Metabolic Equations To Estimate Vo 2 Max Of Healthy Active Canadian Men Aged 18-34 Years-old: Preliminary Results
Bibliographic record
Abstract
VO2max is simply defined by the body’s ability to use oxygen during physical exercise and is widely used as an indicator of cardiorespiratory fitness. Lower VO2max is associated with higher risk of morbidity and mortality as well as low physical performance while higher VO2max levels predict good performance in aerobic sports. Direct measurement of VO2max is still considered as the gold standard. However, it is costly, required sophisticated equipment, and less accessible. Therefore, several metabolic equations have been developed to estimate VO2max using indirect calculation in sub maximal tests. The most commonly used equations are those developed by the American College of Sport Medicine (ACSM) and the research group of Fitness Registry and the Importance of Exercise National Database (FRIEND). PURPOSE: This study aims to evaluate the accuracy of these two equations to estimate VO2max comparatively to direct O2 consumption measurement. METHODS: 30 healthy active men aged between 18-34 years old (BMI: 23,9±2,9 kg/m2) who are avid runners performed a maximal treadmill test with direct VO2 measures (mlO2/kg/min) using a metabolic cart (Vyntus CPX). VO2max estimation was calculated using ACSM and FRIEND running metabolic equations. Direct and indirect results were compared with repeated measures T-test. These preliminary results are part of a larger study which includes 180 men and women of all age group (18-34, 35-54, and ≥ 55y.o.). RESULTS: Indirect VO2max obtained from ACSM and FRIEND equations showed very large (d = 2.01) and moderate (d = 0.6) effect size, and were significantly different when compared to direct measures (ACSM: 66,4±7,0; FRIEND: 56,5±5,9; Vyntus: 53,0±6,3; p<0,001). The mean ACSM overestimation was 13,4 mlO2/kg/min while FRIEND equation was only 3,5 mlO2/kg/min. CONCLUSION: The VO2max calculated with ACSM and FRIEND equations for running showed overestimate values in our male sample. However, the average difference between direct and indirect measurement is smaller when using the FRIEND equation suggesting better accuracy. More research is needed to evaluate the accuracy in different populations and different fitness levels to optimize the VO2max estimation formula.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".