与COVID-19死亡率相关的风险因素:使用墨西哥数据库的机器学习方法
Alejandro Carvantes-Barrera1, Lorena Díaz-González2, Mauricio Rosales-Rivera3
1Maestría en Optimización y Cómputo Aplicado, Universidad Autónoma del Estado de Morelos, Cuernavaca, 62209, Morelos, México.
Journal of medical systems
|August 19, 2023
概括
肺炎和晚年是COVID-19死亡的关键预测因素. 医疗单位类型,如IMSS,以及输管和糖尿病等因素也对墨西哥患者的治疗结果产生重大影响.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 数据科学数据科学数据科学
背景情况:
- 识别COVID-19致死性风险因素对于疫情控制至关重要.
- 墨西哥人口结构和医疗保健系统的多样性带来了独特的挑战.
研究的目的:
- 开发和分析COVID-19死亡率的预测模型.
- 确定墨西哥COVID-19死亡率的主要人口统计,并发病和医疗保健相关的风险因素.
主要方法:
- 使用极端梯度提升 (XGBoost) 进行预测建模.
- 使用Shapley值来解释特征的重要性.
- 分析了墨西哥确诊的COVID-19病例 (2020年2月至2022年4月) 的数据.
主要成果:
- 肺炎和晚年是所有流行病学波浪中死亡的最强预测因素.
- IMSS医疗单位是高风险的,而SSA单位是保护性的. 输管是显著的危险因素,特别是在早期的浪潮.
- 女性性别和年轻年龄组 (18-29岁) 是保护因素;中年 (50-59岁),糖尿病,肥胖,高血压和低人类发展指数是危险因素.
结论:
- 该研究确定了墨西哥COVID-19死亡率的关键,波特异性风险因素.
- 调查结果可以为有针对性的公共卫生干预提供信息,以减少死亡率.
- 医疗保健系统结构和社会经济因素在COVID-19结果中发挥着重要作用.
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