ArticleJournal of the American Heart Association2026
Peak Oxygen Uptake Prediction From Resting and Submaximal Variables of Cardiopulmonary Exercise Testing.
Article in Journal of the American Heart Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
backgroundCardiorespiratory fitness, as measured by peak oxygen uptake during cardiopulmonary exercise testing, is a prognostic indicator. We aim to predict peak oxygen uptake from submaximal variables on cardiopulmonary exercise testing to assess cardiorespiratory fitness when maximal exertion is not possible.
methodsData from 13535 cardiopulmonary exercise testings were collected, and patients were divided into a normal group (NG; n=1076) and other group (OG; n=9823). Regression models to predict maximum oxygen consumption were trained and evaluated on the NG, OG, and combined groups (NG+OG) using stratified 5-fold cross-validation. We trained different models using demographic, resting and submaximal variables.
resultsOptimal models were Bayesian Ridge for the NG and Light Gradient Boosting Machine for the other groups. The mean (SD) R
conclusionsOur peak oxygen uptake prediction model demonstrated strong performance using submaximal exercise variables. This methodology offers a means to assess prognostic markers for individuals who might not achieve maximal exhaustion during cardiopulmonary exercise testing.
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