开发一个增强的评分系统,以预测ICU再接收或在24小时内在医院死亡,使用两个NHS基金会信托机构的例行患者数据
Marco A F Pimentel1, Alistair Johnson2, Julie Lorraine Darbyshire3
1Department of Engineering Science, University of Oxford, Oxford, UK.
BMJ open
|April 12, 2024
概括
一个新的评分系统将ICU数据与生命体征结合起来,可以更好地预测重症监护室 (ICU) 退院后患者病情的恶化. 这种增强的早期预警分数 (EWS) 系统在识别有不良事件风险的患者方面优于传统的EWS.
科学领域:
- 医疗信息学 医疗信息学
- 关键护理医学 关键护理医学
- 患者监测 患者监测
背景情况:
- 集中护理单位 (ICU) 管理重症患者.
- 治疗后的ICU患者需要持续监测病情是否恶化.
- 早期预警分数 (EWS) 系统用于检测有风险的患者.
研究的目的:
- 开发和验证一个增强的连续评分系统.
- 改善ICU出院后患者不良事件的预测.
- 将常规生命体征与ICU出院风险评分结合起来.
主要方法:
- 修改了用于静态分数变量选择的Delphi过程.
- 风险估计的L1调整后勤回归.
- 连续模型整合静态分数和生命体征.
主要成果:
- 模型实现了0.724的AUC,用于预测24小时内重返ICU或住院死亡.
- 超过了国家EWS的表现 (AUC 0.653).
- 外部验证使用来自两个英国NHS信托的数据.
结论:
- 结合ICU停留数据的评分系统可以提高表现,而不仅仅是生命体征.
- 改进的系统可以更好地预测患者病情的恶化.
- 有可能改善患者在ICU后的治疗结果.
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