 2017 ESC/EACTS Guidelines for the management of valvular heart disease. Eur Heart J 2017;38:2739–91. https://doi.org/10.1093/eurheartj/ ehx391; PMID: 28886619. Frank S, Johnson A, Ross J Jr. Natural history of valvular aortic stenosis. Br Heart J 1973;35:41–6. https://doi.org/10.1136/ hrt.35.1.41; PMID: 4685905. Kapadia SR, Leon MB, Makkar RR, et al. 5-year outcomes of transcatheter aortic valve replacement compared with standard treatment for patients with inoperable aortic stenosis (PARTNER 1): a randomised controlled trial. Lancet 2015;385:2485–91. https://doi.org/10.1016/S01406736(15)60290-2; PMID: 25788231. Genereux P, Pibarot P, Redfors B, et al. Staging classification of aortic stenosis based on the extent of cardiac damage. Eur Heart J 2017;38:3351–8. https://doi.org/10.1093/eurheartj/ ehx381; PMID: 29020232. Ito S, Miranda WR, Nkomo VT, et al. Reduced left ventricular ejection fraction in patients with aortic stenosis. J Am Coll Cardiol 2018;71:1313–21. https://doi.org/10.1016/j. jacc.2018.01.045; PMID: 29566814. Everett RJ, Clavel MA, Pibarot P, Dweck MR. Timing of intervention in aortic stenosis: a review of current and future strategies. Heart 2018;104:2067–76 https://doi.org/10.1136/ heartjnl-2017-312304; PMID: 30030337. Adams DH, Popma JJ, Reardon MJ, et al. Transcatheter aortic-valve replacement with a self-expanding prosthesis. N Engl J Med 2014;370:1790–8. https://doi.org/10.1056/ NEJMoa1400590; PMID: 24678937. Leon MB, Smith CR, Mack M, et al. Transcatheter aortic-valve implantation for aortic stenosis in patients who cannot undergo surgery. N Engl J Med 2010;363:1597–607. https://doi. org/10.1056/NEJMoa1008232; PMID: 20961243. Leon MB, Smith CR, Mack MJ, et al. Transcatheter or surgical aortic-valve replacement in intermediate-risk patients. N Engl J Med 2016;374:1609–20. https://doi.org/10.1056/ NEJMoa1514616; PMID: 27040324. Popma JJ, Adams DH, Reardon MJ, et al. Transcatheter aortic valve replacement using a self-expanding bioprosthesis in patients with severe aortic stenosis at extreme risk for surgery. J Am Coll Cardiol 2014;63:1972–81. https://doi. org/10.1016/j.jacc.2014.02.556; PMID: 24657695. Reardon MJ, Van Mieghem NM, Popma JJ, et al. Surgical or transcatheter aortic-valve replacement in intermediaterisk patients. N Engl J Med 2017;376:1321–31. https://doi. org/10.1056/NEJMoa1700456; PMID: 28304219. Smith CR, Leon MB, Mack MJ, et al. Transcatheter versus surgical aortic-valve replacement in high-risk patients. N Engl J Med 2011;364:2187–98. https://doi.org/10.1056/ NEJMoa1103510; PMID: 21639811. Thyregod HG, Steinbruchel DA, Ihlemann N, et al. Transcatheter versus surgical aortic valve replacement in patients with severe aortic valve stenosis: 1-year results

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15.

16.

17.

18.

19.

20.

21.

22.

23.

These methods allow the creation of a hierarchy that gives a higher priority to the most severe outcomes and are able to accommodate multiple events. Characteristically, GPC methods are used for binary outcomes, such as in the primary endpoint of the Tafamidis in Transthyretin Cardiomyopathy Clinical Trial (ATTR-ACT) trial, which included a hierarchical assessment of all-cause death and frequency of cardiovascular-related hospitalisations or the combination of binary and continuous outcomes, such as in the primary endpoint of the TAVR UNLOAD trial, defined as the hierarchical occurrence within one year of all-cause death, disabling stroke, hospitalisations (related to HF, symptomatic aortic valve disease or non-disabling stroke) and change in KCCQ relative to baseline.27,44 Non-hierarchical GPC methods include the O’Brien method.45 Little is known about the relative benefits of one method over another. The Finkelstein– Schoenfeld method is currently the GPC method most widely used in cardiovascular research.

Conclusion HF events, impaired functional status and reduced disease-specific quality of life are highly prevalent in patients with aortic stenosis and are significantly and positively affected by aortic valve interventions. The use of standardised definitions for HF-related events is recommended to improve our understanding of the disease and to allow comparisons among clinical trials. Further research on complex statistical approaches, which take into account the occurrence of multiple events, is warranted.

from the all-comers NOTION randomized clinical trial. J Am Coll Cardiol 2015;65:2184–94. https://doi.org/10.1016/j. jacc.2015.03.014; PMID: 25787196. Osnabrugge RL, Arnold SV, Reynolds MR, et al. Health status after transcatheter aortic valve replacement in patients at extreme surgical risk: results from the CoreValve US trial. JACC Cardiovasc Interv 2015;8:315–23. https://doi.org/10.1016/j. jcin.2014.08.016; PMID: 25700755. Allen LA, Spertus JA. End points for comparative effectiveness research in heart failure. Heart Fail Clin 2013;9:15–28. https:// doi.org/10.1016/j.hfc.2012.09.002; PMID: 23168314. Zannad F, Garcia AA, Anker SD, et al. Clinical outcome endpoints in heart failure trials: a European Society of Cardiology Heart Failure Association consensus document. Eur J Heart Fail 2013;15:1082–94. https://doi.org/10.1093/eurjhf/ hft095; PMID: 23787718. Shen L, Jhund PS, Mogensen UM, et al. Re-examination of the BEST trial using composite outcomes, including emergency department visits. JACC Heart Fail 2017;5:591–9. https://doi. org/10.1016/j.jchf.2017.04.005; PMID: 28774394. Hicks KA, Tcheng JE, Bozkurt B, et al. 2014 ACC/AHA key data elements and definitions for cardiovascular endpoint events in clinical trials: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (writing committee to develop cardiovascular endpoints data standards). J Am Coll Cardiol 2015;66:403–69. https://doi.org/10.1016/j.jacc.2014.12.018; PMID: 25553722. Stone GW, Adams DH, Abraham WT, et al. Clinical trial design principles and endpoint definitions for transcatheter mitral valve repair and replacement: part 2: endpoint definitions: a consensus document from the Mitral Valve Academic Research Consortium. J Am Coll Cardiol 2015;66:308–21. https:// doi.org/10.1016/j.jacc.2015.05.049; PMID: 26184623. Okumura N, Jhund PS, Gong J, et al. Importance of clinical worsening of heart failure treated in the outpatient setting: evidence from the prospective comparison of ARNI with ACEI to determine impact on global mortality and morbidity in heart failure trial (PARADIGM-HF). Circulation 2016;133:2254–62. https://doi.org/10.1161/CIRCULATIONAHA.115.020729; PMID: 27143684. Arnold SV, Spertus JA, Lei Y, et al. Use of the Kansas City Cardiomyopathy Questionnaire for monitoring health status in patients with aortic stenosis. Circ Heart Fail 2013;6:61–7. https://doi.org/10.1161/CIRCHEARTFAILURE.112.970053; PMID: 23230306. Baron SJ, Arnold SV, Wang K, et al. Health status benefits of transcatheter vs surgical aortic valve replacement in patients with severe aortic stenosis at intermediate surgical risk: results from the PARTNER 2 randomized clinical trial. JAMA Cardiol 2017;2:837–45. https://doi.org/10.1001/ jamacardio.2017.2039; PMID: 28658491. Reynolds MR, Magnuson EA, Wang K, et al. Health-related quality of life after transcatheter or surgical aortic valve

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2016;72:926–35. https://doi.org/10.1111/biom.12475; PMID: 26812695. 42. B uyse M. Generalized pairwise comparisons of prioritized outcomes in the two-sample problem. Stat Med 2010;29: 3245–57. https://doi.org/10.1002/sim.3923; PMID: 21170918. 43. Pocock SJ, Ariti CA, Collier TJ, Wang D. The win ratio: a new approach to the analysis of composite endpoints in clinical trials based on clinical priorities. Eur Heart J 2012;33:176–82. https://doi.org/10.1093/eurheartj/ehr352; PMID: 21900289. 44. Maurer MS, Schwartz JH, Gundapaneni B, et al. Tafamidis treatment for patients with transthyretin amyloid cardiomyopathy. N Engl J Med 2018;379:1007–16. https://doi. org/10.1056/NEJMoa1805689; PMID: 30145929. 45. O’Brien PC. Procedures for comparing samples with multiple endpoints. Biometrics 1984;40:1079–87. https://doi. org/10.2307/2531158; PMID: 6534410.

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Co-morbidities

Bidirectional Relationship Between Cancer and Heart Failure: Old and New Issues in Cardio-oncology Edoardo Bertero, 1 Pietro Ameri 2,3 and Christoph Maack 1 1. Comprehensive Heart Failure Center, University Clinic Würzburg, Würzburg, Germany; 2. Cardiovascular Disease Unit, IRCCS Ospedale Policlinico San Martino – IRCCS Italian Cardiovascular Network, Genova, Italy; 3. Department of Internal Medicine and Centre of Excellence for Biomedical Research, University of Genova, Genova, Italy

Abstract The main focus of cardio-oncology has been the prevention and treatment of the cardiac toxicity of chemotherapy and radiotherapy. Furthermore, several targeted therapies have been associated with unexpected cardiotoxic side-effects. Recently, epidemiological studies reported a higher incidence of cancer in patients with heart failure (HF) compared with individuals without HF. On this basis, it has been proposed that HF might represent an oncogenic condition. This hypothesis is supported by preclinical studies demonstrating that hyperactivation of the sympathetic nervous system and renin–angiotensin–aldosterone system, which is a hallmark of HF, promotes cancer growth and dissemination. Another intriguing possibility is that the co-occurrence of HF and cancer is promoted by a common pathological milieu characterised by a state of chronic low-grade inflammation, which predisposes to both diseases. In this review, we provide an overview of the mechanisms underlying the bidirectional relationship between HF and cancer.

