Discharge risk scoring method for predicting mortality in hospitalized chronic heart failure patients with severe systolic dysfunction

OBJECTIVE: Prognostic risk stratification in heart failure is crucial to guide clinical decision-making.The aim of our study was to develop a prognostic discharge risk score model to predict all-cause mortality for chronic heart failure patients with multiple co-morbidities and severe systolic dysfunction. METHODS AND RESULTS: A multivariable logistic regression model was developed with the use of data on clinical, laboratory, imaging and therapeutic findings of 630 patients with advanced systolic heart failure. A risk score model was developed based on multiplying the beta-coefficient number of each variable in the multivariable model. The model performance was evaluated by concordance index and internally validated by the bootstrapping method. 313 patients (49.7%) of the cohort died during a median follow-up duration of 54 months. Median age was 66 years, 37% were female, 26% had atrial fibrillation and 40% had diabetes mellitus. The mean left ventricular ejection fraction (EF) was 25 +/- 10% and 264 patients (42%) had left ventricular EF < or = 20%. Independent predictors of mortality were older than 70 years, orthopnoea, previous hospitalisations, lack of renin-angiotensin system inhibitor therapy at discharge, hyperuricaemia (>7 mg/dl) and haemoglobin level (<10 g/dL). Discharge risk score identified low-, intermediate- and high-risk individuals with 18%, 40% and 52% mortality rates, respectively. The risk score had a discrimination ability with a concordance index of 0.70. CONCLUSIONS: In a large heart failure cohort, including patients with severe systolic dysfunction and having multiple comorbidities, a simple discharge risk score with non-invasive and easy-to-obtain variables during hospital admission represents a valuable tool for risk assessment.