Sleep-Disordered Breathing in the National Football League is not a Trivial Matter
Notice bibliographique
Résumé
Dr. George is on the medical advisory board of Sleep Tech, Wayne, NJ. Mr. Kab has indicated no financial conflicts of interest. We read with interest the recent paper by Rice et al.,1 which looks at a sample of 137 current NFL players using ambulatory monitoring for the determining the prevalence of sleep disordered breathing. The authors concluded that the prevalence of sleep disordered breathing was modest at best, and the results seemed to suggest that there is no need for concern in the young population. In the discussion, they contrast their results with those of our earlier paper,2 and the implication is that our study was neither comprehensive nor generalizable to the players in general. This is disturbing since they have misrepresented our study by stating, “In a single-team study, with players from high (n = 38) and low (n = 14) risk for having sleep apnea, George and colleagues estimated the cross-sectional NFL prevalence of an AHI of at least 10 to be 14% (95% CI, 2%–25%). In this 6-team sample of 137 individuals, we found the prevalence at that cutoff (RDI ≥ 10) to be 8% (95% CI, 4.1%–13.9%).” However, our paper clearly states the methods (and shows in Figure 1) that we drew our sample from 8 teams (20 teams were invited but 12 declined to participate). We used a standard two-stage risk stratification sampling technique as had been used in major epidemiological studies of sleep apnea.3,4 The confidence intervals of our estimates are admittedly larger due to the smaller sample size, but this was because we employed the gold standard of full overnight polysomnography, and this level of testing had a negative effect on participation. The authors further conclude that “sleep disordered breathing did not account for excess cardiovascular risk factors,” suggesting again that there is no need to worry about this diagnosis in these individuals. We find this worrisome since size, BMI and sleep apnea are closely associated, and even the authors I this and their other recent paper5 point out that there is an increase in hypertension and that “…increased size measured by BMI was associated with increased CVD risk factors.”5 Moreover a prevalence of sleep apnea of between 8% (the authors estimate) and 14% (our previous estimate) is not trivial. It is well established that sleep disordered breathing is an independent risk factor for hypertension, and the presence of both of these in professional athletes should not be overlooked or minimized, particularly since there is now evidence that such factors are markedly increased in retired NFL players.6
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,039 | 0,024 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».