Keywords Cancer, heart failure, chemotherapy, neurohormonal activation, inflammation, amyloidosis, carcinoid heart disease Disclosure: CM is supported by the Deutsche Forschungsgemeinschaft (DFG; SFB-894, MA 2528/7-1, TRR-219), and the German Ministry of Education and Science (BMBF; 01EO1504, CF.3, RC.2). Received: 3 January 2019 Accepted: 14 February 2019 Citation: Cardiac Failure Review 2019;5(2):106–11. DOI: https://doi.org/10.15420/cfr.2019.1.2 Correspondence: Christoph Maack, Comprehensive Heart Failure Center, University Clinic Würzburg; Am Schwarzenberg 15, Haus A15, 97078 Würzburg, Germany. E: Maack_C@ukw.de Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

Heart failure (HF) and cancer represent two major causes of morbidity and mortality in developed countries.1,2 The prevalence of these conditions is growing as the age of the population and the burden of shared risk factors, such as diabetes and obesity, are constantly increasing. In past decades, the field of cardiooncology has predominantly focused on prevention and treatment of cardiovascular disease in cancer survivors, who are particularly prone to developing HF as a result of the cardiotoxicity of many antineoplastic agents and the clustering of cardiovascular risk factors in oncological patients.3 The co-occurrence of cancer and HF represents a major clinical problem, because each disease impinges on the treatment of the other disease, and consequently, has a detrimental impact on quality of life and survival.4,5 In this scenario, the interaction between cardiologists and oncologists is indispensable to ensure optimal management of patients affected by both conditions.4 In recent years, a previously unappreciated connection between cancer and cardiovascular disease emerged from epidemiological studies reporting an increased risk of incident cancer in HF patients.6–9 Although the cause of this association is not yet resolved, it has been proposed that HF might represent a cancer-predisposing condition.9–11 Another intriguing possibility is that the co-occurrence of HF and cancer is promoted by a common

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pathological milieu characterised by a state of chronic low-grade inflammation, which predisposes to both diseases.10 In this review, we provide an overview of the mechanisms underlying the bidirectional relationship between HF and cancer (Figure 1). Whereas pathways driving the increased risk of cardiovascular disease in cancer patients have been the subject of intense investigation, mechanistic links driving the increased risk of malignancy in HF patients have not been elucidated so far. In this respect, we outline below two non-mutually exclusive hypotheses that should be addressed by future preclinical and clinical studies.

Incident Heart Failure in Cancer Advances in the treatment of cancer have reduced the morbidity and mortality associated with many types of neoplasms. However, oncological therapies, including chemotherapy, radiotherapy, and newer-generation targeted therapies, may have toxic effects on the heart (Figure 2), up to causing HF either acutely, e.g. by causing acute coronary syndromes or myocarditislike syndromes, or chronically, by directly impacting on cardiac myocyte function.12 Because of the substantial improvements in the management of most types of cancer, these complications may have a major impact on the prognosis of patients with malignancy;

Bidirectional Relationship Between Cancer and Heart Failure in fact, they may become the primary clinical problem when cancer is stably controlled or cured.13

Figure 1: Mechanisms Underlying the Bidirectional Relationship Between Heart Failure and Cancer

A far less common cause of HF in cancer patients is the secretion of cardiotoxic substances, such as light-chain immunoglobulins or vasoactive mediators associated with monoclonal B-cell proliferation and neuroendocrine tumours (NETs), respectively.

From cancer to heart failure: • Cancer therapy-related cardiotoxicity • Amyloidosis – carcinoid heart disease

Chemotherapy- and Radiotherapy-induced Heart Failure Anthracyclines, a class of chemotherapeutic agents commonly used for the treatment of solid and haematologic malignancies, were the first antineoplastic drugs for which a cardiotoxic effect was recognised.14 Anthracycline cardiotoxicity may manifest as HF with acute or subacute onset, but may also lead to subclinical left ventricular dysfunction insidiously progressing to HF over the course of several years after exposure to the drug.15 The incidence of anthracyclinerelated cardiac dysfunction is dose-dependent, and ranges from 5% at a cumulative dose of 400 mg/m2 to 26% for 550 mg/m2.16 However, a subclinical decrease in systolic function has also been reported for lower doses in survivors of acute lymphoblastic leukaemia.17 The antiproliferative effect of anthracyclines stems from their ability to intercalate into nuclear DNA and block topoisomerase 2 activity, consequently inhibiting DNA replication and transcription. Furthermore, these agents cause damage to cellular components by forming complexes with iron and thereby inducing production of reactive oxygen species (ROS). Preclinical studies indicated that oxidative stress might represent the dominant driver of anthracyclines cardiotoxicity, but ROS scavengers failed to prevent doxorubicininduced cardiomyopathy in humans.12,18 Moreover, iron chelating agents did not show any cardioprotective effect in a rat model of anthracycline toxicity.19 A recent experimental study demonstrated that cardiac topoisomerase is a key mediator of doxorubicininduced cardiotoxicity, possibly accounting for the lack of efficacy of antioxidant agents in this setting. In fact, doxorubicin triggers apoptosis and transcriptomic remodelling in a topoisomerasedependent manner, ultimately impacting on oxidative phosphorylation and mitochondrial biogenesis.20 Overall, in spite of a large body of preclinical research addressing the mechanisms of anthracyclines cardiotoxicity, pharmacological approaches aimed at alleviating this important side-effect are limited to a single agent, dexrazoxane, which achieves its cardioprotective activity via topoisomerase inhibition.21 Recently, inhibition of the multifunctional kinase, phosphoinositide 3-kinase gamma, was shown to enhance removal of damaged mitochondria in a mouse model of doxorubicin-induced HF, pinpointing a potential therapeutic strategy to protect the heart against anthracyclines toxicity.22

Cancer

Inflammation

Heart failure

From heart failure to cancer: • SNS and RAAS hyperactivation • Secreted factors

RAAS = renin–angiotensin–aldosterone system; SNS = sympathetic nervous system.

effects mainly by triggering coronary artery vasospasm,12 but preclinical studies indicate that these agents might also be directly toxic to endothelial cells and cardiac myocytes by triggering ROS production and inducing mitochondrial dysfunction.26,27 Radiation therapy represents a standard approach for breast cancer treatment, and often involves the exposure of the heart to high radiation doses. Pericardial fibrosis is the most common radiotherapyrelated lesion, but radiation therapy also damages the myocardium.28 Indeed, although cardiac myocytes are non-proliferating cells, and thus relatively resistant to radiation damage, emerging evidence indicates that chest irradiation can also lead to cardiomyopathy, and preclinical studies pinpointed ROS production with subsequent activation of Ca2+/ calmodulin-dependent protein kinase II as a key mediator of radiation damage to cardiac myocytes.29 In contrast to cardiac myocytes, endothelial cells are continuously proliferating, and thereby more susceptible to radiation damage. Preclinical studies indicate that the primary lesion associated with radiation therapy is endothelial apoptosis, which might account for the clinical observation of accelerated atherosclerosis in patients receiving radiation therapy to the chest.30,31 In fact, cardiac radiation dose correlates with the subsequent risk of ischaemic heart disease in breast cancer patients, and even low levels of exposure heighten the risk of coronary events.32 Furthermore, a recent study observed that radiation therapy in breast cancer patients leads to a dose-dependent increase in the relative risk of HF with preserved ejection fraction (HFpEF).33 The latter observation corroborates the model according to which microvascular endothelial dysfunction represents a key factor in the pathogenesis of HFpEF.34

Antineoplastic Targeted Therapy-induced Heart Failure Since the discovery of anthracyclines-related cardiotoxicity, many other chemotherapeutic agents have been associated with the development of cardiomyopathy. Alkylating agents, such as cyclophosphamide and ifosfamide, inhibit cell proliferation by inducing DNA damage. Cardiotoxicity associated with these drugs manifests predominantly as conduction disorders and pericarditis, and high-dose regimens can lead to myocarditis and HF.23,24 Experimental evidence suggests that alkylating agents cause endothelial and myocyte damage secondary to the accumulation of toxic metabolites.25 Antimetabolites, such as 5-fluorouracil and its pro-drug capecitabine, achieve their cardiotoxic

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Trastuzumab is a humanised monoclonal antibody targeting the human epidermal growth factor receptor (HER)2, a member of the ErbB family of receptors, which is overexpressed in a subset of breast cancer patients.35 Trastuzumab was initially approved as a first-line treatment for metastatic breast cancer, and is currently indicated for the treatment of HER2-positive breast and gastric cancer. The addition of trastuzumab to adjuvant therapy for breast cancer resulted in asymptomatic left ventricular dysfunction or overt HF in up to 18% and 4% of treated patients, respectively.36,37 The observation of trastuzumab cardiotoxicity led scientists to

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Co-morbidities Figure 2: Mechanisms Underlying Incident HF in Cancer

Cancer therapy Chemotherapy

Targeted therapies

Radiation therapy Anthracyclines Vascular injury

ROS Topoisomerase inhibition Antimetabolites Alkylating agents

Myocardial fibrosis

ErbB2 inhibition

Ischaemia Toxic metabolites

Multiple, not fully resolved mechanisms

Heart failure

Trastuzumab

Monoclonal Ab, TKI

Krebs cycle inhibition Myocardial infiltration

Direct toxicity

Serotonin

Ig light chain

Oncometabolites

NET

Plasma cell malignancies

Myeloid leukaemia

Cancer Ab = antibody; Ig = immunoglobulin; NET = neuroendocrine tumours; ROS = reactive oxygen species; TKI = tyrosine kinase inhibitor.

interrogate the function of HER2 signalling in preclinical models of cardiac disease, revealing that this pathway plays an important homeostatic role,38 and is activated in response to cardiac injury; for example, following ischaemia, pressure overload, and anthracycline toxicity (reviewed by De Keulenaer et al.39). Therefore, HER2 inhibition does not cause myocardial damage directly, but rather, blocks an important adaptive signalling pathway and thereby renders the heart more susceptible to pathological stressors. Accordingly, trastuzumabinduced cardiac dysfunction is usually completely reversible 4â&#x20AC;&#x201C;6 weeks after discontinuation of the drug. However, for reasons yet to be fully elucidated, cardiac function is irreversibly compromised in a minority of patients treated with trastuzumab.36 Vascular endothelial growth factor (VEGF) is a key regulator of angiogenesis, the process of new blood vessel formation that sustains tumour growth when its enlargement precludes diffusion of nutrients and oxygen from pre-existing vessels.40 VEGF signalling has become the target of several antineoplastic agents, such as the humanised antibody bevacizumab and the tyrosine kinase inhibitors (TKI) sunitinib and sorafenib. Drugs targeting VEGF signalling have been linked to a wide spectrum of cardiovascular side-effects, such as hypertension, thromboembolism, and cardiomyopathy.41,42 In patients treated with anthracyclines for breast cancer, concurrent treatment with bevacizumab increased HF incidence from 4% to 14%.43 Experimental evidence indicates that the effects of agents inhibiting VEGF signalling on blood pressure and thromboembolic risk might be mediated by decreased production of two vasodilators, nitric oxide and prostacyclin, and increased production of the potent vasoconstrictor, endothelin-1, whose circulating levels were found elevated in patients treated with sunitinib.44â&#x20AC;&#x201C;46 Sunitinib and sorafenib are only two examples of small-molecule TKI for which cardiotoxic effects were recognised. The number of TKI approved for cancer treatment is steadily growing, and cardiovascular side-effects have been reported for many of

