Background: Heart failure (HF) is a prevalent and deadly disease, and preventive strategies focused on at-risk individuals are needed. Current HF prediction models have not examined HF subtypes. We sought to develop and validate risk prediction models for HF with preserved and reduced ejection fraction (HFpEF, HFrEF).
Methods and results: Of 28,820 participants from 4 community-based cohorts, 982 developed incident HFpEF and 909 HFrEF during a median follow-up of 12 years. Three cohorts were combined, and a 2:1 random split was used for derivation and internal validation, with the fourth cohort as external validation. Models accounted for multiple competing risks (death, other HF subtype, and unclassified HF). The HFpEF-specific model included age, sex, systolic blood pressure, body mass index, antihypertensive treatment, and previous myocardial infarction; it had good discrimination in derivation (c-statistic 0.80; 95% confidence interval [CI], 0.78-0.82) and validation samples (internal: 0.79; 95% CI, 0.77-0.82 and external: 0.76; 95% CI: 0.71-0.80). The HFrEF-specific model additionally included smoking, left ventricular hypertrophy, left bundle branch block, and diabetes mellitus; it had good discrimination in derivation (c-statistic 0.82; 95% CI, 0.80-0.84) and validation samples (internal: 0.80; 95% CI, 0.78-0.83 and external: 0.76; 95% CI, 0.71-0.80). Age was more strongly associated with HFpEF, and male sex, left ventricular hypertrophy, bundle branch block, previous myocardial infarction, and smoking with HFrEF (P value for each comparison ≤0.02).
Conclusions: We describe and validate risk prediction models for HF subtypes and show good discrimination in a large sample. Some risk factors differed between HFpEF and HFrEF, supporting the notion of pathogenetic differences among HF subtypes.
Keywords: diastolic heart failure; phenotype; primary prevention; risk factor; systolic heart failure.
© 2016 American Heart Association, Inc.