Distinct Comorbidity Clusters in Patients With Acute Heart Failure

Values are % (n), mean ± SD or median (Q1-Q3), unless otherwise indicated.

ACE = angiotensin-converting enzyme; AF = atrial fibrillation; ARB = angiotensin receptor blocker; BMI = body max index; CKD = chronic kidney disease; EF = ejection fraction; eGFR = estimated glomerular filtration rate; freq = frequency; GDF = growth differentiation factor; HF = heart failure; HFpEF = heart failure with preserved ejection fraction; LVEF = left ventricular ejection fraction; MRA = mineralocorticoid receptor antagonist; NT-proBNP = N-terminal pro–B-type natriuretic peptide.

Results of Cox regression analysis for the combined outcome of all-cause mortality or rehospitalization due to heart failure (HHF) or renal failure and all-cause death alone through day 180, and competing risk analysis for adjudicated HHF or renal failure through day 180. Model 1 was the univariate analysis. Model 2 adjusted for model 1 plus age and sex. Model 3 adjusted for model 2 plus NYHA functional class 1 month before inclusion, region of origin, previous hospitalization for HF, and NT-proBNP levels. Bold indicates significant P values.

Ref. = Reference; other abbreviations as in Table 1.

Results of Cox regression for the combined outcome of all-cause mortality or HHF or renal failure and all-cause mortality through day 180. Model 1 stratified analysis within multimorbidity groups according to their treatment allocation (serelaxin or placebo). Model 2 adjusted for model 1 plus age and sex. Model 3 adjusted for model 2 plus NYHA functional class 1 month before inclusion, region of origin, previous hospitalization for HF (yes/no), and HFrEF vs. HfpEF. Bold indicates significant P values.

Abbreviations as in Tables 1 and 2.

Authors and Disclosures

Karla Arevalo Gomez, MD, MSC,^a,* Jasper Tromp, MD, PHD,^a,b,c,* Sylwia M. Figarska, PHD,^a Iris E. Beldhuis, MD,^a Gad Cotter, MD,^d,e Beth A. Davison, PHD,^d,e G. Michael Felker, MD,^f Claudio Gimpelewicz, MD,^g Barry H. Greenberg, MD,^h Carolyn S.P. Lam, MD, PHD,^a,i Adriaan A. Voors, MD, PHD,^a Marco Metra, MD,^j John R. Teerlink, MD,^k Peter van der Meer, MD, PHD^a

From the ^aDepartment of Cardiology, University Medical Centre Groningen, University of Groningen, the Netherlands; ^bSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore; ^cDuke-NUS Medical School, Singapore; ^dMomentum Research, Inc, Durham, North Carolina, USA; ^eInserm U 942 (Cardiovascular Markers in Stress Conditions), Hopital Lariboisière, Paris, France; ^fDivision of Cardiology, Duke University School of Medicine, Durham, North Carolina, USA; ^gNovartis Pharma AG, Basel, Switzerland; ^hDivision of Cardiology, University of California-San Diego, San Diego, California, USA; ⁱNational Heart Centre Singapore and Duke-National University of Singapore; ^jCardiology, ASST Spedali Civili and Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy; and the ^kSection of Cardiology, San Francisco Veterans Affairs Medical Center and School of Medicine, University of California-San Francisco, San Franscisco, California, USA.

The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the Author Center. * Drs Arevalo and Tromp contributed equally to this work.

