Predicting heart failure readmission and all-cause mortality in patients with acute heart failure: a simple predischarge risk score

Abstract

Abstract Introduction Predischarge risk stratification of patients hospitalized for acute heart failure (AHF) could facilitate tailored treatment and follow-up, however, simple scores to predict short-term risk for HF readmission or death are lacking. Purpose We sought to develop a congestion-focused risk score to predict HF readmission and all-cause mortality after discharge in patients hospitalized for AHF. Methods We used data from a prospective, two-center observational study in adults hospitalized for AHF. Laboratory data were collected on admission. Patients underwent a physical examination, 4-zone, and in a subset 8-zone, lung ultrasound (LUS), and conventional echocardiography at baseline (within a median of 1 day after admission). A second LUS was performed before discharge in a subset of patients. The primary endpoint was the composite of HF rehospitalization or all-cause death. HF hospitalizations were adjudicated blinded to LUS findings. Results Among 297 patients with complete data (median age 74 years, 43% women, mean left ventricular ejection fraction 39%), 76 patients (26%) were hospitalized for HF or died within 90 days after discharge. A stepwise Cox regression model selected four significant independent predictors of the composite outcome and each was assigned points proportional to its regression coefficient: NT-proBNP ≥2000 pg/mL (admission) (3 points), systolic blood pressure <120 mmHg (baseline) (2 points), left atrial volume index ≥60 mL/m² (baseline) (1 point) and ≥9 B-lines on predischarge 4-zone LUS (3 points). The weighted risk score provided adequate risk discrimination for the composite outcome (HR 1.48 per 1 point increase, 95% confidence interval: 1.32-1.67, p<0.001, C-statistic: 0.70; Figure 1). In a subset of patients with 8-zone LUS data (n=176), results were similar (C-statistic: 0.72). Conclusion A four-variable, weighted risk score integrating clinical, laboratory and ultrasound imaging data provided adequate risk discrimination for 90-day adverse outcomes in patients hospitalized for AHF. If validated in a larger dataset, this score could be used to identify patients needing the closest monitoring, more intensive follow-up and early treatment adjustment.Figure 1.