一种客观的方法来检测心肺运动测试期间的叹息
Léon Genecand1,2, Thomas Nibler3, Ivan Guerreiro4,5
1Service de Pneumologie, Département de Médecine, Hôpitaux Universitaires de Genève, Genève, Switzerland. leon.genecand@hug.ch.
Scientific reports
|October 21, 2025
概括
研究人员开发了一种自动化方法,在心肺运动测试 (CPET) 中客观量化过度叹息. 这一突破有助于诊断功能障碍呼吸 (DB) 并了解其与COVID-19后持续性呼吸障碍的联系.
科学领域:
- 肺部医学 肺部医学
- 呼吸系统生理学 呼吸系统生理学
- 医疗技术 医疗技术 医学技术
背景情况:
- 过度叹息是一种已知的呼吸功能障碍 (DB) 的形式.
- 心肺运动测试 (CPET) 主观地评估叹息,但缺乏自动定量.
- 需要客观的方法来测量CPET期间的叹息.
研究的目的:
- 开发和验证一种自动化方法来量化CPET期间的叹息.
- 为了能够客观地评估功能障碍的呼吸模式.
主要方法:
- 利用两个瑞士队列 (n=48导出,n=77验证) 的COVID-19后呼吸障碍患者接受CPET.
- 开发了一个使用滚动中位数过器和潮体积 (VT) 峰值分析的自动检测算法.
- 经验丰富的评级人员使用高分辨率数据对视觉分析进行验证的自动视线检测.
主要成果:
- 自动化方法的准确性很高,在203个检测到的尖峰中,有199个 (98%) 相当于验证队列中的叹息.
- 实现了高的评价者间可靠性 (科恩卡帕=0.89).
- 开发的方法有效量化了CPET期间的叹息.
结论:
- 在CPET期间成功开发了一种简单的自动化方法,用于客观地量化 sigh.
- 这种工具可以促进建立规范性 sigh 值,并探索 DB 患者的 sigh-symptom 关联.
- 该方法有可能改善功能障碍呼吸的诊断和管理.
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