Phenomapping Heart Failure with Preserved Ejection Fraction Using Machine Learning Cluster Analysis: Prognostic and Therapeutic Implications.

Journal: Heart failure clinics
Published Date:

Abstract

Heart failure with preserved ejection fraction (HFpEF) is characterized by a high rate of hospitalization and mortality (up to 84% at 5 years), which are similar to those observed for heart failure with reduced ejection fraction (HFrEF). These epidemiologic data claim for the development of specific and innovative therapies to reduce the burden of morbidity and mortality associated with this disease. Compared with HFrEF, which is due to a primary myocardial damage (eg ischemia, cardiomyopathies, toxicity), a heterogeneous etiologic background characterizes HFpEF. The authors discuss these phenotypes and specificities for defining therapeutic strategies that could be proposed according to phenotypes.

Authors

  • Elena Galli
  • Corentin Bourg
    University of Rennes, CHU Rennes, INSERM, LTSI-UMR 1099, Rennes F-35000, France.
  • Wojciech Kosmala
    Cardiology Department, Wroclaw Medical University, Wroclaw, Poland; Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute, Melbourne, Australia. Electronic address: wojciech.kosmala@umed.wroc.pl.
  • Emmanuel Oger
    Department of Statistics, University of Rennes, Rennes, France.
  • Erwan Donal