The prevalence of gas exchange data processing methods: a semi-automated scoping review.

IF 2 4区 医学 Q2 SPORT SCIENCES International journal of sports medicine Pub Date : 2025-01-20 DOI:10.1055/a-2495-5364
Anton Hesse, Manix White, Christopher Lundstrom
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Abstract

Cardiopulmonary exercise testing involves collecting variable breath-by-breath data and sometimes requiring data processing of outlier removal, interpolation, and averaging before later analysis. These data processing choices, such as averaging duration, affect calculated values such as ˙VO2max. However, assessing the implications of data processing without knowing popular methods worth comparing is difficult. In addition, such details aid study reproduction. We conducted a semi-automated scoping review of articles with exercise testing that collected data breath-by-breath from three databases. Of the 8,344 articles, 376 (mean: 4.5% and 95% confidence interval: 4.1-5.0%) and 581 (mean: 7.0% and 95% confidence interval: 6.4-7.5%) described outlier removal and interpolation, respectively. A random subset of 1,078 articles revealed (mean: 60.9% and 95% confidence interval: 57.9-63.7%) the reported averaging methods. The commonly documented outlier cutoffs were±3 or 4 SD (39.1 and 51.6%, respectively). The dominating interpolation duration and procedure were 1 s (93.9%) and linear interpolation (92.5%). Averaging methods commonly described were 30 (30.9%), 60 (12.4%), 15 (11.6%), 10 (11.0%), and 20 (8.1%) second bin averages. This shows that studies collecting breath-by-breath data often lack detailed descriptions of data processing methods, particularly for outlier removal and interpolation. While averaging methods are more commonly reported, improved documentation across all processing steps will enhance reproducibility and facilitate future research comparing data processing choices.

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气体交换数据处理方法的流行:半自动化范围审查。
心肺运动测试包括收集可变的呼吸数据,有时需要在后期分析之前对数据进行异常值去除、插值和平均处理。这些数据处理选择(如平均持续时间)会影响VO2max等计算值。然而,在不知道值得比较的流行方法的情况下评估数据处理的含义是困难的。此外,这些细节有助于研究的再现。我们对文章进行了半自动化的范围审查,并进行了运动测试,从三个数据库中逐次收集数据。在8,344篇文章中,分别有376篇(平均4.5%,95% CI: 4.1-5.0%)和581篇(7.0%,6.4-7.5%)描述了异常值去除和插值。1078篇文章的随机子集显示60.9%(57.9-63.7%)报告了平均方法。通常记录的异常截止值为±3或4 SD(分别为39.1%和51.6%)。插补时间和插补程序以1秒(93.9%)和线性插补(92.5%)占主导地位。通常描述的平均方法为30(30.9%)、60(12.4%)、15(11.6%)、10(11.0%)和20(8.1%)次箱平均。这表明,收集呼吸数据的研究往往缺乏对数据处理方法的详细描述,特别是对于异常值的去除和插值。虽然平均方法更常被报道,但所有处理步骤的改进文档将提高可重复性,并促进未来比较数据处理选择的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.80
自引率
4.00%
发文量
111
审稿时长
3-8 weeks
期刊介绍: The IJSM provides a forum for the publication of papers dealing with both basic and applied information that advance the field of sports medicine and exercise science, and offer a better understanding of biomedicine. The journal publishes original papers, reviews, short communications, and letters to the Editors.
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