建立和验证基于中国人口中SARS-CoV-2感染的常见实验室指标的预后模型
Anjiang Zhao1,2,3, Yanyang Liu4,5, Junxiang Xia1,6
1Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China.
Annals of medicine
|September 6, 2024
概括
使用乳酸脱酶和白蛋白等实验室标记物的新预后模型可以预测政策变化后的COVID-19患者死亡率. 这种工具有助于早期识别严重病例,以便更好地管理.
科学领域:
- 医学研究 医学研究
- 流行病学 流行病学
- 临床诊断 临床诊断 临床诊断
背景情况:
- 中国的COVID-19控制措施在2022年12月发生了重大调整.
- 从这个时期分析感染数据和实验室标记对于COVID-19患者管理和预后至关重要.
研究的目的:
- 开发和验证一种预后模型,用于预测住院COVID-19患者的死亡率.
- 确定与COVID-19死亡率相关的关键实验室和临床因素.
主要方法:
- 使用后勤回归,LASSO和逐步方法来选显著的死亡率预测因素.
- 使用选定的预测因素构建了一个预后模型和名ogram.
- 用歧视,校准和决策曲线分析来评估模型性能.
主要成果:
- 分析了888名患者 (173人死亡). 关键预测因素包括乳酸脱酶 (LDH),专蛋白 (ALB),公素 (PCT),年龄和疫苗状态.
- 一个七个预测模型 (包括中性粒细胞与淋巴细胞的比率,D-二次体,PCT,C-反应蛋白,ALB,碳酸盐,LDH) 的AUC达到0.842 (训练) 和0.853 (验证).
- 该模型在各种风险值中显示出高的歧视,校准和临床净益.
结论:
- 开发的基于实验室的预后模型在预测COVID-19患者结果方面表现出很高的性能.
- 这种模型可以帮助早期识别严重的COVID-19病例,促进及时的临床干预.
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