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these drugs, such as the ABL inhibitors dasatinib and nilotinib or the multi-kinase inhibitor regorafenib.47 Although the incidence of cardiovascular side-effects with these drugs is relatively low, the underlying mechanisms need to be further clarified to improve the safety of TKI currently under development. Finally, cardiotoxic effects have also been associated with proteasome inhibitors, a class of antineoplastic agents used in the treatment of multiple myeloma and other hematologic malignancies. The first approved agent of this class, bortezomib, might cause HF in up to 4% of treated patients, and the second-generation proteasome inhibitor, carfilzomib, is associated with an even higher cardiotoxicity, with an incidence of cardiovascular adverse events of 18% according to a recent meta-analysis.48,49 The ubiquitinâ&#x20AC;&#x201C;proteasome system plays an important adaptive role in the myocardium, and its inhibition is sufficient to cause cardiac dysfunction in pigs.50 Therefore, cardiotoxicity associated with proteasome inhibitors is likely directly related to their mechanism of action.

Cancer-related Heart Failure HF can also be the consequence of two rare cardiomyopathies, i.e. light-chain amyloidosis and carcinoid heart disease (Figure 2), although this happens more rarely than following oncological treatments. Amyloidosis is a disorder characterised by extracellular deposition of a proteinaceous material, coined as amyloid, derived from misfolding of a variety of precursor proteins.51 Amyloidosis is a systemic disorder and can affect several organs, but amyloid involvement of the heart portends by far the worst prognosis of any other type of organ involvement. Cardiac amyloidosis involves both myocardium and cardiac valves, and manifests as restrictive cardiomyopathy inexorably progressing to overt HF (reviewed by Falk et al.52 and Gertz et al.53). Amyloid light-chain (AL) amyloidosis, which is secondary

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Bidirectional Relationship Between Cancer and Heart Failure to overproduction of immunoglobulin light chain by plasma cell malignancies, is the most severe form of the disease, with a median survival of 6 months from HF onset if the underlying dyscrasia is left untreated.54 Cardiac AL amyloidosis leads to a more severe form of HF despite a lower degree of cardiac hypertrophy, suggesting that AL amyloid protein might have direct toxic effects on cardiac myocytes.55 Preclinical studies indicate that oxidative stress might represent a dominant driver of AL amyloid cardiotoxic activity.56 Treatment of cardiac AL amyloidosis is currently limited to optimal management of HF and the underlying amyloidogenic malignancy, whereas therapeutic approaches directly targeting AL deposition in the myocardium are not currently available in the clinical setting.52 A rare form of cancer-related cardiac involvement is carcinoid heart disease, which is caused by NETs releasing vasoactive mediators, such as serotonin, bradykinin, and histamine. NETs are rare neoplasms arising from enterochromaffin cells of the gastrointestinal or respiratory tract. Because the mediators released by NETs are efficiently inactivated in the liver and the pulmonary vasculature, carcinoid heart disease usually arises from gastrointestinal NET upon their metastasisation to the liver and predominantly affects the right ventricle, whereas left ventricular involvement is observed in 5–10% of cases and is usually associated with bronchial carcinoids.57,58 The typical feature of carcinoid heart disease is the formation of endomyocardial fibrotic plaques, ultimately leading to right-sided HF. Furthermore, fibrotic remodelling often also involves the tricuspid valve, causing valvular regurgitation, which contributes to right ventricular decompensation. Medical therapy for carcinoid syndrome is limited to symptomatic relief with somatostatin analogues, which are ineffective toward myocardial and valvular involvement.59 While AL amyloidosis and carcinoid heart disease are the only forms of cancer-elicited HF observed in the clinical arena so far, experimental work suggests that other malignancies might affect cardiac function via the release of cardiotoxic oncometabolites. Mutations of the Krebs cycle enzyme, isocitrate dehydrogenase, have been identified in a subset of patients with myeloid leukaemia. In rats, this mutation leads to accumulation and release of D-2-hydroxyglutarate from malignant cells, and this oncometabolite impairs cardiac Krebs cycle activity and contractile function.60

Incident Cancer in Heart Failure Recent epidemiological studies revealed that HF patients carry a higher risk of incident cancer compared with individuals without HF, drawing attention toward another potential link between HF and cancer. This finding was first reported in a community-based case– control study, and subsequently confirmed in a large prospective study based on the Danish national registries.6,7 Furthermore, a prospective cohort study demonstrated that patients developing HF following acute MI have an increased risk of incident cancer compared with those who do not develop HF after MI. 8 This association might be accounted for by a detection bias due to intensified medical observation following HF diagnosis. However, the increased risk of incident cancer was observed after the second year after HF diagnosis, and the association persisted after excluding cancer diagnoses made in the first years of follow-up. Furthermore, cancer and HF share several risk factors, such as diabetes and obesity, which might partly explain the association between HF and increased risk of malignancy. In the above-

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mentioned studies, however, the likelihood of receiving a diagnosis of cancer remained higher in HF patients after adjusting for shared risk factor. Another possibility is that the increased risk of incident cancer is driven by a pro-oncogenic effect of HF medications, but recent meta-analyses addressing this issue do not support this concept.61 On these grounds, the present authors and other authors have put forward two non-mutually exclusive hypotheses on how HF might lead to an increased risk of cancer, which are discussed in detail below.9,10 A third potential mechanism was recently elucidated in a preclinical study that demonstrated that ischemic HF enhances tumour growth via release of mitogenic factors by the failing myocardium.11 In that study, MI was induced in mice via coronary artery ligation, and infarcted hearts were transplanted in the cervical region of APCmin mice, which are genetically predisposed to develop colorectal neoplasms. Intriguingly, mice transplanted with an infarcted heart developed a higher tumour burden compared with mice receiving a sham-operated heart. Because recipient mice retained their native healthy hearts, the increase in tumour load could not be attributed to haemodynamic impairment related to HF, but was shown to depend on the mitogenic protein, serpinA3, secreted by the failing myocardium. The translational relevance of this mechanism is underscored by the observation that circulating levels of serpinA3 are increased in chronic HF patients.11 Overall, the results of that study strongly support the concept that a diagnosis of HF represents a risk factor for incident cancer.

The Neurohormonal Hypothesis Hyperactivation of the sympathetic nervous system (SNS) and renin–angiotensin–aldosterone system (RAAS) is a hallmark of HF with reduced ejection fraction (HFrEF), and substantially contributes to episodes of decompensation as well as to cardiac death. Indeed, medical therapy of HFrEF currently relies on neurohormonal inhibitors: blockers of the beta-adrenergic receptors (AR), through which the catecholamines epinephrine and norepinephrine transmit SNS signals; inhibitors of the angiotensin-converting enzyme that synthesises angiotensin II (AngII); and antagonists of the AngII or aldosterone receptor.62 The hypothesis that neurohormonal activation may also account for the increased risk of cancer observed in HF finds its background in a large body of experimental data demonstrating that SNS and RAAS activation promote cancer progression and dissemination via multiple mechanisms. The pro-oncogenic effects of the SNS are predominantly mediated by beta-AR expressed by both cancer cells and, more importantly, non-malignant cells constituting the tumour microenvironment. Specifically, beta-AR signalling was demonstrated to favour tumour growth, induce formation of blood and lymphatic vessels, and promote remodelling of the extracellular matrix, ultimately leading to tissue invasion and metastatic dissemination in vivo.63 Similarly, AngII promotes tumour vascularisation and invasiveness via type 1 AngII receptors.64 An important caveat is that, although SNS and RAAS activation has also been described in HFpEF patients, the latter do not benefit from treatment with beta-AR blockers and RAAS inhibitors, indicating that the role of neurohormonal activation in the progression of HFpEF is not as relevant as in HFrEF.65,66 Two of the epidemiological studies discussed above included a substantial proportion of HFpEF patients, and cancer incidence was independent of left ventricular

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Co-morbidities ejection fraction.6,9 Because neurohormonal hyperactivation might not account for the higher incidence of cancer observed in HFpEF, we hypothesise that other factors are involved in this subset of patients.

The ‘Inflammatory Milieu’ Hypothesis Independent of its aetiology, HF is associated with an increase in circulating and intramyocardial levels of pro-inflammatory cytokines, such as tumour necrosis factor-alpha, interleukin-1, and interleukin-6.67–70 Inflammation is pivotal to the pathogenesis of atherosclerosis, which underlies the development of ischemic heart disease, the most common cause of HF.71 In turn, myocardial injury triggers immune system activation, inducing cytokine release, and thereby fostering a vicious cycle of self-sustained inflammation. Furthermore, it has been hypothesised that microvascular endothelial inflammation might decrease myocardial nitric oxide release, thereby inducing cardiac myocyte hypertrophy and impairing relaxation, which is a hallmark of HFpEF.34 Indeed, HFpEF patients display elevated concentrations of galectin-3, an inflammatory mediator associated with myocardial fibrosis, and pentraxin 3, an inflammatory marker that was observed to correlate with left ventricular diastolic dysfunction.72,73 Furthermore, circulating levels of inflammatory markers (tumour necrosis factoralpha, transforming growth factor-beta, C-reactive protein, procollagen type 1 carboxy-terminal propeptide) were found to be elevated, and correlated with asymptomatic diastolic dysfunction in patients with metabolic syndrome and hypertension.74 Altogether, a wealth of clinical studies indicate that HFrEF and HFpEF are associated with a state of mild chronic systemic inflammation, but it is currently unresolved whether the latter is a cause or consequence of cardiac dysfunction. In contrast, chronic inflammation is considered carcinogenic and capable of boosting the transition from early-stage tumours to overt malignancies.75 In principle, therefore, inflammation might mediate the association of both HFrEF and HFpEF with incident cancer. Although preclinical studies addressing this hypothesis are lacking, this model is corroborated by the results of the Canakinumab AntiInflammatory Thrombosis Outcome Study (CANTOS) trial.76 In that study, the interleukin-1beta-targeting antibody, canakinumab, reduced the rate of recurrent cardiovascular events in patients with previous MI. Intriguingly, additional analyses revealed that treatment with

