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基于COVID-19住院患者的并发症的机械通风预测模型的开发和验证
Yi Zhang1,2, Yang-Jie Zhu3, Dao-Jun Zhu4,5
1Department of Gastroenterology, Changzheng Hospital, Naval Medical University, Shanghai, China.
Frontiers in public health
|July 31, 2023
概括
一个新的模型预测了哪些冠状病毒病2019 (COVID-19) 患者需要机械通风,使用年龄,性别和并发症. 这种工具有助于早期识别和资源分配,以改善患者的治疗结果.
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:
- 机械通风对于管理严重的2019年冠状病毒病 (COVID-19) 以减少死亡率至关重要.
- 早期识别需要机械通风的患者对于及时干预和资源优化至关重要.
- 风险分层工具可以帮助临床医生预测COVID-19患者需要机械通风的需要.
研究的目的:
- 开发和验证用于早期识别可能需要机械通风的COVID-19患者的预测模型.
- 创建一个工具,以协助临床决策的COVID-19患者管理.
- 在COVID-19大流行期间优化稀缺的医疗保健资源的分配.
主要方法:
- 利用来自医疗保健成本和利用项目国家住院患者数据库 (2020) 的大量住院COVID-19患者数据集.
- 采用最小绝对收缩和选择操作员 (LASSO) 和模型构建的多变量后勤回归.
- 使用歧视 (AUC),校准 (Brier分数,斜率,拦截) 和临床实用性来评估模型性能.
主要成果:
- 预测模型包括年龄,性别和11种并发症,显示了中度的歧视 (AUC:0.715) 和良好的校准.
- 该模型显示,在训练和验证组中,在一系列值概率中,临床净益.
- 在培训 (73,957名患者) 和验证 (10,428名患者) 队列中,绩效指标一致.
结论:
- 开发了一种强大的预后模型,用于早期识别需要机械通风的COVID-19患者.
- 该模型在入院时使用易于获得的预测因素,促进实际的临床应用.
- 该工具可以支持临床决策,优化患者管理和资源配置.
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