A systematic review on sleep-related breathing disorders in athletes and para-athletes
Bibliographic record
Abstract
OBJECTIVE: This comprehensive review aims to examine the frequency, consequences, risk factors, and treatment outcomes associated with sleep-related breathing disorders (SRBDs) among athletic populations. METHODS: A systematic literature search was conducted across seven databases from inception through July 2024. RESULTS: Of 3925 studies captured in the search, 20 publications met the inclusion/exclusion criteria. The frequency of SRBDs (apnea-hypopnea index ≥5 events/hour) varied from 7 % to 86.5 %, according to sport modality: (a) 24 % to 86.5 % in rugby players (n = 4 studies); (b) 8 % to 62.5 % in active football players (n = 4); (c) 22 % to 41 % in retired football players (n = 4); (d) 8 % in basketball players (n = 1); (e) 30 % in elite swimmers (n = 1); (f) 61 % in ice hockey players (n = 1); (g) 68 % in judo athletes (n = 1); (h) 58.5 % in golf players (n = 1); (i) 7 % in Brazilian Olympic athletes (n = 1); and (i) 22 % in para-athletes with spinal cord injury (n = 1). Reported consequences (n = 9) included impaired cardiac function, depression, cognitive impairment, and excessive daytime sleepiness. Identified risk factors (n = 12) included: older age, male sex, high body mass index, heavy weight, large neck circumference, prior history of concussion, and playing the lineman or forward position. Treatment with continuous positive airway pressure (CPAP) therapy (n = 2) improved sleep quality, reduced daytime sleepiness, and enhanced athletic performance among golfers and judo athletes; mandibular advancement device (n = 2) reduced apnea severity and snoring among rugby players. CONCLUSIONS: SRBDs occur frequently in athletic populations and pose significant health and performance implications if untreated. There is a paucity of research on SRBDs in para-athletes, which highlights a major knowledge gap.
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How this classification was reachedexpand
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".