hrist M, Stork S, Dorr M, et al. Heart failure epidemiology C 2000-2013: insights from the German Federal Health Monitoring System. Eur J Heart Fail 2016;18:1009–18. https://doi. org/10.1002/ejhf.567; PMID: 27246139. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin 2016;66:7–30. https://doi.org/10.3322/caac.21332; PMID: 26742998. Armenian SH, Xu L, Ky B, et al. Cardiovascular disease among survivors of adult-onset cancer: a community-based retrospective cohort study. J Clin Oncol 2016;34:1122–30. https://doi.org/10.1200/JCO.2015.64.0409; PMID: 26834065. Ameri P, Canepa M, Anker MS, et al. Cancer diagnosis in patients with heart failure: epidemiology, clinical implications and gaps in knowledge. Eur J Heart Fail 2018;20:879–87. https://doi.org/10.1002/ejhf.1165; PMID: 29464808. Rohrmann S, Witassek F, Erne P, et al. Treatment of patients with myocardial infarction depends on history of cancer. Eur Heart J Acute Cardiovasc Care. 2018;7:639–45. https://doi. org/10.1177/2048872617729636; PMID: 28927294. Banke A, Schou M, Videbaek L, et al. Incidence of cancer in patients with chronic heart failure: a long-term follow-up study. Eur J Heart Fail 2016;18:260–6. https://doi.org/10.1002/ ejhf.472; PMID: 26751260. Hasin T, Gerber Y, McNallan SM, et al. Patients with heart failure have an increased risk of incident cancer. J Am Coll Cardiol 2013;62:881–6. https://doi.org/10.1016/j. jacc.2013.04.088; PMID: 23810869. Hasin T, Gerber Y, Weston SA, et al. Heart failure after

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canakinumab was associated with a dose-dependent trend toward reduction of hospitalisation for HF, which was independent of prior HF history, and a lower risk of incident lung cancer.77,78 Altogether, the results of the CANTOS trial strongly support the concept that chronic low-grade inflammation represents a fertile substrate for the progression of HF and cancer. The striking results of the CANTOS trial stand to some degree at odds with studies using broad-spectrum anti-inflammatory agents, namely the tumour necrosis factor-alpha inhibitors, etanercept and infliximab, and the immune-system suppressant, methotrexate, which did not detect any effect of these drugs on cardiovascular events.77,79,80 An important difference between these studies and the CANTOS trial is that only the latter enrolled patients with modestly elevated C-reactive protein levels, reflecting a state of mild systemic inflammation. Furthermore, although excess inflammation is undoubtedly detrimental, cytokine signalling also mediates adaptive responses in the heart, and future studies should be aimed to more precisely identify signalling pathways associated with maladaptive processes driving the progression of HF.81,82 Finally, HF-related inflammation might foster cancer in an indirect way. For instance, a decline in the number of naïve T cells, and a marked increase in highly differentiated effector and memory T cells was recently observed in patients with HF, and is related to elevated levels of interleukin-6.83 These features are consistent with immunosenescence, which consists of the deterioration of both adaptive and innate immunity, and, given the role played by the immune system in malignant cell elimination, may partly account for the increase in cancer incidence in HF, as it has been postulated for ageing.84

Conclusion Until now, the main focus of cardio-oncology has been the prevention and treatment of cardiotoxic effects of chemotherapeutic agents. In this context, elucidation of the underlying mechanisms is instrumental to the development of strategies to prevent chemotherapy-related cardiomyopathy. While this avenue of research is far from being exhausted as a result of the staggering growth of novel anticancer targeted therapies, a new exciting area of cardio-oncology opens up in front of us, inspired by several lines of evidence linking the pathophysiology of HF to the development and progression of malignancy.

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Heart Failure and Cancer: Mechanisms of Old and New Cardiotoxic Drugs in Cancer Patients Alessandra Cuomo, Alessio Rodolico, Amalia Galdieri, Michele Russo, Giacomo Campi, Riccardo Franco, Dalila Bruno, Luisa Aran, Antonio Carannante, Umberto Attanasio, Carlo G Tocchetti, Gilda Varricchi and Valentina Mercurio Department of Translational Medical Sciences, Federico II University, Naples, Italy

Abstract Although there have been many improvements in prognosis for patients with cancer, anticancer therapies are burdened by the risk of cardiovascular toxicity. Heart failure is one of the most dramatic clinical expressions of cardiotoxicity, and it may occur acutely or appear years after treatment. This article reviews the main mechanisms and clinical presentations of left ventricular dysfunction induced by some old and new cardiotoxic drugs in cancer patients, referring to the most recent advances in the field. The authors describe the mechanisms of cardiotoxicity induced by anthracyclines, which can lead to cardiovascular problems in up to 48% of patients who take them. The authors also describe mechanisms of cardiotoxicity induced by biological drugs that produce left ventricular dysfunction through secondary mechanisms. They outline the recent advances in immunotherapies, which have revolutionised anticancer therapies.

Keywords Anticancer drugs-induced cardiotoxicity, heart failure, anthracyclines, HER2, VEGF, immunotherapy. Disclosure: CGT received speaking honoraria from Alere and is supported by a Ricerca di Ateneo-Federico II University grant. All other authors have no conflicts of interest to declare. Received: 21 October 2018 Accepted: 30 January 2019 Citation: Cardiac Failure Review 2019;5(2):112–8. DOI: https://doi.org/10.15420/cfr.2018.32.2 Correspondence: Carlo Gabriele Tocchetti, Dipartimento di Scienze Mediche Traslazionali, Centro Interdipartimentale di Ricerca Clinica e Traslazionale (CIRCET), Universita’ degli Studi di Napoli Federico II, Naples, Italy. E: carlogabriele.tocchetti@unina.it Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

The increasing progress in cancer therapies has reduced mortality rates for many cancers. Unfortunately, many life-saving therapies are burdened by the risk of cardiotoxicity (CTX). The cardiovascular system appears to be particularly susceptible to the action of many antineoplastic drugs, which may cause vasospastic or thromboembolic ischaemia, arterial hypertension, dysrhythmia, and left ventricular (LV) dysfunction, leading to heart failure (HF).1–7 These problems are even more relevant in an ageing population as cancer can occur in patients with pre-existing cardiovascular conditions.8 Some of these side-effects may occur or persist once the cancer is eliminated or controlled. Asymptomatic reduction in LV function and HF are the typical complications of cancer therapies in the long term.9 Many studies have tried to clarify the mechanisms underlying cancer therapy-related HF.10 Anthracyclines (ANTs) are the most studied cardiotoxic drugs. The main mechanism hypothesised for their cardiotoxicity is direct damage of cardiomyocytes through the production of reactive oxygen species (ROS) and reactive nitrogen species.11–15 With the increasing use of new biological drugs, other mechanisms of CTX have been observed, with drugs that affect the heart through secondary mechanisms.16 Newer intracellular signalling inhibitors block pathways of primary importance for myocardial function, especially under conditions of cardiac stress, such as hypertension

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or hypertrophy.17 Furthermore, in recent years, a growing incidence of myocarditis, due to the use of immune checkpoint inhibitors that unleash immune responses, has been recorded.18–21 This situation is complicated by the fact that novel biological drugs are sometimes combined (concomitantly or sequentially) with traditional chemotherapies. A typical example is the anti-ErbB2 receptor antibody trastuzumab, which can lead to LV dysfunction on its own and in people without pre-existing cardiovascular disease, but also unmask or worsen LV dysfunction in patients previously treated with ANTs, by interfering with the neuregulin/ErbB2 pathway that seems to modulate the increase in ROS-caused ANTs.1,2,22,23

Anthracyclines ANTs are a typical example of cardiotoxic anticancer drugs, and their effects have been observed and studied since the 1960s.24 ANT-induced cardiomyopathy is characterised by the occurrence of cardiomyocyte damage that can eventually lead to HF. ANTs are a keystone in the treatment of many cancers, such as lymphomas, leukaemias and sarcomas, but also for early or advanced breast cancer.17 Their sideeffects are usually dose-dependent and more frequently detected in the first year after completing treatment.25,26 ANT CTX can manifest acutely in up to 30% of patients soon after infusion, requiring either modification or withdrawal of anticancer regimens. Risk factors have been identified for the development of cancer therapy-related HF,

Heart Failure and Cancer pre-existing heart disease and advanced age.25 Moreover, there seems to be a gender-related predisposition. Although experimental data point towards better resistance from women regarding cardiotoxicity with involvement of mitochondria and less oxidative stress, very few studies have been conducted in humans, although female patients in clinical studies appear to be more susceptible to doxorubicininduced cardiotoxicity.2,27,28 This apparent paradox may be explained because both age and menopausal status seem to be the two most important determinants of the sex-specific differences observed in the clinical setting, with higher susceptibility in prepuberal girls and postmenopausal women. Studies in young children receiving anticancer drugs for haematological malignancies suggest that prepuberal girls are more susceptible to develop early or late cardiac toxicity than boys of the same age.27,29 These data are consistent with the absence of female hormones at this age. Unfortunately, no survey has been conducted to specifically assess sex differences in the occurrence of ANT cardiotoxicity in adults. Several mechanisms underlying anthracycline CTX have been observed, but the main ones we will focus on are induction of oxidative stress, activation of DNA damage responses and impairment of mitochondrial biogenesis and metabolism. The consequence of these processes is cardiomyocyte death, apoptosis and necrosis, while the surviving cardiomyocytes develop maladaptive changes. This leads to pathological remodelling of the LV, with dilatation and impairment of contractility, until the decline of systolic function and development of clinically manifest HF.9 ANTs are characterised by a marked susceptibility to be rapidly reduced to unstable metabolites, such as doxorubicin-semiquinone, which generate hydrogen peroxide and superoxide by reacting with oxygen. ROS are also produced thanks to the ability of these drugs to chelate intracellular free iron, creating iron-doxorubicin complexes that react with oxygen (Figure 1). Furthermore, ANTs can directly interfere with the activity of major iron-transporting and iron-binding proteins, such as ABCB8, a mitochondrial iron exporter, promoting mitochondrial iron accumulation and ROS production. It has also been observed that hearts from patients with doxorubicin-related heart dysfunction have significantly higher mitochondrial iron levels than in patients with other types of cardiomyopathies or normal cardiac function.30 Research led by Edward Yeh has shown that the production of ROS could also be secondary to the interaction of ANTs with the beta isozyme of topoisomerase 2 (Top2), the only isoform expressed by adult mammalian cardiomyocytes.31 While the interaction of the drug with Top2-alpha – overexpressed in proliferating cancerous cells but not in quiescent tissues – generates a ternary Top2-doxorubicin-DNA cleavage complex that in turn triggers the death of tumour cells, the Top2-beta-doxorubicin-DNA complex induces DNA double strand breaks, ultimately promoting cardiomyocyte death.31 The ensuing DNA break induces the activation of p53, an enzyme that activates the proteins responsible for the DNA repair process, but can also repress genes involved in mitochondrial biogenesis, such as PPARGC1, oxidative phosphorylation, ultimately leading to defective organelle biogenesis and metabolic failure.31 An abnormal accumulation of mitochondria damaged by doxorubicin in the myocardium has also been reported, promoting the production of ROS and the death of cardiomyocytes. This accumulation would seem to be caused by the activation of p53, which is able to inhibit the normal recycling of dysfunctional mitochondria via autophagy.9

