Predicting Mortality Among Patients Hospitalized for Heart Failure

CONTEXT: A predictive model of mortality in heart failure may be useful for clinicians to improve communication with and care of hospitalized patients. OBJECTIVES: To identify predictors of mortality and to develop and to validate a model using information available at hospital presentation. DESIGN, SETTING, AND PARTICIPANTS: Retrospective study of 4031 community-based patients presenting with heart failure at multiple hospitals in Ontario, Canada (2624 patients in the derivation cohort from 1999-2001 and 1407 patients in the validation cohort from 1997-1999), who had been identified as part of the Enhanced Feedback for Effective Cardiac Treatment (EFFECT) study. MAIN OUTCOME MEASURES: All-cause 30-day and 1-year mortality. RESULTS: The mortality rates for the derivation cohort and validation cohort, respectively, were 8.9% and 8.2% in hospital, 10.7% and 10.4% at 30 days, and 32.9% and 30.5% at 1 year. Multivariable predictors of mortality at both 30 days and 1 year included older age, lower systolic blood pressure, higher respiratory rate, higher urea nitrogen level (all P150) had a mortality rate of 59.0% at 30 days and 78.8% at 1 year. Patients with higher 1-year risk scores had reduced survival at all times up to 1 year (log-rank, P<.001). For the derivation cohort, the area under the receiver operating characteristic curve for the model was 0.80 for 30-day mortality and 0.77 for 1-year mortality. Predicted mortality rates in the validation cohort closely matched observed rates across the entire spectrum of risk. CONCLUSIONS: Among community-based heart failure patients, factors identifiable within hours of hospital presentation predicted mortality risk at 30 days and 1 year. The externally validated predictive index may assist clinicians in estimating heart failure mortality risk and in providing quantitative guidance for decision making in heart failure care.