Exercise ventilatory efficiency in elite athletes assessed for the Paris 2024 Olympic Games: The effect of sex and sport categories
Bibliographic record
Abstract
Abstract Ventilatory efficiency during cardiopulmonary exercise testing (CPET) is obtained by relating minute ventilation (V'E) to CO2 output (V'CO2). Limited information is available regarding exercise ventilatory efficiency in young elite athletes. We assessed ventilatory efficiency in elite athletes; evaluating the influence of sex and/or ESC sport categories; evaluating the agreement between the V'E/V'CO2 slope and nadir in measuring ventilatory efficiency; evaluating differences between subgroups of athletes stratified by ventilatory efficiency. A cohort of 443 elite athletes prospectively underwent CPET. The slope (s1) and the intercept of the linear region of the V'E/V'CO2 relationship, the V'E/V'CO2 value at the lactate threshold and the V'E/V'CO2 nadir were used to assess ventilatory efficiency. Male athletes and endurance athletes, both males and females, had higher exercise ventilatory efficiency (p < 0.001). A strong positive correlation was observed between V'E/V'CO2 s1 and nadir (p < 0.001). Of note, both high (V'E/V'CO2 s1 < 24) and very high (V'E/V'CO2 s1 < 22) levels of ventilatory efficiency were associated with greater exercise tolerance (i.e., peak oxygen uptake, maximal power; p < 0.001). The results of our study emphasize the need to include the measurement of ventilatory efficiency in the evaluation of elite athletes, potentially refining their training strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".