用电子健康记录数据识别急性呼吸衰竭表型
Charles R Terry1, Daniel L Brinton2, Katie G Kirchoff3
1Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Medical University of South Carolina, Charleston, SC.
CHEST critical care
|November 27, 2025
概括
电子健康记录 (EHR) 可以在依赖呼吸机的患者中识别两种明显的急性呼吸衰竭亚现象. 这些子类型在生理学和器官功能方面存在差异,其中一种与较高的死亡率有关.
科学领域:
- 关键护理医学 关键护理医学
- 肺部病理学 肺部病理学
- 医疗信息学 医疗信息学
背景情况:
- 之前的研究使用临床试验和观察数据确定了急性呼吸衰竭的亚现象.
- 之前没有使用现实世界电子健康记录 (EHR) 数据来表征亚现型.
研究的目的:
- 为了确定急性呼吸机依赖性呼吸衰竭的亚现型是否可以使用易于获取的EHR数据进行识别.
主要方法:
- 一项多中心回顾性队列研究利用了来自两个机构的电子健康记录数据 (n=4,233和n=8,313).
- 训练和验证K-means集群模型使用在输入后24小时和48小时的多重归算数据.
主要成果:
- 在24小时和48小时后,两组稳定群被一致确定,根据肺生理学, perfusion,器官功能障碍和代谢状态来区分患者.
- 与集群1相比,集群2的90天死亡率更高,呼吸机日数增加,即使经过多变量调整.
- 在输管后48小时内,观察到从高急性集群2到低急性集群1的交叉.
结论:
- 急性呼吸机依赖性呼吸衰竭呈现出两种可以通过电子健康记录数据识别的可辨别的亚现象.
- 这些子类型在关键的生理特征和器官功能障碍标志物上有所不同.
- 这一发现支持开发EHR工具,以早期识别高风险患者.
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