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VO(2max) prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study
BACKGROUND: Oxygen uptake (VO(2)) is one of the most important measures of fitness and critical vital sign. Cardiopulmonary exercise testing (CPET) is a valuable method of assessing fitness in sport and clinical settings. There is a lack of large studies on athletic populations to predict VO(2max) u...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198721/ https://www.ncbi.nlm.nih.gov/pubmed/37162318 http://dx.doi.org/10.7554/eLife.86291 |
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author | Wiecha, Szczepan Kasiak, Przemysław Seweryn Szwed, Piotr Kowalski, Tomasz Cieśliński, Igor Postuła, Marek Klusiewicz, Andrzej |
author_facet | Wiecha, Szczepan Kasiak, Przemysław Seweryn Szwed, Piotr Kowalski, Tomasz Cieśliński, Igor Postuła, Marek Klusiewicz, Andrzej |
author_sort | Wiecha, Szczepan |
collection | PubMed |
description | BACKGROUND: Oxygen uptake (VO(2)) is one of the most important measures of fitness and critical vital sign. Cardiopulmonary exercise testing (CPET) is a valuable method of assessing fitness in sport and clinical settings. There is a lack of large studies on athletic populations to predict VO(2max) using somatic or submaximal CPET variables. Thus, this study aimed to: (1) derive prediction models for maximal VO(2) (VO(2max)) based on submaximal exercise variables at anaerobic threshold (AT) or respiratory compensation point (RCP) or only somatic and (2) internally validate provided equations. METHODS: Four thousand four hundred twenty-four male endurance athletes (EA) underwent maximal symptom-limited CPET on a treadmill (n=3330) or cycle ergometer (n=1094). The cohort was randomly divided between: variables selection (n(runners) = 1998; n(cyclist) = 656), model building (n(runners) = 666; n(cyclist) = 219), and validation (n(runners) = 666; n(cyclist) = 219). Random forest was used to select the most significant variables. Models were derived and internally validated with multiple linear regression. RESULTS: Runners were 36.24±8.45 years; BMI = 23.94 ± 2.43 kg·m(−2); VO(2max)=53.81±6.67 mL·min(−1)·kg(−1). Cyclists were 37.33±9.13 years; BMI = 24.34 ± 2.63 kg·m(−2); VO(2max)=51.74±7.99 mL·min(−1)·kg(−1). VO(2) at AT and RCP were the most contributing variables to exercise equations. Body mass and body fat had the highest impact on the somatic equation. Model performance for VO(2max) based on variables at AT was R(2)=0.81, at RCP was R(2)=0.91, at AT and RCP was R(2)=0.91 and for somatic-only was R(2)=0.43. CONCLUSIONS: Derived prediction models were highly accurate and fairly replicable. Formulae allow for precise estimation of VO(2max) based on submaximal exercise performance or somatic variables. Presented models are applicable for sport and clinical settling. They are a valuable supplementary method for fitness practitioners to adjust individualised training recommendations. FUNDING: No external funding was received for this work. |
format | Online Article Text |
id | pubmed-10198721 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-101987212023-05-20 VO(2max) prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study Wiecha, Szczepan Kasiak, Przemysław Seweryn Szwed, Piotr Kowalski, Tomasz Cieśliński, Igor Postuła, Marek Klusiewicz, Andrzej eLife Medicine BACKGROUND: Oxygen uptake (VO(2)) is one of the most important measures of fitness and critical vital sign. Cardiopulmonary exercise testing (CPET) is a valuable method of assessing fitness in sport and clinical settings. There is a lack of large studies on athletic populations to predict VO(2max) using somatic or submaximal CPET variables. Thus, this study aimed to: (1) derive prediction models for maximal VO(2) (VO(2max)) based on submaximal exercise variables at anaerobic threshold (AT) or respiratory compensation point (RCP) or only somatic and (2) internally validate provided equations. METHODS: Four thousand four hundred twenty-four male endurance athletes (EA) underwent maximal symptom-limited CPET on a treadmill (n=3330) or cycle ergometer (n=1094). The cohort was randomly divided between: variables selection (n(runners) = 1998; n(cyclist) = 656), model building (n(runners) = 666; n(cyclist) = 219), and validation (n(runners) = 666; n(cyclist) = 219). Random forest was used to select the most significant variables. Models were derived and internally validated with multiple linear regression. RESULTS: Runners were 36.24±8.45 years; BMI = 23.94 ± 2.43 kg·m(−2); VO(2max)=53.81±6.67 mL·min(−1)·kg(−1). Cyclists were 37.33±9.13 years; BMI = 24.34 ± 2.63 kg·m(−2); VO(2max)=51.74±7.99 mL·min(−1)·kg(−1). VO(2) at AT and RCP were the most contributing variables to exercise equations. Body mass and body fat had the highest impact on the somatic equation. Model performance for VO(2max) based on variables at AT was R(2)=0.81, at RCP was R(2)=0.91, at AT and RCP was R(2)=0.91 and for somatic-only was R(2)=0.43. CONCLUSIONS: Derived prediction models were highly accurate and fairly replicable. Formulae allow for precise estimation of VO(2max) based on submaximal exercise performance or somatic variables. Presented models are applicable for sport and clinical settling. They are a valuable supplementary method for fitness practitioners to adjust individualised training recommendations. FUNDING: No external funding was received for this work. eLife Sciences Publications, Ltd 2023-05-10 /pmc/articles/PMC10198721/ /pubmed/37162318 http://dx.doi.org/10.7554/eLife.86291 Text en © 2023, Wiecha et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Medicine Wiecha, Szczepan Kasiak, Przemysław Seweryn Szwed, Piotr Kowalski, Tomasz Cieśliński, Igor Postuła, Marek Klusiewicz, Andrzej VO(2max) prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study |
title | VO(2max) prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study |
title_full | VO(2max) prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study |
title_fullStr | VO(2max) prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study |
title_full_unstemmed | VO(2max) prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study |
title_short | VO(2max) prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study |
title_sort | vo(2max) prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198721/ https://www.ncbi.nlm.nih.gov/pubmed/37162318 http://dx.doi.org/10.7554/eLife.86291 |
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