Modeling Survival Time to Death among Stroke Patients at Jimma University Medical Center, Southwest Ethiopia: A Retrospective Cohort Study.

Autor: Negasa BW; Department of Statistics, College of Natural and Computational Sciences, Mattu University, Mattu, Ethiopia., Wotale TW; Department of Statistics, College of Natural and Computational Sciences, Mattu University, Mattu, Ethiopia., Lelisho ME; Department of Statistics, College of Natural and Computational Sciences, Mizan-Tepi University, Tepi, Ethiopia., Debusho LK; Department of Statistics, University of South Africa, Pretoria, South Africa., Sisay K; Department of Statistics, College of Natural and Computational Sciences, Jimma University, Jimma, Ethiopia., Gezimu W; Department of Nursing, College of Health Sciences, Mattu University, Mattu, Ethiopia.
Jazyk: angličtina
Zdroj: Stroke research and treatment [Stroke Res Treat] 2023 Nov 29; Vol. 2023, pp. 1557133. Date of Electronic Publication: 2023 Nov 29 (Print Publication: 2023).
DOI: 10.1155/2023/1557133
Abstrakt: Background: Stroke is a life-threatening condition that occurs due to impaired blood flow to brain tissues. Every year, about 15 million people worldwide suffer from a stroke, with five million of them suffering from some form of permanent physical disability. Globally, stroke is the second-leading cause of death following ischemic heart disease. It is a public health burden for both developed and developing nations, including Ethiopia.
Objectives: This study is aimed at estimating the time to death among stroke patients at Jimma University Medical Center, Southwest Ethiopia.
Methods: A facility-based retrospective cohort study was conducted among 432 patients. The data were collected from stroke patients under follow-up at Jimma University Medical Center from January 1, 2016, to January 30, 2019. A log-rank test was used to compare the survival experiences of different categories of patients. The Cox proportional hazard model and the accelerated failure time model were used to analyze the survival analysis of stroke patients using R software. An Akaike's information criterion was used to compare the fitted models.
Results: Of the 432 stroke patients followed, 223 (51.6%) experienced the event of death. The median time to death among the patients was 15 days. According to the results of the Weibull accelerated failure time model, the age of patients, atrial fibrillation, alcohol consumption, types of stroke diagnosed, hypertension, and diabetes mellitus were found to be the significant prognostic factors that contribute to shorter survival times among stroke patients.
Conclusion: The Weibull accelerated failure time model better described the time to death of the stroke patients' data set than other distributions used in this study. Patients' age, atrial fibrillation, alcohol consumption, being diagnosed with hemorrhagic types of stroke, having hypertension, and having diabetes mellitus were found to be factors shortening survival time to death for stroke patients. Hence, healthcare professionals need to thoroughly follow the patients who pass risk factors. Moreover, patients need to be educated about lifestyle modifications.
Competing Interests: The authors declare that there are no competing interests.
(Copyright © 2023 Bikiltu Wakuma Negasa et al.)
Databáze: MEDLINE
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