Risk Score for Rehospitalization Prediction in Heart Failure from a North African Centre

Abstract

Background: Rehospitalization in heart failure (HF) patients reflects suboptimal outpatient management, disease progression, or socioeconomic barriers. Effective prediction tools are crucial for timely interventions and better resource allocation. Objective: To evaluate clinical, echocardiographic, and adherence-related predictors of rehospitalization within six months of discharge among HF patients and to construct a simplified, cumulative risk score suitable for LMICs. Methods: We conducted a retrospective cohort study including 3000 patients with HF admitted between 2010 and 2024 at Ibn Rochd University Hospital, using the UTIC registry. Predictive factors were identified using multivariable logistic regression. A cumulative score was developed from significant variables. Results: The cohort had a mean age of 64.3 years, with 59% men. LVEF <40%, ischemic etiology, NYHA class III–IV, atrial fibrillation, and poor medication adherence were significant independent predictors. Rehospitalization rates increased with the number of risk factors: 12% for 0–1, 24% for 2, and 48% for ≥3. Conclusion: A five-point risk score based on accessible clinical and behavioral variables provides a practical tool for predicting HF readmissions. Integration into discharge planning could guide follow-up intensity and reduce preventable hospitalizations, particularly in LMICs. Implications: The score’s implementation can serve as a decision-making tool in overburdened healthcare systems, where clinical triage is often intuitive and unsupported by structured data. It provides a framework for early post-discharge intervention, potentially reducing long-term costs and improving quality of life for HF patients.