Incident Heart Failure Prediction in the Elderly

Abstract

Despite the rising heart failure (HF) incidence and aging United States population, there are no validated prediction models for incident HF in the elderly population. We sought to develop a new prediction model for 5-year risk of incident HF among older persons. Proportional hazards models were used to assess independent predictors of incident HF, defined as hospitalization for new onset HF, in 2935 elderly participants without baseline HF enrolled in the Health ABC study (73.6±2.9 years, 47.9% males, 58.6% whites). A prediction equation was developed and internally validated by bootstrapping, allowing the development of a 5-year risk score. Incident HF developed in 258 (8.8%) participants during 6.5±1.8 years of follow-up. Independent predictors of incident HF included age, history of coronary disease and smoking, baseline systolic blood pressure and heart rate, serum glucose, creatinine, and albumin levels, and left ventricular hypertrophy. The Health ABC HF model had a c-statistic 0.73 in the derivation dataset, 0.72 by internal validation (optimism-corrected), and good calibration (goodness-of-fit χ2 6.24, p=0.621). A simple point score was created to predict incident HF risk into four risk groups corresponding to 20% 5-yr risk. The actual 5-year incident HF rates in these groups were 2.9%, 5.7%, 13.3%, and 36.8% respectively. The Health ABC HF prediction model uses common clinical variables to predict incident HF risk in the elderly, an approach that may be used to target and treat high-risk individuals.