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预测模型用于在急诊室识别传染性COVID-19患者

Myat Oo Aung¹, Indumathi Venkatachalam^1,2, Jean X Y Sim^1,2

¹Infection Prevention and Epidemiology Department, Singapore General Hospital, Singapore, Singapore.

Antimicrobial stewardship & healthcare epidemiology : ASHE

|May 22, 2024

概括

紧急部门的预测模型可以早期识别感染性COVID-19患者. 该模型使用临床数据和快速测试,实现了高精度,有助于感染控制工作.

科学领域:

传染病流行病学传染病流行病学
临床信息学临床信息学
公共卫生公共卫生

背景情况:

实时逆转录酶聚合酶链反应 (RT-PCR) 是COVID-19诊断的标准,但有延迟.
在急诊室 (ED) 中,针对2019年新冠肺炎 (COVID-19) 传染病的有效预测算法可以减轻与医疗相关的传播.
及时识别传染病患者对于预防感染至关重要.

研究的目的:

开发一种预测模型,在ED呈现时识别可感染的COVID-19患者.
用已确定的指标来评估模型的性能,例如接收器操作特征曲线 (AUROC) 下的面积.

主要方法:

在新加坡总医院 (SGH) 从2020年3月到2022年12月进行了一项回顾性队列研究.
通过使用人口,临床,症状,实验室和抗原快速测试数据开发和验证了两种预测模型.
传染性COVID-19被定义为RT-PCR的周期值 (Ct) 值<25.

主要成果:

这项研究包括78,687名患者,其中6,132人检测出严重急性呼吸道冠状病毒2 (SARS-CoV-2) 阳性.
在SARS-CoV-2阳性患者中,近70%的人患有传染性COVID-19 (Ct<25).
最初的模型实现了0.85.8的AUROC. 结合抗原快速测试结果,AUROC提高到0.97,具有高灵敏度 (95.0%) 和特异性 (92.8%).

结论:

使用易于获得的ED数据的临床预测模型可以有效地识别传染性COVID-19患者.
这些模型可以显著提高医疗保健机构内的感染预防策略.
早期识别有助于迅速隔离,并减少疾病的传播.

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