Abstract
In recent years, numerous prognostic models have been developed to predict VO2max. Nevertheless, their accuracy in endurance athletes (EA) stays mostly unvalidated. This study aimed to compare predicted VO2max (pVO2max) with directly measured VO2max by assessing the transferability of the currently available prediction models based on their R2, calibration-in-the-large, and calibration slope. 5,260 healthy adult EA underwent a maximal exertion cardiopulmonary exercise test (CPET) (84.76% male; age 34.6±9.5 yrs.; VO2max 52.97±7.39 mL·min-1·kg-1, BMI 23.59±2.73 kg·m-2). 13 models have been selected to establish pVO2max. Participants were classified into four endurance subgroups (high-, recreational-, low- trained, and “transition”) and four age subgroups (18–30, 31–45, 46–60, and ≥61 yrs.). Validation was performed according to TRIPOD guidelines. pVO2max was low-to-moderately associated with direct CPET measurements (p>0.05). Models with the highest accuracy were for males on a cycle ergometer (CE) (Kokkinos R2 = 0.64), females on CE (Kokkinos R2 = 0.65), males on a treadmill (TE) (Wasserman R2 = 0.26), females on TE (Wasserman R2 = 0.30). However, selected models underestimated pVO2max for younger and higher trained EA and overestimated for older and lower trained EA. All equations demonstrated merely moderate accuracy and should only be used as a supplemental method for physicians to estimate CRF in EA. It is necessary to derive new models on EA populations to include routinely in clinical practice and sports diagnostic.
Citation: Wiecha S, Kasiak PS, Cieśliński I, Takken T, Palka T, Knechtle B, et al. (2023) External validation of VO2max prediction models based on recreational and elite endurance athletes. PLoS ONE 18(1):
e0280897.
https://doi.org/10.1371/journal.pone.0280897
Editor: Alvaro Reischak-Oliveira, Universidade Federal do Rio Grande do Sul, BRAZIL
Received: June 12, 2022; Accepted: January 10, 2023; Published: January 25, 2023
Copyright: © 2023 Wiecha et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.