Predictive Accuracy of Heart Failure-Specific Risk Equations in an Electronic Health Record-Based Cohort

Circ Heart Fail. 2020 Nov;13(11):e007462. doi: 10.1161/CIRCHEARTFAILURE.120.007462. Epub 2020 Oct 23.

Abstract

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 (χ2<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.

Keywords: cardiology; cardiovascular diseases; health; heart failure; prevention.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • African Americans
  • Aged
  • Decision Support Techniques*
  • Electronic Health Records*
  • Female
  • Health Status Indicators*
  • Heart Disease Risk Factors
  • Heart Failure / diagnosis
  • Heart Failure / ethnology
  • Heart Failure / prevention & control*
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Primary Prevention*
  • Race Factors
  • Retrospective Studies
  • Risk Assessment
  • Sex Factors
  • Time Factors
  • Whites
  • Young Adult