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Highest oxygen consumption prediction: introducing variable theoretical proportional factors for diferent sports

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2024

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springer
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Lorenzo-Capellá, I., Ramos-Álvarez, J.J., Jiménez-Herranz, M.E. et al.. Highest oxygen consumption prediction: introducing variable theoretical proportional factors for different sports. Eur J Appl Physiol (2024). https://doi.org/10.1007/s00421-024-05625-w

Abstract

Purpose The use of a fixed theoretical-proportional-factor (TPF15) is one of the indirect highest-oxygen-consumptions (HOC) assessment methods, but it may not accurately reflect the physiological differences across various sports (cycling-triathlon- running-football-multisport). The aim of this study is to evaluate the variability of TPF across different sports, proposing a series of sport-specific new TPF values for more accurate HOC estimation. Methods A sample of 340 adults (26.01 ± 7.18 years) performed a maximal-incremental-test using sport-specific-ergometers. HOC was considered for cycling ̇ VO2peak , whereas for the other investigated sports it was considereḋVO2max . HOC was directly measured using a gas-analyzer, and TPF values were calculated using heart rate (HR): the ratio of HR max /HR rest multiplied for the measured values of HOC. A one-way ANOVA was used to measure differences and Bland–Altman plots were constructed to compare predicted and actual ̇ VO2max/̇VO2peak. Results Actual HOC was significantly greater than those predicted by the fixed TPF 15 (P < 0.001). Sport-specific new TPF values ranged from 16.55 in multisport to 20.15 in cycling, consistently exceeding the old fixed TPF 15 , and predict- ing therefore better HOC. The new TPF exhibited a closer agreement with the directly measured ̇ VO2max/̇VO2peak com- pared to the TPF 15 . Furthermore, the new TPF reduced the typical-measurement-error (14.94–17.78%) compared to TPF 15 (15.63–24.13%). Conclusion This study suggests that new TPF values predict ̇ VO2max/̇VO2peak with higher accuracy compared to the traditional method. The use of HR max and HR rest values allows to customize training programs for different athletes. Future research should focus on validating these findings across larger populations of athletes

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