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American Heart Association, Circulation Research, 2(130), p. 200-209, 2022

DOI: 10.1161/circresaha.121.319595

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Development and Validation of a Long-Term Incident Heart Failure Risk Model

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

Background: Average lifetime risk for heart failure (HF) is high but differs significantly across and within sex-race groups. No models for estimating long-term risk for HF exist, which would allow for earlier identification and interventions in high-risk subsets. The authors aim to derive 30-year HF risk equations. Methods: Adults between the ages of 20 to 59 years and free of cardiovascular disease at baseline from 5 population-based cohorts were included. Among 24 838 participants (55% women, 25% Black based on self-report), follow-up consisted of 599 551 person-years. Sex- and race-specific 30-year HF risk equations were derived and validated accounting for competing risk of non-HF death. HF was based on a clinical diagnosis. Model discrimination and calibration were assessed using 10-fold cross-validation. Finally, the model was applied to varying risk factor patterns for systematic examination. Results: The rate of incident HF was 4.0 per 1000 person-years. Harrell C statistics were 0.82 (0.80–0.83) and 0.84 (0.82–0.85) in White and Black men and 0.84 (0.82–0.85) and 0.85 (0.83–0.87) in White and Black women, respectively. Hosmer-Lemeshow calibration was acceptable, with χ 2 <30 in all subgroups. Risk estimation varied across sex-race groups: for example, in an average 40-year-old nonsmoker with an untreated systolic blood pressure of 140 mm Hg and body mass index of 30 kg/m 2 , risk was estimated to be 22.8% in a Black man, 13.7% in a White man, 13.0% in a Black woman, and 12.1% in a White woman. Conclusions: Sex- and race-specific equations for prediction of long-term risk of HF demonstrated high discrimination and adequate calibration.