Abstract TH963: Performance of PREVENT-HF Risk Equations across HFpEF vs HFrEF
Abstract
Background: The recent PREVENT-HF risk equations were developed to estimate 10-year risk of overall HF. While HF with preserved vs reduced ejection fraction (HFpEF; HFrEF) have common risk factors, distinct differences in risk conferred by older age, obesity, and coronary artery disease are known. In this context, we sought to evaluate the performance of PREVENT-HF equations relative to HFpEF vs HFrEF. Methods: We examined participants from 4 pooled community-based cohort studies: the Multi-Ethnic Study of Atherosclerosis (MESA), Framingham Heart Study (FHS) offspring exam 6, Cardiovascular Heart Study (CHS), and Prevention of Renal and Vascular End-stage Disease (PREVEND) study. We excluded those with ages <30 and >79 years, prevalent HF, prevalent CVD, and missing key clinical information. We compared the performance of the PREVENT-HF equation in predicting incident HFpEF vs HFrEF at 10 years using Uno’s C-statistics and area under receiver operating characteristic (AUROC). Results: Among 22,061 participants (age 59 ± 14 years, 54% women, BMI 27 ± 5 kg/m 2 ), 322 developed HFpEF and 464 HFrEF during a median follow-up of 10 years. The PREVENT-HF risk equation performed well for both HFpEF (c-statistic 0.81, 95% CI 0.80-0.83) and HFrEF (c-statistic 0.78 (95% CI 0.76-0.80), with similar improvement compared with age and sex alone (HFpEF: c-statistic 0.78, 95% CI 0.76-0.80; HFrEF: c-statistic 0.75, 95% CI 0.73-0.76, P<0.001 for delta for both). The AUROC remained stable across 1-10 years demonstrating consistently strong discrimination for both HFpEF and HFrEF. Time-dependent AUCs were generally higher for HFpEF compared with HFrEF, indicating slightly better discrimination for HFpEF across all time horizons ( Figure ). Conclusions: Our findings demonstrate overall similar performance of the PREVENT-HF risk model with respect to HFpEF and HFrEF. Future studies on subtype-specific risk models may improve upon current risk prediction tools for overall HF.
Article Details
Authors (11)
Juhi Parekh
Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
Louisa Mounsey
Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
Pedro Ribeiro
Chiadi Ndumele
JOHNS HOPKINS HOSPITAL, Silver Spring, Maryland, United States
Norrina Allen
NORTHWESTERN UNIVERSITY, Chicago, Illinois, United States
Bruce Psaty
University of Washington, Seattle, WA, USA.
JORGE KIZER
Univ California San Francisco, Kentfield, California, United States
Daniel Levy
Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
Rudolf De Boer
Erasmus MC, Rotterdam, Netherlands
Sadiya Khan
Northwestern University, Chicago, Illinois, United States
Jennifer Ho
Harvard Medical School, Newton, Massachusetts, United States