A novel risk score model for predicting mortality in heart failure with preserved ejection fraction: Insights from the CURE-HF Registry-ApHAC score.

aimsTo create a simple risk score model to predict post-discharge mortality in patients with heart failure with preserved ejection fraction (HFpEF) after treatment for acute decompensated heart failure (HF). METHODS AND

resultsThis was a post-hoc analysis from the CURE-HF registry, which was a prospective multi-center cohort study conducted in Japan between July 2014 and March 2019. We included 378 consecutive patients with HFpEF (left ventricular ejection fraction ≥50%) who were followed for two years. The total cohort was randomly divided into two cohorts: the derivation (n = 278) and the validation (n = 100) cohort. The primary endpoint was all-cause mortality within two years. Logistic regression models were used to evaluate the associations between covariates and the primary endpoint, and to produce the risk score model. C-statistics were calculated to assess the discriminative ability of the derived model. The median age was 83 years, and 52% of the patients were female. In total, 97 patients died within two years. No significant differences were observed between the derivation and validation cohorts in baseline characteristics. On multivariable logistic regression analysis with backward stepwise variable selection, the following variables were selected as the components of the risk score model: age, prior HF admission, serum albumin, and creatinine. The model enabled stratification of mortality rates across thirds, and the average predicted versus observed probabilities of death for the low-, intermediate-, and high-risk groups were 8% vs. 9%, 23% vs. 21%, and 46% vs. 49%, respectively. The c-statistic of the derived model in the validation cohorts was 0.764, indicating a good discrimination of the primary endpoint.

conclusionsWe developed a simple risk score model for predicting two-year mortality in patients with HFpEF. This score model may be useful in guiding decisions regarding close follow-up, advanced therapies, or palliative care for these patients.