气体交换数据处理方法的普及:半自动化范围审查
Anton Hesse1, Manix White1, Christopher Lundstrom1
1Department of Kinesiology.
International journal of sports medicine
|January 20, 2025
概括
心肺运动测试数据处理方法,如异常值去除和插值,在研究中经常被描述得很差. 改善这些技术的文档对于研究可重复性和比较分析选择至关重要.
科学领域:
- 运动生理学 运动生理学
- 数据科学在体育医学中的数据科学
背景情况:
- 心肺运动测试 (CPET) 生成需要处理的呼吸数据.
- 数据处理选择 (例如,平均持续时间) 显著影响关键指标,如最大氧气吸收 (VO2max).
- 缺乏标准化的报告,阻碍了CPET研究的比较和可重复性.
研究的目的:
- 进行范围审查,以确定CPET研究中使用的常见数据处理方法.
- 评估在已发表的研究中报告了异常值去除,插值和平均值技术的程度.
- 提供对当前实践的见解,以指导未来的研究,并提高方法的透明度.
主要方法:
- 对CPET文章进行了一次半自动化范围审查,收集每次呼吸的数据.
- 我们搜索了三个主要的数据库,以确定相关的研究.
- 数据提取的重点是报告的异常值去除,插值和平均值的方法.
主要成果:
- 在4.5%的文章中描述了异常值的删除,在7.0%的文章中描述了插值.
- 平均方法在60.9%的文章子集中报告.
- 常见的异常值截止值为±3或4SD;1秒线性插值占主导地位;30秒和60秒的bin平均值最常见.
结论:
- 在CPET研究中,经常缺乏对数据处理步骤的详细报告,特别是异常值删除和插值.
- 虽然平均方法更常见地报告,但需要全面的文档.
- 加强对所有数据处理方法的报告将提高研究可重复性,并使未来的比较分析成为可能.
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