Department of Statistics, College of Natural and Computational Sciences, Gambella University, Gambella, Ethiopia.
Monitoring, Evaluation, Accountability and Learning (MEAL) Officer, Doctors with Africa-CUAMM, Gambella, Ethiopia.
Eur J Med Res. 2024 Sep 9;29(1):452. doi: 10.1186/s40001-024-02026-9.
A stroke or a cerebrovascular accident is a common cause of death and a leading cause of long-term, severe disability in both developed and developing countries. The most recent global burden of disease report states that there were 11.9 million new cases of stroke worldwide; stroke accounts for nearly 1 in 8 deaths globally (12%, 6.5 million deaths) and claims a life every 5 s, making it the second most common cause of death worldwide. The goal of the study was to identify the most important factors influencing stroke patients' time to death at Gambella General Hospital.
Data was gathered from patient files in a hospital using a retrospective study methodology, spanning the period from September 2018 to September 2020. R 3.4.0 statistical software and STATA version 14.2 were used for data entry and analysis. The survival time was compared using the log-rank tests and the Kaplan-Meier survival curve. The fitness of the Cox proportional hazard model was examined.
The final model that was fitted was the log-logistic AFT model. A statistically significant correlation was defined as having a p value of less than 0.05 and the accelerated factor (γ) with its 95% confidence interval was employed. Eight days was the total median death time (95% CI 6-10). Significant predictors for shortened mortality time were age (γ = 0.94; 95% CI (0.0.920-0.980), hypertension (γ = 0.63; 95% CI (0.605-0.660), and baseline complications (γ = 0.24; 95% CI (0.223-0.256).
The shortened timing of death was significantly predicted by age, hypertension, and baseline complications. In light of the study's findings, health administrators and caregivers should work to improve society's overall health.
中风或脑血管意外是发达国家和发展中国家常见的死亡原因,也是导致长期、严重残疾的主要原因。最近的全球疾病负担报告显示,全球有 1190 万例新发中风病例;中风占全球死亡人数的近 1/8(12%,650 万人死亡),每 5 秒钟就有 1 人死亡,是全球第二大死因。本研究的目的是确定影响甘贝拉综合医院中风患者死亡时间的最重要因素。
本研究采用回顾性研究方法,从 2018 年 9 月至 2020 年 9 月期间从患者病历中收集数据。使用 R 3.4.0 统计软件和 STATA 版本 14.2 进行数据输入和分析。使用对数秩检验和 Kaplan-Meier 生存曲线比较生存时间。检查 Cox 比例风险模型的拟合优度。
最终拟合的模型是对数逻辑 AFT 模型。具有统计学意义的相关性定义为 p 值小于 0.05,使用加速因子(γ)及其 95%置信区间。总中位死亡时间为 8 天(95%CI 6-10)。缩短死亡率的显著预测因素是年龄(γ=0.94;95%CI(0.0.920-0.980))、高血压(γ=0.63;95%CI(0.605-0.660))和基线并发症(γ=0.24;95%CI(0.223-0.256))。
年龄、高血压和基线并发症显著预测死亡时间缩短。鉴于本研究的结果,卫生管理人员和护理人员应努力改善社会整体健康水平。