Multimethod survival analysis of mortality predictors in advanced heart failure: a cohort study from Pakistan

This study investigates mortality predictors in patients with NYHA Class III or IV heart failure and left ventricular systolic dysfunction at two Pakistani hospitals (n = 299). Survival rates declined over time, with no significant gender differences observed in anemic patients via Kaplan–Meier analysis. Cox proportional hazards and Bayesian Cox regression identified age, anemia, ejection fraction, hypertension, and serum creatinine as significant mortality predictors. Among parametric models, the exponential distribution demonstrated optimal fit based on Akaike and Bayesian information criteria. The analysis revealed that elevated serum sodium levels were associated with reduced mortality risk. Methodologically, this research provides a comprehensive multimethod comparison of survival analysis techniques within a Pakistani cohort, highlighting the Cox model's superior predictive performance while demonstrating the utility of parametric approaches when specific hazard forms are assumed. The consistent identification of key prognostic factors across multiple analytical methods strengthens the clinical relevance of these findings for risk stratification and targeted interventions in advanced heart failure patients within similar resource-limited settings.