FUNDING SUPPORT AND AUTHOR DISCLOSURES This study was funded by the PROMINENT project (funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sk³odowska-Curie grant agreement number 754425). Dr Tromp is supported by the National University of Singapore Startup grant, the tier 1 grant from the ministry of education, and the CSIRG New Investigator Grant from the National Medical Research Council; has received consulting or speaker fees from Daiichi Sankyo, Boehringer Ingelheim, Roche Diagnostics, and Us2.ai; and owns patent US-10702247-B2 unrelated to the present work. Drs Cotter and Davison are employees of Momentum Research, Inc, which has received grants from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics Inc, Corteria Pharmaceuticals, Roche Diagnostics Inc, Sanofi, Windtree Therapeutics Inc, and XyloCor Therapeutics. Dr Felker has received research grants from the National Heart, Lung, and Blood Institute, the American Heart Association, Amgen, Bayer, BMS, Merck, Cytokinetics, and CSL-Behring; has acted as a consultant to Novartis, Amgen, BMS, Cytokinetics, Medtronic, Cardionomic, Boehringer Ingelheim, American Regent, Abbott, AstraZeneca, Reprieve, Myovant, Sequana, Windtree Therapeutics, and Whiteswell; and has served on clinical endpoint committees/data safety monitoring boards for Amgen, Merck, Medtronic, EBR Systems, VWave, LivaNova, Siemens, and Rocket Pharma. Dr Gimpelewicz is an employee of Novartis. Dr Greenberg is a consultant for or on the advisory board of AstraZeneca, Bayer, Ionis, Merck, Mesoblast, and Tenaya; and has been on the Data Safety Monitoring Board of ACI, Axon, AstraZeneca, Bayer, Cytokinetics, Boehringer Ingelheim, EBR Systems, Faraday, Inventiva, Impulse Dynamics, Ionis, Salubris, Vifor, Viking, and Windtree. Dr Lam is supported by a Clinician Scientist Award from the National Medical Research Council of Singapore; has received research support from Bayer and Roche Diagnostics; has served as consultant or on the Advisory Board/Steering Committee/Executive Committee for Actelion, Alleviant Medical, Allysta Pharma, Amgen, AnaCardio AB, Applied Therapeutics, Astra- Zeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Cytokinetics, Darma Inc, EchoNous Inc, Eli Lilly, Impulse Dynamics, Ionis Pharmaceutical, Janssen Research & Development LLC, Medscape/ WebMD Global LLC, Merck, Novartis, Novo Nordisk, ProSciento Inc, Radcliffe Group Ltd, Roche Diagnostics, Sanofi, Siemens Healthcare Diagnostics, and Us2.ai; and serves as co-founder and nonexecutive director of Us2.ai. Dr Voors has received research support and/or has been a consultant for Amgen, AstraZeneca, Bayer AG, Boehringer Ingelheim, Cytokinetics, Merck, MyoKardia, Novo Nordisk, Novartis, and Roche Diagnostics. Dr Metra received personal fees of minimal amounts in the last 3 years from Actelion, Amgen, LivaNova, and Vifor pharma as a member of Executive or Data Monitoring Committees of sponsored clinical trials; and from AstraZeneca, Abbott Vascular, Bayer, Boehringer Ingelheim, and Edwards Therapeutics for participation on advisory boards and/or speeches at sponsored meetings. Dr Teerlink has received research support and/or has been a consultant for Amgen, AstraZeneca, Bayer AG, Boehringer Ingelheim, Bristol Myers Squibb, Cytokinetics, Medtronic, Merck, Novartis, Servier, and Windtree Therapeutics. Dr van der Meer received grant support and/or consultancy fees from Novartis, Pharma Nord, Pfizer, Ionis, Astra Zeneca, Vifor Pharma, Pharmacosmos, BridgeBio, and Novo Nordisk. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

ADDRESS FOR CORRESPONDENCE: Prof Dr Peter van der Meer, Department of Cardiology, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, the Netherlands. E-mail: p.van.der. meer@umcg.nl.

Perspectives

COMPETENCY IN PATIENT CARE AND PROCEDURAL SKILLS: HF frequently co-occurs with multiple comorbidities. Multimorbidity is not random. A better understanding of the unique multimorbidity patterns in AHF may improve personalized treatment allocation, clinical trial design, and help plan health care services. We performed an LCA to delineate multimorbidity groups. The aim of this analysis was not to create a novel prediction model for outcomes in AHF. This method is unbiased and data-driven and can identify novel, potentially “hidden” patterns that are obscured due to the broad constellation of characteristics of these patients. Altogether, the results observed highlight that the distinct combination of multiple comorbidities follows a pattern and affects the outcome and treatment response of patients with AHF.

TRANSLATIONAL OUTLOOK: The present study delves into the complexities of multimorbidity groups and their implications on the outcome and treatment response of patients with AHF. Our results are based on a post hoc analysis of a clinical trial, which inherently may introduce biases. Although efforts have been made to validate the results using an independent cohort, it remains imperative to prospectively validate these findings in a clinical trial setting, in which the impact of comorbidities on patient outcomes is a critical consideration in the study design and planning. By considering such factors in future trials, we may potentially identify effective therapeutic interventions for specific populations of patients. Conducting further research in this direction can pave the way for a more nuanced understanding of multimorbidity and its role in identifying responders to therapies, thereby advancing both personalized medicine and scientific inquiry.