在低血压中分层死亡风险,使用以结果为导向的生命体征轨迹集群
Zhuolun Liu1, Li Li2,3, Yongmin Zhang1
1School of Computer Science and Engineering, Central South University, Changsha 410083, China.
iScience
|March 11, 2026
概括
低血压患者的早期生命体征模式可以预测死亡风险. 具体来说,在前两个小时内的呼吸速率轨迹是关键指标,较高的速率与死亡风险增加有关.
科学领域:
- 临界护理医学 临界护理医学
- 在医疗保健中的数据科学.
- 生理监测 生理监测
背景情况:
- 在患有低血压的重症患者中,早期生命体征轨迹的预后价值尚不清楚.
- 准确的死亡风险分层对于这些患者的及时干预至关重要.
研究的目的:
- 开发和验证一种风险分层死亡率模型,使用早期生命体征轨迹来确定低血压患者的风险分层死亡率.
- 为了确定最能预测死亡率的特定生命体征模式.
主要方法:
- 采用以结果为导向的两步聚类模型,在症状出现后12小时内分析生命体征轨迹.
- 使用权重学习来确定分析的最佳时间窗口.
- 该模型是使用MIMIC-IV数据库的数据开发的,并在eICU和Xiangya多ICU数据库中验证的.
主要成果:
- 确定了三个不同的生命体征轨迹集群,表明死亡率逐渐增加.
- 与集群1 (HR 2.30) 相比,集群3显示出死亡率调整后最高的风险比率.
- 最初2小时内的呼吸速率轨迹成为死亡风险的主要歧视因素. 外部验证证实了该模型的概括性和预测准确性.
结论:
- 生命体征轨迹,特别是早晨的呼吸速率模式,可以有效地分层低血压患者的死亡风险.
- 初始阶段呼吸率升高与死亡率增加密切相关.
- 这种方法为在重症监护机构早期识别高风险低血压患者提供了一种新的方法.
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