4.7 Article

10-Year Risk Equations for Incident Heart Failure in the General Population

Journal

JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
Volume 73, Issue 19, Pages 2388-2397

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jacc.2019.02.057

Keywords

epidemiology; heart failure; primary prevention; risk factor

Funding

  1. National Institutes of Health's (NIH's) National Center for Advancing Translational Sciences [KL2TR001424]
  2. NIH/National Heart, Lung, and Blood Institute (NHLBI) [R21 HL085375]
  3. Netherlands Heart Foundation (CVON DOSIS) [2014-40]
  4. Netherlands Heart Foundation (CVON RED-CVD) [2017-11]
  5. Netherlands Heart Foundation (CVON SHE-PREDICTS-HF) [2017-21]
  6. Jackson State University [HHSN268201800013I]
  7. Tougaloo College [HHSN268201800014I]
  8. Mississippi State Department of Health [HHSN268201800015I/HHSN26800001]
  9. University of Mississippi Medical Center from the NHLBI [HHSN268201800010I, HHSN268201800011I, HHSN268201800012I]
  10. National Institute for Minority Health and Health Disparities (NIMHD)
  11. AstraZeneca
  12. Abbott
  13. Bristol-Myers Squibb
  14. Novartis
  15. Roche
  16. Trevena
  17. Thermo Fisher
  18. Actelion
  19. Corvia
  20. National Institutes of Health [U01HL125511-01A1, U10HL110312, R01AG045551-01A1]
  21. Akros
  22. Amgen
  23. Bayer
  24. GlaxoSmithKline
  25. Gilead
  26. InnoLife
  27. Luitpold/American Regent
  28. Medtronic
  29. Merck

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BACKGROUND Primary prevention strategies to mitigate the burden of heart failure (HF) are urgently needed. However, no validated risk prediction tools are currently in use. OBJECTIVES This study sought to derive 10-year risk equations of developing incident HF. METHODS Race-and sex-specific 10-year risk equations for HF were derived and validated from individual-level data from 7 community-based cohorts with at least 12 years of follow-up. Participants who were recruited between 1985 and 2000, between 30 to 79 years, and were free of cardiovascular disease at baseline were included to create a pooled cohort (PC) and were randomly split for derivation and internal validation. Model performance was also assessed in 2 additional cohorts. RESULTS In the derivation sample of the PC (n = 11,771), 58% were women, 22% were black with a mean age of 52 +/- 12 years, and HF occurred in 1,339 participants. Predictors of HF included in the race-sex-specific models were age, blood pressure (treated or untreated), fasting glucose (treated or untreated), body mass index, cholesterol, smoking status, and QRS duration. The PC equations to Prevent HF model had good discrimination and strong calibration in internal and external validation cohorts. A web-based tool was developed to facilitate clinical application of this tool. CONCLUSIONS The authors present a contemporary analysis from 33,010 men and women demonstrating the utility of the sex-and race-specific 10-year PC equations to Prevent HF risk score, which integrates clinical parameters readily available in primary care settings. This tool can be useful in risk-based decision making to determine who may merit intensive screening and/or targeted prevention strategies. (c) 2019 by the American College of Cardiology Foundation.

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