一个简化的肺炎严重程度指数 (PSI) 用于预测COVID-19的临床结果
Shu-Ching Chang1, Gary L Grunkemeier2, Jason D Goldman3,4,5
1Providence St. Joseph Health, Portland, Oregon, United States of America.
一个简化的17个因素的肺炎得分指数 (PSI-17) 准确地预测了COVID-19患者的30天死亡率,类似于原来的20个因素的PSI (PSI-20). 通过消除电子医疗记录集成的手动图表审查,PSI-17简化了风险评估.
科学领域:
- 医疗信息学 医疗信息学
- 流行病学 流行病学
- 临界护理医学 临界护理医学
背景情况:
- 肺炎评分指数 (PSI) 是一个经过验证的工具,用于预测社区肺炎的30天死亡率.
- PSI也是COVID-19患者死亡率的强有力的预测因素.
- 主要的PSI变量在电子病历中并不容易获得,因此需要手动查看病历.
研究的目的:
- 为了比较简化的17个因素的PSI (PSI-17) 与原来的20个因素的PSI (PSI-20) 对COVID-19患者30天死亡率的预测性能.
- 评估电子医疗记录中使用PSI-17进行自动化风险计算的可行性.
主要方法:
- 对1138名住院COVID-19患者进行了回顾性队列研究.
- 使用相关性分析和物流回归模型对PSI-17和PSI-20进行比较.
- 基于歧视 (AUC),校准 (ICI) 和整体表现 (屏障评分) 的预测能力的评估.
主要成果:
- 在PSI-17和PSI-20之间观察到高相关性 (0.95).
- 单变量分析表明,两种分数的性能指标 (AUC,ICI,屏障评分) 都相似.
- 多变量逻辑回归显示,PSI-17 (0.85) 和PSI-20 (0.86) 之间的AUC没有显著差异.
结论:
- PSI-17和PSI-20在预测COVID-19患者30天死亡率方面表现出相似的有效性.
- 通过消除手动图表审查的需要,PSI-17提供了一个实际的优势.
- PSI-17是电子医疗记录中自动化风险分层的可行且易于获得的替代方案.
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