A novel prognostic index to determine the impact of cardiac conditions and co-morbidities on one-year outcome in patients with heart failure

Abstract

Prognostic stratification is relevant in clinical decision making in heart failure (HF). Predictors identified during hospitalization or in clinical trials may be unrepresentative of HF in the community. The aim of this study was to derive and validate, in different clinical settings, a risk stratification model for the prediction of stable HF outcomes. The study included 807 patients, 350 enrolled at discharge from the hospital (44%), 309 in the outpatient clinic (38%), and 148 in the home-care setting (18%). There were 292 patients in the derivation cohort and 515 in the validation cohort. A multivariate logistic analysis was performed to obtain the CardioVascular Medicine Heart Failure (CVM-HF) index. One-year mortality was 20.8% in the derivation cohort and 20.7% in the validation cohort. The CVM-HF index included cardiac conditions and co-morbidities and stratified the 1-year mortality risk as low (death rate 4%), average (32%), high (63%), and very high (96%). The area under the curve of the receiver-operating characteristic curve was 0.844 (95% confidence interval [CI] 0.779 to 0.89) for the derivation cohort and 0.812 (95% CI 0.76 to 0.86) for the validation cohort. Model performance was equally good in the 3 different HF settings. In a subgroup of 409 patients, the CVM-HF index (area under the curve 0.821, 95% CI 0.79 to 0.89) outperformed the most-used prognostic models (the Charlson index and the Heart Failure Risk Scoring System). In conclusion, the CVM-HF index, a novel prognostic model that is easy to derive and applicable to unselected patients, may represent a valuable tool for the prognostication of stable HF outcomes.