Four-pillar era mortality prediction in acute decompensated heart failure: the ICARUS score

Background Acute decompensated heart failure (ADHF) remains a leading cause of hospitalisation and short-term mortality. Despite widespread adoption of quadruple guideline-directed medical therapy, early, pragmatic risk stratification at admission is essential to optimise clinical management and resource allocation. Purpose To identify independent predictors of in-hospital mortality in patients with ADHF within the contemporary era of four-pillar therapy and to derive and validate a practical bedside risk score (The ICARUS Score). Methods We conducted a retrospective cohort study of 1588 consecutive adults hospitalised with ADHF (including both de novo and decompensated chronic heart failure) between 2022 and 2025. Prespecified candidate predictors were entered into a multivariable logistic regression model using backward selection. Model fit was assessed with the Hosmer-Lemeshow test, and discrimination was evaluated by the area under the receiver operating characteristic curve (AUC). Regression coefficients were scaled to create a simplified points-based system. Internal validation was performed using bootstrapping to ensure robust performance. Results Among 1588 patients (median age 68 years; 69.3% male; median LVEF 30%), in-hospital mortality was 4.28% (68/1,588; 95% CI 3.34–5.39). Independent risk factors were diabetes (OR 1.81), NYHA III–IV (OR 1.97), MLHFQ ≥41 (OR 2.09), atrial fibrillation (OR 2.29), hyperkalaemia (K⁺>5.5 mmol/L; OR 2.63), and systolic BP ≤110 mmHg (OR 3.14). Protective factors were beta-blocker use at admission (OR 0.38), implantable device (OR 0.22), and in-hospital SGLT2 inhibitor therapy (OR 0.27). The model showed good goodness-of-fit (Hosmer-Lemeshow p = 0.997) and strong discriminative ability (AUC 0.81) (Figure 1). The ICARUS points system performed similarly (AUC 0.792; 95% CI 0.738-0.845), with stepwise increases in mortality across strata (Figure 2). Conclusions The ICARUS score, integrating nine readily obtainable clinical and therapeutic variables, accurately stratifies in-hospital mortality risk in the current era of heart failure management. This pragmatic bedside tool provides clinicians with a robust method to identify high-risk patients and tailor intensive care from the moment of admission, making it easy to use across diverse clinical settings.Figure 1.ROC curve analysisFigure 2.