Comparison of Vestibular/Ocular Motor Screening (VOMS) and Computerized Eye-tracking to Identify Exposure to Repetitive Head Impacts
Notice bibliographique
Résumé
INTRODUCTION: Military service members (SMs) are exposed to repetitive head impacts (RHIs) in combat and training that are purported to adversely affect brain health, including cognition, behavior, and function. Researchers have reported that RHI from blast-related exposure may affect both vestibular and ocular function, which in turn may be related to symptomology. As such, an examination of the effects of RHI on exposed military SMs should incorporate these domains. To date, researchers have not compared groups of exposed special operations forces (SOF) operators on combined clinical vestibular/ocular and eye-tracker-based outcomes. Therefore, the primary purpose of this study was to compare participant-reported symptoms and performance on the Vestibular/Ocular Motor Screening (VOMS) tool with performance on the computerized RightEye tracking system between SOF operators exposed to blast-related RHI and healthy controls without blast-related exposure. In addition, the study aimed to compare subgroups of snipers and breachers exposed to RHI to controls on the preceding metrics, as well as identify a subset of individual (demographic) factors, participant-reported symptoms, and performance metrics on VOMS and RightEye that best identify SOF operators exposed to RHI from unexposed controls. MATERIALS AND METHODS: The study involved a cross-sectional design including 25 Canadian SOF SMs comprised of breachers (n = 9), snipers (n = 9), and healthy, unexposed controls (n = 7). The former 2 groups were combined into an RHI group (n = 18) and compared to controls (n = 7). Participants provided demographics and completed a self-reported concussion-related symptom report via the Military Acute Concussion Evaluation 2, the VOMS, and RightEye computerized eye-tracking assessments. Independent samples t-tests and ANOVAs were used to compare the groups on the outcomes, with receiver operating characteristic curve and area under the curve (AUC) analyses to identify predictors of blast exposure. This study was approved by the Defence Research Development Canada Human Research Ethics Committee and the Canadian Forces Surgeon General/Special Forces Command. RESULTS: The results from t-tests supported group differences for age (P = .012), participant-reported symptoms (P = .006), and all VOMS items (P range = <.001-.02), with the RHI group being higher than healthy controls on all variables. ANOVA results supported group differences among snipers, breachers, and controls for age (P = .01), RightEye saccades (P = .04), participant-reported total symptom severity (P = .03), and VOMS total scores (P = .003). The results of the receiver operating characteristic curve analyses supported age (AUC = 0.81), Military Acute Concussion Evaluation 2 participant-reported total symptom severity (AUC = 0.87), and VOMS total scores (AUC = 0.92) as significant predictors of prior blast exposure. CONCLUSIONS: Participant-reported concussion symptoms, VOMS scores, and age were useful in identifying SOF operators exposed to RHI from controls. RightEye metrics were not useful in differentiating RHI groups from controls. Differences between snipers and breachers warrant further research. Overall, the findings suggest that VOMS may be a useful tool for screening for the effects of exposure to RHI in SOF operators. Future investigations should be conducted on a larger sample of military SMs, consider additional factors (e.g., RHI exposure levels, medical history, and sex), and include additional assessment domains (e.g., balance, cognitive, and psychological).
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».