Cognitive Function in Varsity Football Athletes is Maintained in the Absence of Concussion
Notice bibliographique
Résumé
Introduction Repetitive sub‐clinical head impacts (SHI) are linked to progressive cognitive decline and post mortem chronic traumatic encephalopathy (CTE) diagnoses in pro contact‐sport athletes. This is particularly evident in aging, though there remains a paucity of knowledge surrounding the onset of trauma‐related cognitive decline in younger athletes. In addition, the influence of cumulative SHI, particularly in the absence of concussion, is poorly understood. As such, we tested the hypothesis that cognitive function would be impaired as a function of career‐long and season‐long exposure to SHI in varsity (collegiate‐level) American football athletes. Methods Male varsity football athletes (n = 31, age 22.3 ± 1.6) completed the Cambridge Brain Sciences (CBS) cognitive battery before (pre) and after (post) their football season. Scores were compared in a repeated measures design against an age (20.6 ± 1.2) and sex matched control group (n = 35) who completed cognitive testing at the same time interval. Individuals sustaining a concussion within the past year were excluded. The CBS cognitive battery ( www.cambridgebrainsciences.com ) consists of 12 online tests assessing a broad range of cognitive skills. Previous work by Hampshire et al (2012) used PCA to identify 3 functionally and cortically distinct networks tested by the CBS battery: Short Term Memory, Reasoning, and Verbal Ability. Based on their previously established factor loadings, a linear composite score for each of these 3 networks was calculated for preseason raw scores. Previously established age‐ and sex‐matched normative values for this population (n > 18 000) were also compared to preseason scores. Postseason control tests are ongoing and were excluded from network and normative comparisons as the current literature does not address the effects of repeated testing on scores. Results In the preseason, there were no significant differences between footballers and controls on any of the 12 CBS tests. Preliminary results suggest that across the season, footballer and control participant scores do not differ either between groups or within groups compared to preseason scores (see ). MANOVA – F(36,276) = 1.336, p = 0.148, η 2 = 0.387. In terms of the network linear composite scores, there were no significant differences between controls and football athletes (see ) for any network. MANOVA – F(3, 61) = 0.55, p = 0.65, η 2 = 0.026. Lastly, in comparison to normative values, football athletes differed on 6 tests of cognitive function, and controls differed from the normative scores on 4 tests (indicated with “N” in ) at the preseason time point. Conclusions Overall, these results suggest the maintenance of normal cognitive function, as assessed behaviourally, in the absence of concussion in an elite contact‐sport population. Small differences between normative and sample means warrant further exploration focussed on examining the functional implications of cumulative SHI as behavioural decline may be masked by compensatory neural mechanisms. Support or Funding Information Canada Excellence Research Chair funding to A.M. Owen
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».