Abstract

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.