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.
Keywords
averaging - outliers - interpolation - cardiopulmonary exercise testing - breath-by-breath - reproducibility
