预测模型来估计高海拔肺风险:一个单中心的回顾性结果报告研究
Yangzong Suona1, Luobu Gesang2,3,4, Zhuoga Danzeng1,3
1High Altitude Medical Research Institute, Tibet Autonomous Region People's Hospital, Lhasa, China.
BMJ open
|November 3, 2023
概括
这项研究使用临床症状开发了一种用于高海拔肺 (HAPE) 的新型预测模型. 这种易于使用的工具可以对HAPE进行早期自我风险评估,改善个人可访问性,并可能防止严重的后果.
科学领域:
- 高度医学 高度医学
- 肺部生理学 肺部生理学
- 临床预测建模模型
背景情况:
- 高海拔肺 (HAPE) 对上升到高海拔地区的个人构成重大风险.
- 早期识别和风险评估对于预防HAPE严重并发症至关重要.
研究的目的:
- 根据常见的临床症状开发HAPE的第一个预测模型.
- 为HAPE创建一个可访问的自我风险预测工具.
- 为了能够及早识别面临HAPE风险的个体.
主要方法:
- 一项回顾性研究招募了西藏自治区人民医院的614名患者.
- 预测者使用单变量和多变量分析进行选,并开发了名ograms.
- 使用接收机操作特征 (ROC) 曲线和校准图表来评估模型性能.
主要成果:
- 六个关键预测因素与HAPE发生率有显著的关联.
- 开发了两种模型,显示出高预测准确度 (AUC为0.934和0.889).
- 该模型显示了良好的校准和近99%的临床净益处.
结论:
- 开发的预测模型 (nomogram) 准确估计了HAPE风险.
- 该模型提供了高分辨率和潜在的临床适用性.
- 这种易于执行的评分工具使个人能够在没有医疗支持的情况下进行自我风险评估.
关键词:
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