肺部扩散能力和COVID-19后呼吸障碍:多中心数据集的见解
Gerald S Zavorsky1, Giovanni Barisione2, Thomas Gille3
1Department of Physiology and Membrane Biology, University of California Davis, Sacramento, CA, United States.
Data in brief
|August 21, 2025
概括
这项研究为COVID-19幸存者提供了宝贵的肺功能测试数据集,有助于长期评估肺功能障碍以及对氧化和一氧化碳扩散能力的新诊断工具的验证.
科学领域:
- 肺部医学和呼吸系统研究
- 传染病流行病学
- 生物医学数据科学
背景情况:
- 肺部并发症是COVID-19幸存者的持续挑战,需要强有力的长期评估方法.
- 准确评估肺功能对于了解和管理COVID-19后的呼吸系统后果至关重要.
研究的目的:
- 在COVID-19后的患者中提供一个精选的,开放的肺功能测量数据集.
- 促进肺功能障碍的预测模型的开发,并验证新的诊断方法.
主要方法:
- 收集了来自8个国际中心的572名患者和72名对照者的氧化 (DLNO) 和一氧化碳 (DLCO) 的呼吸量,肺体积和扩散能力.
- 通过排除缺失值和低质量的测量来过数据;与呼吸障碍严重程度相关的肺功能子集 (mMRC尺度).
- 使用SPSS (.sav) 和.csv格式在Mendeley数据云库中的数据可访问性.
主要成果:
- 该数据集包括来自大量COVID-19幸存者的详细肺功能指标,包括DLNO和DLCO.
- 一个子组的分析表明肺功能测量与呼吸障碍严重程度之间的相关性.
- 这些数据支持用于预测建模的总z分数 (DLNO+DLCO) 的计算.
结论:
- 这一开放式数据集是研究COVID-19肺部长期影响的研究人员的关键资源.
- 这些数据可以加速对氧化和一氧化碳诊断的验证,以评估COVID-19后的肺部健康.
- 有助于更深入地了解呼吸系统障碍,并帮助为幸存者制定有针对性的干预措施.
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