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Figure 1: The Main Mechanisms of Anthracycline-induced Injury to Cardiac Cells

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ROS and RNS overproduction DNA damage

Primary effects

Protein carbonylation Inhibition of Lipid neuregulin-1/ HER-2 peroxidation survival signalling

Intermediate effects

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Cell dysfunction: necrosis, apoptosis

Disruption of iron homeostasis

Release of Disruption HMGB1 of Ca and homeostasis activation of TLRs

Disregulation of miRNAs

Inhibition of topoisomerase 2B

The classic model of anthracycline (ANT) cardiotoxicity involves the generation of reactive oxygen species (ROS) by the quinone moiety common to all anthracyclines. ROS and RNS hyperproduction results in damage to DNA, protein carbonylation and lipid peroxidation, leading to cellular dysfunction and cardiomyocyte death. ANTs can also bind and block the functions of topoisomerases 2A (TOP2A) and 2B (TOP2B). Tumour cells express high levels of TOP2A, whereas TOP2B is ubiquitously expressed. Cardiomyocytes express TOP2B, but not TOP2A. ANTs form a complex with TOP2B inhibiting its enzymatic activity. Without functional TOP2B, DNA breaks accrue, leading to the activation of p53 tumour-suppressor protein, mitochondrial dysfunction and the generation of ROS that result in cardiomyocyte death. Another mechanism underlying doxorubicin-dependent oxidative stress is linked to the ability of the drug to directly interfere with the activity of NADPH oxidase and nitric oxide synthase (NOS). Both NADPH oxidase and NOS can transfer electron from NADPH to doxorubicin, causing the formation of semiquinone doxorubicin (SQ-DOX). SQ-DOX in turn transfers an electron to O2 and generates O2−. In the NOS compartment, O2− can react with NO to form peroxynitrite (ONOO−), a powerful oxidant that can generate free radicals. An alternative mechanism by which ANTs exert their cardiotoxic effects is the inhibition of neuregulin-1-human epidermal growth factor receptor 2 in cardiomyocytes. Doxorubicin also induces necrosis of immune (i.e. macrophages) and cancer cells, releasing high mobility group box 1, which activates Toll-like receptors 2 and 4 in cardiomyocytes and inflammatory cells, inducing the release of proinflammatory cytokines. These primary effects induce a plethora of secondary effects in cardiomyocytes, such as DNA damage, lipid peroxidation, mitochondrial dysfunction, which result in cell dysfunction and death.9 HER-2 = human epidermal growth factor receptor 2; HMGB1 = high mobility group box 1 miRNA = micro RNA; RNS = reactive nitrogen species; ROS = reactive oxygen species; TLR = Toll-like receptor. Source: Varricchi et al.9 Reproduced with permission from Frontiers.

ANTs are also involved in the activation of the mitogen-activated protein kinase (MAPK) cascade through reactive oxygen species and Ca2+. In particular, it is worth mentioning the role of p38 MAPK in the induction of cardiomyocyte death.32 It has been demonstrated that before any clinical sign of LV dysfunction in ANT cardiotoxicity, there is a reduction in the phosphocreatine:adenosine triphosphate ratio, suggesting the presence of alterations in myocardial energetics.33 In this study, the authors also demonstrated that ANTs can affect the normal functioning of creatine kinase (CK) by oxidising its sulfhydryl groups. More studies on this pathway are needed to identify novel cardioprotective therapeutic approaches. The possible protective role of CK in heart diseases is supported by improved cardiac function in murine hearts overexpressing myofibrillar CK and subjected to pressure overload, compared with non-transgenic mice.34 Moreover, CK overexpression seems to improve cardiac function and general myocardial energetics and also the survival of mice affected by CTX induced by ANTs.35 Among their other effects on cardiomyocytes energy metabolism, ANTs can alter fatty acid oxidation, due to a reduction of the phosphorylation of the enzyme anti-acetyl-CoA carboxylase and of the intracellular concentration of 5’-activated protein kinase (AMPK). Further studies will be needed to clarify the role of AMPK in ANTs-induced HF.36,37

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Figure 2: Mechanism of Action of Trastuzumab and Pathogenesis of its Cardiotoxicity Trastuzumab HER-2

HER-2

Trastuzumab NRG-1

HER-2 HER-3

HER-4

Tumour cell

Inhibition of cancer cell proliferation

Anti-ErbB2 Drugs

HER-2

HER-4

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Cardiomyocyte dysfunction

Antibody-dependent cellular cytotoxicity Trastuzumab is a monoclonal antibody that binds the extracellular domain IV of human epidermal growth factor receptor 2 (HER-2). It is used to treat breast cancer patients (~30%) in whom HER-2 is overexpressed and spontaneously homodimerises or forms heterodimers with other HER receptors, especially HER-3. This ligand-independent activation of HER-2 promotes proliferation and survival of tumour cells. Trastuzumab blocks the interaction HER-2/HER-3 and downstream signalling halting the growth of tumour cells. Moreover, trastuzumab induces the antibody-dependent immune cell-mediated cytotoxicity of cancer cells (left side). In the heart, neuregulin-1 (NRG-1) triggers HER-4/HER-4 homodimerisation and HER-4/HER-2 heterodimerisation on cardiomyocytes to induce protective pathways in response to stress. Blockade of cardiac HER-2 by trastuzumab results in the disruption of NRG-1-dependent signaling and consequently in alterations of structure and functions that cause cardiomyocyte death (right side). HER = human epidermal growth factor receptor; NRG = neuregulin. Source: Varricchi et al. 20189 Reproduced with permission from Frontiers.

Several approaches have been proposed to reduce ANT CTX. Beside limiting the cumulative anthracycline doses, the interest of the scientific community has also been focusing on antioxidant drugs.2,3 However, none of these strategies is unanimously recommended, emphasising the need for further studies.8 The use of dexrazoxane has been clinically evaluated in children treated with doxorubicin for acute lymphoblastic leukaemia, resulting in reduced myocardial injury, as indicated by a decreased level of serum troponin T.15,38 Among traditional HF drugs, beta-blockers have been shown to reduce oxidative stress and calcium overload in myocardial cells.39,40 Carvedilol has been shown to have a preventive role against LV dysfunction in patients treated with ANTs reducing the production of ROS, apoptosis of cardiomyocytes and mitochondrial alterations.41–43 In some experimental models of ANT-induced cardiotoxicity, nebivolol was also able to improve LV function, increase nitric oxide (NO) levels and reduce oxidative stress.44,45 Nebivolol, used before ANT-based treatments, also reduced the incidence of LV dysfunction, compared with placebo.46 The renin-angiotensin-aldosterone system also plays a key role in ANT-induced CTX.47 In particular, in patients treated with ANTs, enalapril reduced the incidence of LV dysfunction when compared with placebo.48 In vitro and in vivo experiments demonstrated the cardioprotective effects of angiotensin receptor blockers – candesartan can reduce in vitro ANT cardiotoxicity, while telmisartan can blunt acute LV dysfunction induced by doxorubicin when administered pre- and post-chemotherapy in rats.49 Furthermore, telmisartan can inhibit the production of TNF-alpha and interleukin 6 and can affect the availability of NO.50 It also seems that the co-administration of angiotensin-converting enzyme inhibitors and carvedilol can reduce cardiac damage induced by ANTs.51

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ErbB2 (also known as HER-2/NEU) belongs to the epidermal growth factor receptor (EGFR) family. These receptors can homodimerise or heterodimerise and are phosphorylated upon binding with their ligands, initiating several cellular responses. 52 ErbB2 is overexpressed in 25–30% of breast cancers and this has led to research specifically targeting drugs such as trastuzumab, pertuzumab and lapatinib. 53 Trastuzumab is the prototypical biological drug. It is a humanised monoclonal antibody that targets ErbB2, binding to its extracellular domain IV, and has revolutionised ErbB2+ breast cancer protocols since its introduction in 1998. It can also cause CTX that spans from asymptomatic decreases in LV ejection fraction (LVEF) to congestive HF.1,10,54 Most patients with little or no risk factors can tolerate trastuzumab for long periods of time. Given the importance of this drug in ErbB2+ breast cancer, the Cardiac Safety Study in Patients With HER2 + Breast Cancer (SAFE-HEaRt study) has been designed to evaluate whether anti-HER2 therapies can be given to women with mildly reduced heart function and optimised cardiac therapy and monitoring.55 The mechanisms of CTX induced by ErbB2 blockers have not been fully elucidated (Figure 2). In the heart, neuregulin, secreted from endothelial cells, upon binding to ErbB4 induces the dimerisation of ErbB4 and ErbB2, thus activating protective trophic and pro-survival pathways in response to stress, such as hypertension, hypertrophy, or exposure to ANTs, and it has also been shown that it can modulate cardiomyocyte proliferation in mammalian hearts.9,12,56– 60 The inhibition of the neuregulin-1/Erbb2 axis weakens the myocardium and makes it vulnerable to myocardial injury. Timolati et al demonstrated a role of neuregulin-1 in the modulation of doxorubicin-induced oxidative damage, with an impact on antioxidant enzymes such as glutathione reductase, suggesting that trastuzumab may act as a modulator of ANT-related toxicity.23 The interactions between ANT and trastuzumab have been extensively studied. The coadministration of trastuzumab with ANTs in people with breast cancer, increased ANT toxicity in early trials and is now avoided.61–63 In fact, it has now been shown that anti-HER-2 drugs block the protective mechanisms of HER-2, exacerbating the oxidative damage caused by ANTs.12,64 ErbB2 knockout mice develop dilated cardiomyopathy and show a higher prevalence of cardiomyocyte death when treated with ANT.65 On the other hand, Belmonte et al. demonstrated that overexpression of ErbB2 in the heart reduced ROS levels, increasing the activity of glutathione peroxidase 1 and its co-activating factors such as c-Abl and Arg.66 The same group reported a bidirectional crossregulation between ErbB2 and beta-adrenergic signalling pathways.67 Interestingly, patients treated with trastuzumab, ANTs, or both have been shown to be exposed to reduced risk of LV dysfunction when incidentally administered with beta-blockers.68 Recent data suggest that beta-blockers, such as bisoprolol and metoprolol are not able to fully prevent trastuzumab-induced cardiomyopathy, showing that blockade of beta-1 alone is not sufficient to protect the heart.69,70 While non-selective beta-blockers did not really prove beneficial in the ANT setting, these clinical and experimental findings support their use in the trastuzumab setting.67,71

