氧和指数轨迹表型对机械通风患者的ICU死亡率的预测值:一个多数据库追溯队列研究
Xiawei Shi1, Yangyang Shi2, Liming Fan1
1Zhejiang Chinese Medical University, Hangzhou, China.
Journal of intensive care
|November 29, 2023
概括
在侵袭性机械通风 (IMV) 的重症患者中识别氧和指数 (OSI) 轨迹表型可以预测重症监护室 (ICU) 死亡率. 动态OSI模式为个性化治疗策略提供了有价值的预后见解.
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
- 生物统计学 生物统计学
背景情况:
- 侵袭性机械通风 (IMV) 的重症患者表现出显著的异质性,导致高死亡率.
- 缺乏确定的预后指标阻碍了这些患者的个性化治疗.
- 研究动态氧和指数 (OSI) 轨迹为风险分层提供了一种新的方法.
研究的目的:
- 在接受侵入性机械通风 (IMV) 的患者中识别不同的氧和指数 (OSI) 轨迹表型.
- 评估这些OSI表型与重症监护室 (ICU) 死亡率和无通风日 (VFD) 之间的关联.
- 开发一个预测模型,用于早期识别具有不良预后表型的患者.
主要方法:
- 使用基于组的轨迹模型来定义OSI轨迹表型.
- 用双重可靠的分析来检查OSI表型与ICU死亡率之间的关联.
- 为了识别高风险患者,构建了一个预测模型,将XGBoost纳入倾向得分生成中.
主要成果:
- 确定了四种OSI轨迹表型:低级稳定,上升,下降和高级稳定.
- 高水平的稳定和上升的OSI表型与增加的ICU死亡率有显著的关联.
- 一个预测模型在识别患有上升或高水平稳定OSI表型的患者方面表现良好 (AUC: 0.851培训,0.743验证).
结论:
- 动态OSI轨迹表型与需要IMV的ICU患者的死亡率有很强的相关性.
- 这些OSI表型可以作为指导临床管理的有价值的预后指标.
- 对OSI轨迹的纵向监测可以帮助早期风险分层和为重症患者提供个性化护理.
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