Predicting heart failure outcome from cardiac and comorbid conditions: the 3C-HF score

Abstract

Background: Prognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF outcome have multiple limitations. We developed a simple risk stratification model, based on routinely available clinical information including comorbidities, the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause 1-year mortality in HF patients.

Methods: We recruited in a cohort study 6274 consecutive HF patients at 24 Cardiology and Internal Medicine Units in Europe. 2016 subjects formed the derivation cohort and 4258 the validation cohort. We entered information on cardiac and comorbid candidate prognostic predictors in a multivariable model to predict 1-year outcome.

Results: Median age was 69 years, 35.8% were female, 20.6% had a normal ejection fraction, and 65% had at least one comorbidity. During 5861 person-years follow-up, 12.1% of the patients met the study end-point of all-cause death (n=750) or urgent transplantation (n=9). The variables that contributed to outcome prediction, listed in decreasing discriminating ability, were: New York Heart Association class III-IV, left ventricular ejection fraction <20%, no beta-blocker, no renin-angiotensin system inhibitor, severe valve heart disease, atrial fibrillation, diabetes with micro or macroangiopathy, renal dysfunction, anemia, hypertension and older age. The C statistic for 1-year all-cause mortality was 0.87 for the derivation and 0.82 for the validation cohort.

Conclusions: The 3C-HF score, based on easy-to-obtain cardiac and comorbid conditions and applicable to the 1-year time span, represents a simple and valuable tool to improve the prognostic stratification of HF patients in daily practice.