Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model

A predictive model of mortality in heart failure may be useful for clinicians to improve communication with and care of hospitalized patients.

To identify predictors of mortality and to develop and to validate a model using information available at hospital presentation.

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.

All-cause 30-day and 1-year mortality.

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 P<.001), and hyponatremia (P<.01). Comorbid conditions associated with mortality included cerebrovascular disease (30-day mortality odds ratio [OR], 1.43; 95% confidence interval [CI], 1.03-1.98; P =.03), chronic obstructive pulmonary disease (OR, 1.66; 95% CI, 1.22-2.27; P =.002), hepatic cirrhosis (OR, 3.22; 95% CI, 1.08-9.65; P =.04), dementia (OR, 2.54; 95% CI, 1.77-3.65; P<.001), and cancer (OR, 1.86; 95% CI, 1.28-2.70; P =.001). A risk index stratified the risk of death and identified low- and high-risk individuals. Patients with very low-risk scores (< or =60) had a mortality rate of 0.4% at 30 days and 7.8% at 1 year. Patients with very high-risk scores (>150) 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.

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.