Comparison of VO2max Estimations for Maximal and Submaximal Exercise Tests in Apparently Healthy Adults
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Bibliographic record
Abstract
Due to limited accessibility, direct measurement of VO2max is rarely performed in clinical settings or sports centers. As a result, regression equations have been developed and are currently used during exercise tests to provide an indirect estimation. The American College of Sports Medicine (ACSM) has recommended a regression equation for running to provide an indirect estimation of VO2. However, significant differences have been observed between these estimations and directly measured VO2max. Additionally, since submaximal assessments may be more convenient for both athletes and sedentary/diseased individuals, they were included in the analysis. This study aimed to evaluate the accuracy of VO2max estimations provided using the ACSM running equation when used during both maximal and submaximal exercise tests among adult runners. A total of 99 apparently healthy and active adults (age: 39.9 ± 12.2 years; VO2max: 47.4 ± 6.0 mL O2/kg∙min−1) participated in this study. Two types of submaximal estimations were performed to predict VO2max: one based on age-predicted maximal heart rate (HRmax) (ACSMsubmax,Fox), and the second using the actual HRmax measured during the exercise test (ACSMsubmax,measured). The measured VO2max was compared to these estimations obtained from a single exercise test. Both maximal and submaximal exercise tests significantly overestimated VO2max (ACSMmax: +9.8, p < 0.001; ACSMsubmax,Fox: +3.4, p < 0.001; ACSMsubmax,measured: +3.8 mL O2/kg∙min−1, p < 0.001). However, the submaximal estimations were closer to the measured VO2max (p < 0.001). This analysis demonstrated that the included methods overestimated the true VO2max. Nonetheless, the submaximal exercise tests provided a more accurate prediction of VO2max compared to the maximal exercise tests when using the ACSM running equation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it