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在接受雷姆迪西维尔治疗的COVID-19患者中,高血糖症的危险因素
Woorim Kim1,2, Go Woon Lee1,3, Nuga Rhee4
1College of Pharmacy, Chungbuk National University, Cheongju-si, Korea.
Clinical and translational science
|November 15, 2023
概括
在COVID-19患者的remdesivir治疗期间确定高血糖症的危险因素至关重要. 诸如较高的BMI和某些药物等因素会增加这些不良事件的风险.
科学领域:
- * 传染病 传染病
- * 药理学 药理学 药理学
- * 医学信息学 医学信息学
背景情况:
- *雷梅西维尔是用于治疗2019年新冠病毒病 (COVID-19) 的住院患者的关键抗病毒药物.
- *高血糖不良事件 (AEs) 是与雷梅西维尔药物管理相关的潜在并发症.
- *了解这些AE的预测因素对于优化患者护理和治疗策略至关重要.
研究的目的:
- * 为了确定在接受雷德西维尔的COVID-19患者中与高血糖性AE相关的因素.
- * 开发和评估用于预测高血糖相关并发症的机器学习模型.
- * 帮助开发个性化的雷梅西维尔治疗方案.
主要方法:
- *对1262名住院的COVID-19患者进行了回顾性分析,这些患者接受了remdesivir治疗.
- * 后勤回归分析,以评估共变量和高血糖AE之间的关系.
- * 机器学习算法的应用 (多变量逻辑回归,弹性网,随机森林) 用于风险预测.
主要成果:
- *高体重指数 (BMI) ≥23 kg/m2,使用质子抑制剂,胆固醇药物和心血管疾病的存在与高血糖性AE的风险增加显著相关.
- *这些风险因素的赔率比率从大约1.97到2.73.3不等.
- *机器学习模型显示预测性能中等,接收器运行特征曲线 (AUROC) 下面面积值在0.60到0.66.
结论:
- * 特定的患者特征和同时服用的药物与COVID-19治疗雷梅西韦治疗期间高血糖症的风险更高有关.
- *机器学习方法显示出开发这些不良事件的风险分层工具的潜力.
- *研究结果支持需要量身定制的雷梅西维尔治疗策略,考虑到个体患者的风险概况.
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