The Pooled Cohort Equations to Prevent HF predicted 5-year incident heart failure with excellent discrimination in White adults (C-statistic 0.82) and adequate in Black adults (C-statistic 0.69).
Cohort (n=31,256)
Yes
Does the Pooled Cohort Equations to Prevent HF tool accurately predict incident HF in a real-world, electronic health record-based primary prevention cohort?
The Pooled Cohort Equations to Prevent HF tool provides excellent discrimination for predicting 5-year incident HF in White adults and adequate discrimination in Black adults within a real-world EHR cohort.
Effect estimate: C-statistic 0.82 (95% CI 0.79-0.86)
Background: Guidelines recommend identification of individuals at risk for heart failure (HF). However, implementation of risk-based prevention strategies requires validation of HF-specific risk scores in diverse, real-world cohorts. Therefore, our objective was to assess the predictive accuracy of the Pooled Cohort Equations to Prevent HF within a primary prevention cohort derived from the electronic health record. Methods: We retrospectively identified patients between the ages of 30 to 79 years in a multi-center integrated healthcare system, free of cardiovascular disease, with available data on HF risk factors, and at least 5 years of follow-up. We applied the Pooled Cohort Equations to Prevent HF tool to calculate sex and race-specific 5-year HF risk estimates. Incident HF was defined by the International Classification of Diseases codes. We assessed model discrimination and calibration, comparing predicted and observed rates for incident HF. Results: Among 31 256 eligible adults, mean age was 51.4 years, 57% were women and 11% Black. Incident HF occurred in 568 patients (1.8%) over 5-year follow-up. The modified Pooled Cohort Equations to Prevent HF model for 5-year risk prediction of HF had excellent discrimination in White men (C-statistic 0.82 95% CI, 0.79–0.86) and women (0.82 0.78–0.87) and adequate discrimination in Black men (0.69 0.60–0.78) and women (0.69 0.52–0.76). Calibration was fair in all race-sex subgroups (χ 2 <20). Conclusions: A novel sex- and race-specific risk score predicts incident HF in a real-world, electronic health record-based cohort. Integration of HF risk into the electronic health record may allow for risk-based discussion, enhanced surveillance, and targeted preventive interventions to reduce the public health burden of HF.
Bavishi et al. (Fri,) conducted a cohort in Heart failure (n=31,256). Pooled Cohort Equations to Prevent HF was evaluated on Incident HF (C-statistic 0.82, 95% CI 0.79-0.86). The Pooled Cohort Equations to Prevent HF predicted 5-year incident heart failure with excellent discrimination in White adults (C-statistic 0.82) and adequate in Black adults (C-statistic 0.69).