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Heart Failure and Cancer Figure 3: Mechanism of Action of Checkpoint Inhibitors A

C MHC

TCR

PD-1 PD-L1

Activated T cell B7 CD28

Ipilimumab

B7 CTLA-4

APC

Inhibited T cell

TCR CTLA-4

Nivolumab

Tumour proliferation PD-1

PD-L1

MHC TCR

CTLA-4

PD-1

Ipilimumab

APC

PD-L1

Injured cardiomyocytes

PD-L1

B7 CD28

PD-1

Activated T cell

Nivolumab Pembrolizumab

Atezolizumab Avelumab Durvalumab

Killing of tumour cells

A: Tumour cells escape immune surveillance by promoting checkpoint activation. Tumour cells express the immune checkpoint activator programmed cell death ligand 1 (PD-L1) and produce antigens (blue dots) that are captured by antigen-presenting cells (APCs). These cells present antigens to cytotoxic CD8+ T cells through the interaction of major histocompatibility complex (MHC) molecules and T-cell receptor (TCR). T-cell activation requires costimulatory signals mediated by the interaction between B7 and CD28. Inhibitory signals from cytotoxic T lymphocyteâ&#x20AC;&#x201C; associated protein 4 (CTLA-4) and programmed cell death protein 1 (PD-1) checkpoints dampen T-cell response and promote tumour proliferation. B: Checkpoint inhibitors stimulate T-cell activation. Monoclonal antibodies targeting CTLA-4 (ipilimumab), PD-1 (nivolumab, pembrolizumab), and PD-L1 (atezolizumab, avelumab, durvalumab) block immune inhibitory checkpoints (CTLA-4, PD-1, and PD-L1, respectively) and restore antitumour immune response, resulting in tumour cell death via release of cytolytic molecules (e.g. tumour necrosis factor-alpha, granzyme B, interferon gamma). C: Hypothetical mechanism by which checkpoint inhibitors can promote autoimmune lymphocytic myocarditis. PD-L1 is expressed in human and murine cardiomyocytes, and its expression can increase during myocardial injury. Combination of checkpoint blockade (ipilimumab plus nivolumab) unleashes immune responses and can cause autoimmune lymphocytic myocarditis. Lymphocytes in myocardium and tumours showed clonality of TCR, suggesting that heart and tumours can share antigens (blue dots) recognised by the same T cell clones. Source: Varricchi et al. 201718 Reproduced with permission from Wolters Kluwer Health.

Anti-vascular Endothelial Growth Factor Drugs As seen above, ROS play a central role in the mechanisms of CTX induced by ANTs and by ErbB2 blockers. AMPK, which may have a role in ANT-induced cardiotoxicity, seems to be targeted also by the tyrosine kinase inhibitor sunitinib. Indeed, sunitinib is primarily known as a vascular endothelial growth factor (VEGF) inhibitor, but it is also a multiple tyrosine kinase inhibitor. Among many other kinases (>30), it can inhibit ribosomal S6 kinase, activating the intrinsic apoptotic pathway, and AMPK (usually activated by energetic stress), contributing to the reduction of adenosine triphosphate levels.52,72,73 Our preliminary findings show that CK can also modulate sunitinib actions on the contractile apparatus of cardiomyocytes by regulating oxidative stress.74,75

CTX.78,79 Using a preclinical model of engineered cardiomyocytes (first murine and then human), Truitt et al. demonstrated that sunitinib can induce cardiomyocyte death, decrease the contractile force of the heart and generate spontaneous beating at clinical doses. They also found a correlation between an increase in the afterload and the CTX induced by sunitinib. According to these findings, antihypertensive therapies may be used to reduce the effects of sunitinib.79

Additionally, it seems that sunitinib can prolong the opening time of the mitochondrial permeability transition pore, with consequent swelling and deformation of the mitochondria in murine cardiomyocytes affected by pressure overload.76 Conversely, studies have demonstrated that oxidative phosphorylation is not significantly affected by sunitinib and suggest that its CTX is less frequent than predicted.77

Sorafenib is another tyrosine kinase inhibitor with significant CTX. Most of the information we have on CTX induced by sunitinib and sorafenib comes from two meta-analyses including almost 7,000 patients given sunitinib and 900 patients given sorafenib. These showed that 4.1% of patients treated with sunitinib developed HF, while 1% of patients treated with sorafenib had signs of cardiac dysfunction.80,81 It is important to highlight that both meta-analyses only included retrospective studies. So far, there are few data derived from prospective studies, although Schmidinger et al. demonstrated that three of 14 patients who had a cardiac event and were administered with sorafenib, developed LV dysfunction assessed by significant reduction of LVEF.82

It has been shown that sunitinib damages pericytes and can affect the microvascular circulation of the heart, rather than impair cardiomyocyte functionality directly, and a recent paper has investigated the connection between afterload and sunitinib-induced

Despite the aforementioned studies, the real incidence of CTXinduced by sorafenib is not yet clear and more studies are needed for this reason. Sorafenib can inhibit at least 15 different kinases, such as VEGFR, PDGFR, Raf-1/B-Raf, FLT3 and c-Kit.52,83,84 In addition, a 2018

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Co-morbidities study demonstrated that sorafenib has an intrinsic cardiotoxic effect on cardiomyocytes, impairing calcium homeostasis.85

Immunotherapy Over the past few years, cancer immunotherapies have revolutionised the clinical management of a wide spectrum of solid and haematopoietic malignancies. The forefront of immunotherapy is represented by immune checkpoint inhibitors (ICIs), whose purpose is to inhibit molecules such as cytotoxic-T-lymphocyte-associated antigen 4 (CTLA-4) and of programmed cell death 1 (PD-1) and its ligand PD-L1. CTLA-4, expressed on T cells, competes with CD28 in binding CD80 and/or CD86, expressed on antigen-presenting cells, modulating the amplitude of T-cell activation and showing immunosuppressive activity.86–88 This results in immunosuppression with downmodulation of T helper cell activity and enhancement of regulatory cells.

the most impact. The same authors showed that serum troponin was abnormal in 94% of the cases, highlighting a possible role in early detection of ICI CTX. Instead, measurement of EF may be less useful for surveillance, because EF with myocarditis was normal in half of the cases. In fact, a preserved EF in not reassuring in ICI myocarditis, unlike other types of myocarditis where a normal EF is traditionally considered relatively benign and self-limiting.99 The development of myocarditis in patients treated with ICIs has a solid biological base. In 2001, a seminal paper by Nishimura et al. demonstrated that mice deficient for the CTLA-4 and PD-1 axes presented with autoimmune myocarditis and dilated cardiomyopathy, showing that these molecules can prevent autoimmunity.100 Furthermore, absence of PD-L1, or its inhibition, can worsen the survival from myocarditis, suggesting a role for PD-1/PD-L1 and CTLA-4 in limitation of T cell–mediated autoimmune myocarditis. Interestingly, PD-1 and PD-L1 were observed to be increased in cardiomyocytes from rat hearts subjected to ischaemia-reperfusion.100,101

PD-1, expressed at low levels on T cells, activated natural killer cells, B cells, monocytes, immature Langerhans’ cells and cardiomyocytes, and its ligand PD-L1, constitutively expressed at low levels on both professional and non-professional antigen-presenting cells as well as on non-haematopoietic cells plays a fundamental role in the maintenance of peripheral tolerance and the prevention of autoimmune diseases.89 Monoclonal antibodies targeting CTLA-4 (ipilimumab), PD-1 (nivolumab, pembrolizumab), and PD-L1 (atezolizumab, avelumab, durvalumab) block these immune inhibitory checkpoints and restore the antitumour immune response, leading to tumour cell death through the release of cytolytic molecules, such as tumour necrosis factor-alpha, granzyme B and interferon-gamma (Figure 3).18 However, immune checkpoints play a central role in the maintenance of self-tolerance. Therefore, blocking these pathways can lead to imbalances in immunologic tolerance that results in immune-related adverse events.90 These sideeffects are common, but fortunately in most cases they are reversible and not severe. They include mostly skin manifestations, such as pruritus, rash and vitiligo in 43–45% of patients, but also liver and gastrointestinal events that may occur 6–7 weeks after treatment was initiated. Greater concern is expressed on endocrinopathies, observed in about 6–8% of patients. They are the only immune-related adverse events with a high risk of irreversible toxicity and result from immune infiltration into either the thyroid or pituitary glands, causing thyroiditis or hypophysitis, respectively.91–93

Immunotherapies have been introduced more recently, and in view of the fact that autoimmune myocarditis induced by ICIs has fulminant progression, including immunologists in this cardio-oncologic collaboration appears necessary for better management of ICI CTX.104 At the moment, beyond ICIs, novel monoclonal antibodies targeting several immune checkpoints, and new cancer therapies, such as engineered T cells, cancer vaccines and PI3K inhibitors are being studied and developed.105–108 A thorough cardio-immuno-oncologic collaboration seems fundamental, to the assessment of potential toxicities of current and novel drugs, in clinical as well as in basic research also considering that these drugs are often combined, thus increasing their cardiotoxic potential.99,109

When ICIs were introduced as cancer treatments, little attention was paid to cardiac side-effects. Then, isolated cases of fulminant myocarditis (Figure 3) and other cardiovascular disorders (pericarditis, vasculitis and AV blocks) were reported by several independent groups.19,94–97 The 2018 study by Mahmood et al. is significantly larger than previous reports.98 The authors present a retrospective, multicentre review of myocarditis in 35 patients and show that myocarditis presented early, with a median presentation of more than 30 days after starting ICIs, and 81% presenting within 3 months of treatment initiation. This suggests the importance of a surveillance protocol, especially in the initial phases of therapy when it may have

