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Risk Factors for Heart Failure with Preserved or Reduced Ejection Fraction Among Medicare Beneficiaries: Application of Competing Risks Analysis and Gradient Boosted Model

Authors Lee MP, Glynn RJ, Schneeweiss S, Lin KJ, Patorno E, Barberio J, Levin R, Evers T, Wang SV, Desai RJ

Received 12 March 2020

Accepted for publication 16 May 2020

Published 15 June 2020 Volume 2020:12 Pages 607—616


Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Editor who approved publication: Professor Vera Ehrenstein

Moa P Lee,1,2 Robert J Glynn,1 Sebastian Schneeweiss,1 Kueiyu Joshua Lin,1,3 Elisabetta Patorno,1 Julie Barberio,1 Raisa Levin,1 Thomas Evers,4 Shirley V Wang,1 Rishi J Desai1

1Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA; 2Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA; 3Department of Medicine, Massachusetts General Hospital & Harvard Medical School, Boston, MA, USA; 4Bayer AG, Wuppertal, Germany

Correspondence: Rishi J Desai
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 1620 Tremont Street, Boston, MA 02120, USA
Tel +1 617-278-0932
Fax +1 617-232-8602

Background: The differential impact of various demographic characteristics and comorbid conditions on development of heart failure (HF) with preserved (pEF) and reduced ejection fraction (rEF) is not well studied among the elderly.
Methods: Using Medicare claims data linked to electronic health records, we conducted an observational cohort study of individuals ≥ 65 years of age without HF. A Cox proportional hazards model accounting for competing risk of HFrEF and HFpEF incidence was constructed. A gradient-boosted model (GBM) assessed the relative influence (RI) of each predictor in the development of HFrEF and HFpEF.
Results: Among 138,388 included individuals, 9701 developed HF (incidence rate = 20.9 per 1000 person-years). Males were more likely to develop HFrEF than HFpEF (HR = 2.07, 95% CI: 1.81– 2.37 vs. 1.11, 95% CI: 1.02– 1.20, P for heterogeneity < 0.01). Atrial fibrillation and pulmonary hypertension had stronger associations with the risk of HFpEF (HR = 2.02, 95% CI: 1.80– 2.26 and 1.66, 95% CI: 1.23– 2.22) while cardiomyopathy and myocardial infarction were more strongly associated with HFrEF (HR = 4.37, 95% CI: 3.21– 5.97 and 1.94, 95% CI: 1.23– 3.07). Age was the strongest predictor across all HF subtypes with RI from GBM > 35%. Atrial fibrillation was the most influential comorbidity for the development of HFpEF (RI = 8.4%) while cardiomyopathy was the most influential comorbidity for the development of HFrEF (RI = 20.7%).
Conclusion: These findings of heterogeneous relationships between several important risk factors and heart failure types underline the potential differences in the etiology of HFpEF and HFrEF.

Keywords: heart failure, epidemiology, risk factors, LVEF, HEpEF, HFrEF, competing risks, GBM

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