DETERMINANTS OF TIME TO DEATH OF STROKE PATIENTS: USING SHARED FRAILTY MODELS

Abstract

Stroke is a severe medical condition causing brain cell death, causing physical changes, communication problems, cognitive issues, emotional problems, and pain. Stroke, the second largest global death cause, is causing an increasing burden of mortality, morbidity, and disability. The main aim of this study was to analyze the factors influencing the time to death of stroke patients by using shared frailty models. The study was conducted in Harar City, at Harar General Hospital, Jegol Hospital and Hiwot Fana Specialized University Hospital. The study was utilized a retrospective study design and considered 224 sample stroke patients from 1 September 2020 to 1 November 2023. Among the total of 224 stroke patients 51(22.77%) experienced a death and the rest 173(77.23%) were censored. The estimated median time to death for stroke patients was 14 days, highlighting the acute nature of this condition. Through rigorous analysis, the Inverse Gaussian frailty model with the Weibull baseline hazard function emerged as the most suitable statistical model, accurately predicting the time to death of stroke patients and yielding the smallest AIC value. The study identified hypertension, cardiac disease, diabetes mellitus, atrial fibrillation, and basic complications as significant factors influencing time to death at a 5% significance level. Furthermore, clustering effect between hospitals appears to have a significant impact on the time it takes for stroke patients to die. This suggests that the presence of frailty (clustering) effects underscores the importance of considering hospital-level heterogeneity in understanding the time-to-death of stroke patients. In light of these findings, the recommendation of the study emphasizes the importance of better hospital management, investigating additional factors, and effectively managing conditions such as hypertension, cardiac disease, diabetes mellitus, atrial fibrillation, and basic complications to improve outcomes for stroke patients.