Cardiorespiratory Screening in Elite Endurance Sports Athletes: The Quebec Study
Bibliographic record
Abstract
BACKGROUND: Cardiorespiratory disorders are common in athletes. However, these conditions are often underdiagnosed, which potentially results in impaired performance and increased health risks. The aim of this study was to evaluate, in a research setting, the prevalence of cardiorespiratory disorders in athletes in order to determine the potential value of a screening program. METHODS: One hundred thirty-three athletes were studied. Each subject underwent a physical examination. A eucapnic voluntary hyperventilation (EVH) test and a methacholine inhalation test were performed to confirm the diagnosis of asthma. A cardiovascular evaluation was also performed, including maximal exercise test with electrocardiogram, 24-hour ambulatory blood pressure monitoring, 24-hour Holter monitoring, and blood sampling. RESULTS: Seventy-four (56%) athletes had airway hyperresponsiveness to EVH or the methacholine inhalation test. Among those with airway hyperresponsiveness, 45 (61%) athletes were only hyperresponsive to EVH, and 10 (14%) were only hyperresponsive to the methacholine inhalation test (using the criteria of a PC20 ≤ 4 mg/mL). Thirty-two (24%) athletes had a known diagnosis of asthma, while 34 (26%) athletes received a new asthma diagnosis. Ninety-seven (73%) athletes were sensitized to common airborne allergens. Forty-seven (35%) athletes completed the cardiovascular evaluation. Three (6%) and 7 (15%) athletes had a previous or new diagnosis of cardiovascular disease, respectively. Resting systemic hypertension was documented in 2 (4%) athletes and exaggerated blood pressure response to exercise was found in 12 (26%) athletes. CONCLUSION: This cardiorespiratory screening data set in athletes showed a high prevalence of exercise-induced asthma and exercise hypertension, which in many cases were not previously diagnosed.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".