In addition, novel data point to a direct relationship between cancer and the heart. Indeed, cancer and HF share common mechanisms, risk factors and comorbidities, while several studies have suggested that cancer cachexia can trigger cardiac dysfunction, and that cardiovascular health can predict all-cause mortality in cancer patients.8,110–117 More recently, experimental studies led by Rudolf de Boer have elegantly shown that HF stimulates tumour growth by circulating factors.118 Investigation of the mechanisms and pathways linking HF to cancer is a novel, but very promising field of research that aims to answer exciting questions of whether HF promotes malignancies.111

Suter TM, Ewer MS. Cancer drugs and the heart: importance and management. Eur Heart J 2013;34:1102–11. https://doi. org/10.1093/eurheartj/ehs181; PMID: 22789916. Zamorano JL, Lancellotti P, Rodriguez Muñoz D, et al. 2016 ESC Position Paper on cancer treatments and cardiovascular toxicity developed under the auspices of the ESC. 2016;37:2768–801. https://doi.org/10.1093/eurheartj/ehw211; PMID: 27567406. Armenian SH, Lacchetti C, Barac A, et al. Prevention and monitoring of cardiac dysfunction in survivors of adult cancers: American Society of Clinical Oncology clinical

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Future Perspectives Cardio-oncology is an ever-expanding field of research. In this article we have only discussed the studies conducted on ANTs anti-HER2 drugs and anti-VEGF drugs, but several other drugs (alkylating agents, antimetabolites, proteasome inhibitors, other, tyrosine kinase inhibitors, antimicrotubule agents) can generate LV dysfunction.17 A tight collaboration among cardiologists and oncologists is building up quickly.102,103

practice guideline. J Clin Oncol 2017;35:893–911. https://doi. org/10.1200/JCO.2016.70.5400; PMID: 27918725. Moslehi JJ. Cardiovascular toxic effects of targeted cancer therapies. N Engl J Med 2016;375:1457–67. https://doi. org/10.1056/NEJMra1100265; PMID: 27732808. Kenigsberg B, Wellstein A, Barac A. Left ventricular dysfunction in cancer treatment: is it relevant? JACC Heart Fail 2018;6:87–95. https://doi.org/10.1016/j.jchf.2017.08.024; PMID: 29413379. Guha A, Armanious M, Fradley MG. Update on cardiooncology: Novel cancer therapeutics and associated cardiotoxicities. Trends Cardiovasc Med 2018;29:29–39. https://

doi.org/10.1016/j.tcm.2018.06.001; PMID: 29910109. Babiker HM, McBride A, Newton M, et al. Cardiotoxic effects of chemotherapy: A review of both cytotoxic and molecular targeted oncology therapies and their effect on the cardiovascular system. Crit Rev Oncol Hematol 2018;126:186–200. https://doi.org/10.1016/j.critrevonc.2018.03.014; PMID: 29759560. Ameri P, Canepa M, Anker MS, et al. Cancer diagnosis in patients with heart failure: epidemiology, clinical implications and gaps in knowledge. Eur J Heart Fail 2018;20:879–87. https:// doi.org/10.1002/ejhf.1165; PMID: 29464808.

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associated with immune checkpoint inhibitors: a systematic review and meta-analysis. JAMA Oncol 2018;4: 1721–8. https://doi.org/10.1001/jamaoncol.2018.3923; PMID: 30242316. 105. Brudno JN, Kochenderfer JN. Chimeric antigen receptor T-cell therapies for lymphoma. Nat Rev Clin Oncol 2018;15:31–46. https://doi.org/10.1182/blood-2017-06-793869; PMID: 28857075. 106. De Henau O, Rausch M, Winkler D, et al. Overcoming resistance to checkpoint blockade therapy by targeting pi3k-γ in myeloid cells. Nature 2016;539:443–7. https://doi. org/10.1038/nature20554; PMID: 27828943. 107. Li M, Sala V, De Santis MC, et al. Phosphoinositide 3-kinase gamma inhibition protects from anthracycline cardiotoxicity and reduces tumor growth. Circulation 2018;138:696–711. https://doi.org/10.1161/CIRCULATIONAHA.117.030352; PMID: 29348263. 108. Kaneda MM, Messer KS, Ralainirina N, et al. PI3Kγ 3 is a molecular switch that controls immune suppression. Nature 2016;539:437–42. https://doi.org/10.1038/nature19834; PMID: 27642729. 109. Sharma A, Burridge PW, McKeithan WL, et al. High-throughput screening of tyrosine kinase inhibitor cardiotoxicity with human induced pluripotent stem cells. Sci Transl Med 2017;9:eaaf2584. https://doi.org/10.1126/scitranslmed. aaf2584; PMID: 28202772. 110. Anker MS, von Haehling S, Landmesser U, et al. Cancer and heart failure-more than meets the eye: common risk factors and co-morbidities. Eur J Heart Fail 2018;20:1382–4. https://doi. org/10.1002/ejhf.1252; PMID: 29943887. 111. Bertero E, Canepa M, Maack C, Ameri P. Linking heart failure to cancer. Circulation 2018;138:735–42. https://doi.org/10.1161/ CIRCULATIONAHA.118.033603; PMID: 30359132. 112. Schafer M, Oeing CU, Rohm M, et al. Ataxin-10 is part of a cachexokine cocktail triggering cardiac metabolic dysfunction in cancer cachexia. Mol Metab 2016;5:67–78. https://doi.org/10.1016/j.molmet.2015.11.004; PMID: 26909315. 113. Barkhudaryan A, Scherbakov N, Springer J, Doehner W. Cardiac muscle wasting in individuals with cancer cachexia. ESC Heart Fail 2017;4:458–67. https://doi.org/10.1002/ ehf2.12184; PMID: 29154433. 114. Loncar G, Springer J, Anker M, et al. Cardiac cachexia: hic et nunc. J Cachexia Sarcopenia Muscle 2016;7:246–60. https://doi. org/10.1002/jcsm.12118; PMID: 27386168. 115. Pavo N, Raderer M, Hulsmann M, et al. Cardiovascular biomarkers in patients with cancer and their association with all-cause mortality. Heart 2015;101:1874–80. https://doi. org/10.1136/heartjnl-2015-307848; PMID: 26416836. 116. Anker MS, Ebner N, Hildebrandt B, et al. Resting heart rate is an independent predictor of death in patients with colorectal, pancreatic, and non-small cell lung cancer: results of a prospective cardiovascular long-term study. Eur J Heart Fail 2016;18:1524–34. https://doi.org/10.1002/ejhf.670; PMID: 27910284. 117. Cramer L, Hildebrandt B, Kung T, et al. Cardiovascular function and predictors of exercise capacity in patients with colorectal cancer. J Am Coll Cardiol 2014;64:1310–9. https://doi.org/10.1016/j.jacc.2014.07.948; PMID: 25257631. 118. Meijers WC, Maglione M, Bakker SJ, et al. Heart failure stimulates tumor growth by circulating factors. Circulation 2018;138:678–91. https://doi.org/10.1161/ CIRCULATIONAHA.117.030816; PMID: 29459363.

C A R D I A C FA I L U R E R E V I E W

Co-morbidities

Diet, the Gut Microbiome and Heart Failure Sivadasanpillai Harikrishnan Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India

Abstract The collection of microorganisms that live in coexistence within or on the host body has been referred to as the microbiota. In humans, such cohabitation is mostly seen in the gut, mainly in the colon. The gut microbiome is acquired from the environment and is modified mostly by the diet. There are preliminary data to show that gut microbia can directly influence the pathogenetic disease processes in heart failure (HF). HF leads to bowel wall oedema and regional hypoxia, causing a change in the microbial flora of the gut, which can initiate or perpetuate certain pathogenetic process in HF. The structural component of the microbiota itself, such as lipopolysaccharides or the substances produced by the bacteria, such as trimethylamine N-oxide, is implicated in the pathogenesis of HF. This process is termed as the ‘heart–gut axis’ in HF. Manipulating the gut microbia or targeting products from the microbia may become treatment options for HF in future.

Keywords Heart failure, gut microbia, microbiota, trimethylamine N-oxide, lipopolysaccharide. Disclosure: The author has no conflicts of interest to disclose. Received: 7 November 2018 Accepted: 15 January 2019 Citation: Cardiac Failure Review 2019;5(2):119–22. DOI: https://doi.org/10.15420/cfr.2018.39.2 Correspondence: Sivadasanpillai Harikrishnan, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India. E: drharikrishnan@outlook.com Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

“All diseases begin in the gut.” – Hippocrates (460–370 BC) In recent years many researchers have described the relationship between the gut microbiota and many diseases, including heart disease, hypertension, diabetes and obesity.1,2 Diet is one of the major factors that influence the pattern of the gut microbiota.3 This article discusses how the gut microbiota affects heart failure.

What is the Human Gut Microbiome? The collection of micro-organisms that co-exists within or on the host body has been referred to as the microbiota.1 There are more than 2,000 species of commensal organisms (mostly bacteria) that co-exist with the human body, the vast majority in the gut. A healthy human adult has approximately 100 trillion bacteria in the gut, mostly in the colon.1,4 The gut microbiome is acquired from the environment, it is not genetically acquired, and the gut is usually sterile in the womb. For example, the fetus acquires different microbiota during caesarean section and during vaginal delivery.5 Subsequently, the fetus acquires different types of microbiome depending on diet and the environment to which it is exposed.6,7 The human gut microbiome is dominated by five phyla: Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria and Cerrucomicrobia.1,8 Usually the gut microbiota is stable within the individual and family. In the healthy gut, the anaerobic groups Bacteroidetes and Firmicutes contribute to more than 90% of the total bacterial species.8

What Decides the Pattern of an Individual’s Gut Microbiome? The specific patterns of gut microbiota are called enterotypes.9 An unwelcome change in the gut microbiome is called dysbiosis.10 One of the most important factors that influences the enterotype is the individual’s long‐term diet. For example, diets high in animal protein and fat will show high levels of Bacteroides and low levels of Prevotella (also part of the Bacteroidetes genus).11 On the contrary, diets high in carbohydrates and low in animal protein and fat will have low levels of Bacteroides and high levels of Prevotella. Another example of the diet–gut microbial interaction is found in Japanese people. Their guts contain Bacteroides plebeius, which produces an enzyme that aids in seaweed digestion.12 Other factors that influence the gut microbial pattern other than the diet are environmental changes, hygiene, antibiotic use and disease states.1,6

