Objective: To determine whether easily obtained clinical parameters serve as predictors of survival in patients with congestive heart failure. Several scoring systems to predict heart failure survival have been developed; however, many of these deal principally with transplant recipients or do not account for a patient's response to therapy.
Methods: A total of 680 patients with an ejection fraction of less than 40% were included in the analysis. Baseline assessments were performed and treatment regimens were identified; patients were then followed for up to 5 years. Univariate and multivariate Cox regression models were used to determine clinically important predictors of survival. Kaplan-Meier survival functions for patients with and without the prognostic variable were constructed and mortality was calculated at 1 year and 5 years.
Results: Ejection fraction improvement at 6 months, diabetes mellitus, age, serum creatinine, and blood urea nitrogen (BUN) were significant predictors for survival in the univariate model. Ejection fraction improvement, age, and BUN were significant predictors in the multivariate model. These findings were used to construct a model for predicting patient mortality. Improved ejection fraction (>15 ejection fraction units) gave a 1-year mortality of 2% and a 5-year mortality of 11%. Mortality rates according to patient age and BUN levels were also calculated.
Conclusion: Ejection fraction improvement was the most important predictor for survival in patients with systolic dysfunction; monitoring ejection fraction changes through repeat echocardiograms has important prognostic value. In patients without ejection fraction improvement, age and renal function are important survival determinants.
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