基于智能手表的最大氧气消耗测量用于预测急性山病:诊断精度评估研究
Xiaowei Ye1, Mengjia Sun1, Shiyong Yu1
1Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
JMIR mHealth and uHealth
|July 6, 2023
概括
通过智能手表VO2max测量心肺呼吸能力,可以预测急性山病 (AMS). 将智能手表VO2max与红细胞分布宽度 (RDW-CV) 结合起来,可以提高高海拔地区AMS预测的准确性.
科学领域:
- 运动生理学 运动生理学
- 高度医学 高度医学
- 可穿戴技术可穿戴技术
背景情况:
- 对于适应高海拔地区而言,心肺健康至关重要.
- 心肺健康与急性山病 (AMS) 之间的联系尚未得到充分研究.
- 可穿戴设备为AMS预测提供了一种评估心肺呼吸能力 (VO2max) 的实用方法.
研究的目的:
- 使用自行管理的智能手表测试 (SWT) 验证VO2max估计.
- 评估VO2max-SWT模型对AMS易感性的预测性能.
- 调查心肺健康在AMS发展中的作用.
主要方法:
- 通过SWT和心肺运动测试 (CPET) 在低空和高空测量VO2max.
- 分析红细胞特征和血红蛋白水平.
- 布兰德-阿尔特曼分析以获得VO2max协议;用于AMS预测的后勤回归和ROC曲线.
主要成果:
- 对于CPET和SWT,VO2max在高海拔地区显著下降.
- 在估计VO2max时,SWT表现出很好的准确性,略高估计.
- 较低的VO2max (CPET和SWT) 与AMS的发展有关.
- VO2max-SWT和RDW-CV独立预测了AMS,它们的组合产生了最高的预测准确度 (AUC=0.839).
结论:
- 智能手表设备提供了一个可行的方法来估计VO2max.
- 基于SWT的VO2max是预测AMS易感性的一个有价值的指标.
- 将智能手表衍生的VO2max与RDW-CV相结合,可以提高高海拔地区的AMS预测.
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