Effect of Player Position on Serum Biomarkers during Participation in a Season of Collegiate Football
Notice bibliographique
Résumé
This prospective cohort study examined the relationship between a panel of four serum proteomic biomarkers (glial fibrillary acidic protein [GFAP], ubiquitin C-terminal hydrolase-L1 [UCH-L1], total Tau, and neurofilament light chain polypeptide [NF-L]) in 52 players from two different cohorts of male collegiate student football athletes from two different competitive seasons of Division I National Collegiate Athletic Association Football Bowl Subdivision. This study evaluated changes in biomarker concentrations (as indicators of brain injury) over the course of the playing season (pre- and post-season) and also assessed biomarker concentrations by player position using two different published classification systems. Player positions were divided into: 1) speed (quarterbacks, running backs, halfbacks, fullbacks, wide receivers, tight ends, defensive backs, safety, and linebackers) versus non-speed (offensive and defensive linemen), and 2) “Profile 1” (low frequency/high strain magnitudes positions including quarterbacks, wide receivers, and defensive backs), “Profile 2” (mid-range impact frequency and strain positions including linebackers, running backs, and tight ends), and “Profile 3” (high frequency/low strains positions including defensive and offensive linemen). There were significant increases in GFAP 39.3 to 45.6 pg/mL and NF-L 3.5 to 5.4 pg/mL over the course of the season ( p < 0.001) despite only five players being diagnosed with concussion. UCH-L1 decreased significantly, and Tau was not significantly different. In both the pre- and post-season blood samples Tau and NF-L concentrations were significantly higher in speed versus non-speed positions. Concentrations of GFAP, Tau, and NF-L increased incrementally from “Profile 3,” to “Profile 2” to “Profile 1” in the post-season. UCH-L1 did not. GFAP increased (by Profiles 3, 2, 1) from 42.4 to 49.6 to 78.2, respectively ( p = 0.051). Tau increased from 0.37 to 0.61 to 0.67, respectively ( p = 0.024). NF-L increased from 3.5 to 4.9 to 8.2, respectively ( p < 0.001). Although GFAP and Tau showed similar patterns of elevations by profile in the pre-season samples they were not statistically significant. Only NF-L showed significant differences between profiles 2.7 to 3.1 to 4.2 in the pre-season ( p = 0.042). GFAP, Tau, and NF-L concentrations were significantly associated with different playing positions with the highest concentrations in speed and “Profile 1” positions and the lowest concentrations were in non-speed and “Profile 3” positions. Blood-based biomarkers (GFAP, Tau, NF-L) provide an additional layer of injury quantification that could contribute to a better understanding of the risks of playing different positions.
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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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».