Factors influencing survival outcomes in patients with stroke in Zimbabwe: A 12-month longitudinal study

Abstract Background In this longitudinal study, we aimed to determine factors influencing survival outcomes among patients with stroke over a 12-month period. The investigation sought to uncover influential determinants to enhance the precision of prognostic assessments and inform targeted interventions for individuals affected by strokes. Methods Employing a longitudinal study design, participants were observed for 12 months from baseline, censoring survivors at the endpoint. The dataset originated from a comprehensive study involving stroke patients treated at three referral hospitals in Zimbabwe: Parirenyatwa, Sally Mugabe, and Chitungwiza Central Hospital. The primary outcome variable, the duration of survival until death, was measured in days from the initiation of stroke treatment. Gompertz parametric regression analysis was utilized for data modeling following Accelerated Failure Time (AFT) model diagnostics. Results In our study, 188 stroke patients were enrolled at baseline. However, 51 patients were excluded from the analysis due to either missing information or loss to follow-up. Among the remaining 137 patients who were tracked over a 12-month period, 42% were censored, and 58% were deceased. Individuals utilizing ’Free Service (older than 65/pensioners/retirees)’ hospital bill payment methods showed a decreased risk of death (HR: 0.4, 95% CI: 0.20, 0.80), suggesting a protective effect compared to cash paying patients. Those with a secondary school level education displayed a significantly lower risk of death (HR: 0.2, 95% CI: 0.04, 0.69) compared to those without formal education. Age was a significant factor, with individuals aged 45-65 and those over 65 years showing higher adjusted hazard ratios (HR: 4.9, 95% CI: 1.80, 13.25; HR: 5.5, 95% CI: 1.92, 15.95, respectively) relative to those below 45 years of age. Housing status revealed a protective effect for those residing with parents/relatives (adjusted HR: 0.4, 95% CI: 0.20, 0.66), while individuals with a ’Very severe’ functional outcome showed an increased hazard (adjusted HR: 4.9, 95% CI: 1.12, 21.33). Conclusion The study findings demonstrate that hospital bill payment methods, housing status, educational attainment, functional outcome, and age significantly affect survival outcomes among stroke patients. This highlights the need to consider socio-demographic and clinical variables in the development of prognostic assessments and targeted interventions for individuals recovering from stroke.