How the Gut Microbiota Affects the Host The gut microbiome has many functions.13 One of its functions is a protective function via pathogen displacement, nutrient and receptor competition and production of antimicrobial factors.1 The gut microbiota also secretes some vitamins. One of the most important functions of the gut microbiome is metabolic, as it aids in the digestion of food components. For example, gut bacteria are involved in the breakdown of sugars (e.g. glycans, which are complex sugars that cannot be cleaved by any human

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Co-morbidities enzymes) by glycoside hydrolase. Gut microbiota participates in the human digestive process through two main catabolic pathways – saccharolytic or proteolytic.14 Both pathways lead to the production of short-chain fatty acids (SCFAs). The second catabolic pathway also produces toxic molecules such as ammonia, various amines, thiols, phenols and indoles, which are cleared by the kidneys but will accumulate if there is renal dysfunction.1,14,15 It is reasonable to view the microbiome as an ‘organ’ that weighs approximately 1–2 kg, although it is without a distinct structure. The microbiome constantly makes compounds, some of which are absorbed and are biologically active. Thus, it can be considered as an endocrine organ producing biologically active entities that diffuse into the bloodstream and act at distant sites.1 The gut microbiota are separated from the lamina propria by a single layer of intestinal epithelium. The intestinal epithelium deploys a variety of mechanisms to restrict commensal bacteria to the intestinal lumen and to prevent egression of these microbiota to the underlying tissue.16 The gut microbiota in turn have evolved to evade the host’s immune system and circumvent the antimicrobial host response. 16 The intestinal barrier mechanism has a dual role to play – it protects against the invasion of microorganisms and absorption of bacterial toxins, but also enables the absorption of essential products, electrolytes and nutrients.17 The gut microbiota produces many substances that are able to enter the bloodstream and subsequently influence pathobiological processes. The permeability of these substances is dependent on the functional and structural integrity of the mucosal barrier. Potential barrier disruptors include hypoperfusion of the gut, infections, toxins, drugs and other lifestyle factors.17 Sometimes it may be a structural component of the microbiota itself, such as lipopolysaccharides (LPS) or peptidoglycans, that interact with host mucosal surface cells through pattern recognition receptors.1,18 In addition, molecules produced by microbial organisms can also gain entry to cause various effects. Some identified pathways include the trimethylamine N-oxide (TMAO) pathway, the SCFA pathway and the bile acid pathway.1 The precursor of TMAO is l-carnitine or choline, which is present in food substances such as red meat. If a person has a high intake of red meat, TMAO production is increased, which is implicated in the pathogenesis of heart disease.2

How Do We Study the Gut Microbiome? It is not easy to study the gut microbiome because it contains millions of bacteria and thousands of species. There are also fungi and viruses present, which can pose difficulties because their genetic material interferes with the identification of the bacterial genome in question. A further issue with studying the gut microbial genome is that the microbial community is distinct in different regions of the intestine, and also because the genome changes frequently due to horizontal gene transfer.19

is usually more expensive but offers increased resolution, enabling a more specific taxonomic and functional classification.20 Wang et al. explained this as: “16S rDNA sequence attempts to reveal ’who’s there?’ in a given microbial community, while shotgun metagenomic sequencing can be used to answer the complementary question of ’what can they do?’.”21

Association of the Gut Microbiota with Heart Disease There are many recent publications on the association between the gut microbiota and heart disease, especially heart failure.22–26 Changes in the gut microbiota can lead to the development of risk factors for atherosclerotic vascular disease and directly influence pathogenetic disease processes such as acute coronary syndromes and heart failure.27 Obesity is one example. Its pathology is associated with changes in the relative abundance of two dominant bacterial divisions, Bacteroidetes and Firmicutes.28 Obese patients have been shown to display high Firmicutes counts. It has also been found that the obese microbiome has an increased capacity to harvest energy from the diet, and that the obese “trait” is transmissible: colonisation of germ-free mice with an obese microbiota results in a significantly greater increase in total body fat than colonisation with a lean microbiota, with the same diet.29 In addition, hypertension and diabetes have also been found to have associations with specific gut microbial patterns, and researchers have discovered certain links in the pathogenesis of these diseases and bacterial interactions.22,30,31 In a study comparing patients who had coronary heart disease (CHD) with those who did not, it was found that in patients who had CHD, the proportion of the phylum Bacteroidetes was lower, with a higher proportion of Firmicutes.32 Increased TMAO levels were found to be associated with an increased risk of incident major adverse cardiovascular events (MACEs) in a cohort of 4,007 patients who underwent coronary angiography followed up for 3 years.33 In another study, a Cleveland clinic cohort of 530 patients presenting to the emergency department with chest pain showed elevated plasma TMAO levels at presentation that were independently associated with risk of MACEs.34 The Bacteroidetes:Firmicutes ratio is known to be altered in all chronic diseases and therefore may not be a reliable identifier of a particular disease. Raised TMAO levels are implicated in endothelial and smooth muscle cell activation, foam cell formation, and myocardial and renal fibrosis.2 In a recent systematic review and meta-analysis (16 publications, 19,256 patients), elevated concentrations of TMAO and its precursors were associated with increased risks of MACEs and all-cause mortality, independent of traditional risk factors.35 Another meta-analysis and systematic review of 26,167 patients also showed a positive dosedependent association between TMAO plasma levels and increased cardiovascular risk and mortality.36

Association of the Microbiota with Heart Failure The traditional method is culture, but it is tedious and time consuming. Bacterial genomic sequencing is the next most suitable method. One popular method is 16S ribosomal RNA (rRNA) gene amplicon analysis. Metagenomic sequencing, another method that is gaining popularity,

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The gut microbiota is also implicated in the pathogenesis of heart failure (HF). In HF, due to reduced ejection fraction, there is a reduction in intestinal blood flow and low oxygen delivery. This predisposes the gut to the growth of pathogenic types of anaerobic bacteria.37

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Diet, Gut Microbiome and Heart Failure Patients with chronic HF also develop bowel wall oedema due to venous congestion that impedes the absorptive function of the gut and permits bacterial overgrowth in the mucus layer adjacent to the apical surface of the colonic mucosa.36 Increased intestinal permeability, assessed by the sugar cellobiose test, has also been reported in patients with HF, and this increased permeability correlates with right atrial pressure and C-reactive protein levels.38,39 These bacteria produce many harmful substances including TMAO and endotoxin (LPS), which predisposes or leads to worsening of HF. These discoveries have led to the hypothesis of the heart–gut axis of HF (Figure 1).40,41 Higher LPS concentrations have been found in patients with decompensated HF, which correlates with the increased level of bowel wall oedema, as discussed earlier. LPS decreases after ‘re-compensation’. According to Sandek et al., this suggests a cause and effect relationship between the oedematous gut wall, epithelial dysfunction and translocating LPS.42 High TMAO levels are found in patients with HF, which predict higher long-term mortality, even after adjusting for traditional risk factors and cardiorenal indexes.41 TMAO has been found to be a prognostic factor in HF patients, and higher levels predict a poor prognosis at 1-year follow-up. A combination of TMAO and the traditional marker N-terminal pro-brain natriuretic peptide are able to provide additional prognostic information.43 Why do TMAO levels increase to such an extent in HF? The changes in bacterial composition, as discussed earlier, appear to be the primary driver of TMAO levels.25 Renal impairment and changing dietary patterns may also contribute.25 How TMAO affects the pathobiology of HF is not clear. Proposed theories include stimulation of cytokines such as tumour necrosis factor-alpha, which can aggravate myocardial fibrosis, microvascular dysfunction in the heart independent of its proatherosclerotic effects, neurohormonal derangements, and so on, but we do not yet have a clear answer.25

Can We Manipulate the Gut Microbiome to Treat Disease? There are some studies on manipulation of the gut microbiome that give us hope in treating related diseases. Manipulation can be achieved in many ways. We can alter the diet to change the type of microbiota, we can target the chemicals produced by the gut microbiota, or we can directly alter the microbial flora by the addition of probiotics. If we reduce red meat in the diet, we reduce the intake of choline and lecithin, and thereby reduce TMAO, which has a positive impact on the risk of heart disease. For example, changing to a Mediterranean diet has been shown to reduce markers of HF. Another method is to administer nonabsorbable antibiotics that kill specific microbiota and thus alter the overall microbial pattern. Probiotics is another method that can alter the gut’s microbial pattern. Probiotics are live beneficial bacteria (Bifidobacteria, Lactobacilli, Streptococci and non-pathogenic strains of Escherichia coli) that can be ingested to create an appropriate intestinal microbial balance. There are studies using Saccharomyces boulardii in HF that have shown benefit. However, the positive effects of probiotics only apply to a restricted group of microbial species and potential hazards exist, including the possibility of turning these microbiota into opportunistic pathogens in immunocompromised individuals.44

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Figure 1: Hypothesis of the Heart–Gut Axis in Heart Failure HF Decreased cardiac output

Decrease in intestinal perfusion

Venous congestion

Mucosal ischaemia

Bowel wall oedema

Increased bacterial growth (anaerobic, pathogenic strains)

Increased intestinal permeability

Increased bacterial translocation

Increased circulating endotoxins (LPS)

Increased TMAO

Myocardial fibrosis, microvascular dysfunction Aggravates underlying inflammation – cytokine activation, monocyte – macrophage activation, endothelial dysfunction

Worsening of HF HF = heart failure; LPS = lipopolysaccharides; TMAO = trimethylamine N-oxide.

The ongoing Gut-Heart trial has randomised 150 patients with stable HF and a left ventricular ejection fraction <40% to receive the antibiotic rifaximin, the probiotic yeast S boulardii (ATCC 74012) or no treatment in a 1:1:1 fashion. 45 The primary endpoint is ejection fraction at 3 months. The outcome of the trial will shed some light into the possible therapeutic avenues in the future targeting gut microbiome. The last – and very interesting – method that is gaining popularity in the treatment of many gastrointestinal diseases is faecal transplantation. Faecal transplantation from lean volunteers was found to show a benefit in weight reduction as well as a reduction in risk factor levels for HF.46 We are not yet sure of the best method to alter the gut microbiota; however, the most safe and promising option may be to rely on alteration of the diet.

Conclusion Millions of years of co-evolution have created diverse ecosystems of gut microbiota that contribute to the maintenance of human metabolic homeostasis. We are slowly discovering the various ways that these co-habitants work in health and disease. We are therefore not alone – we are linked with our gut microbiota, which controls our systems remotely. Understanding and manipulating the microbiota may hold future answers for health and disease.

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