Clinical Predictors of In‐Hospital Mortality in Acutely Decompensated Heart Failure—Piecing Together the Outcome Puzzle

Abstract

The substantial public health impact of hospitalization for acute decompensated heart failure, from an economic and clinical perspective, has generated substantial interest in understanding predictors of risk in this syndrome. Utilization of classification and regression tree (CART) analysis on the Acute Decompensated Heart Failure National Registry (ADHERE) dataset has provided important risk stratification from readily available clinical variables. Increasingly, high-risk patients were identified by combination of blood urea nitrogen level of 43 mg/dL, serum creatinine level of 2.75 mg/dL, and systolic blood pressure less than 115 mm Hg, which were all independent predictors of high risk for in-hospital mortality. On the basis of these 3 variables, acutely decompensated heart failure patients can be readily stratified into groups at low, intermediate, and high risk for in-hospital mortality, with mortality risks ranging from 2.1% to 21.9%. Although risk stratification alone cannot improve outcomes, identification of patients at high and low risk may improve resource utilization and better focus the intensity of care according to outcome.