Sport concussion assessment tool-second edition in an emergency department setting
Notice bibliographique
Résumé
Objective To investigate the clinical usefulness of the Sport Concussion Assessment Tool-Second Edition (SCAT2) in patients with mild traumatic brain injuries (MTBI). Design A cross-sectional, descriptive study. Setting Emergency Department of Tampere University Hospital, Finland. Patients Patients (N=38, 26 men and 12 women) between the ages of 18 and 60 years, with no premorbid medical or psychiatric conditions, who met the WHO criteria for MTBI were enrolled. Alcohol intoxication was an exclusion criterion. Interventions A broad clinical assessment and the SCAT2 were completed within 4 days postinjury (Median=19.6 h, SD=24.8, Range=2–94.5 h). CT of the head was performed in the ED. A head MRI was done within 1 week postinjury. Main Outcome Measurements Outcome measurements included clinical injury severity markers (loss of consciousness (LOC), GCS, post-traumatic amnesia (PTA), retrograde amnesia (RA), disorientation, and focal neurological deficits), and the SCAT2 subscores and total score. Results The mean SCAT2 total score was 76.4 (SD=9.7, range=52–93). The mean Standardised Assessment of Concussion score was 25.3 (SD=2.1, range=21–30), balance score was 20.9 (SD=6.7, range=8–30), and symptom severity score was 16.6 (SD=14.1, range=0–60). The vast majority of the sample endorsed 5 or more symptoms (89.5%). The SCAT2 total scores and subscores were not significantly associated with the MTBI severity markers (eg, LOC, PTA, and RA) or imaging findings. Conclusions The SCAT2 measures the acute consequences of MTBI reasonably well in many civilian patients with MTBIs. However, the scores do not reflect the clinical or radiological severity of injury. Acknowledgements The authors would like to thank research assistants Anne Simi for her contribution in data collection. Competing interests Grant Iverson has been reimbursed by the government, professional scientific bodies, and commercial organizations for discussing or presenting research relating to mild TBI and sport-related concussion at meetings, scientific conferences, and symposiums. These include, but are not limited to, the National Academy of Neuropsychology, American Academy of Clinical Neuropsychology, International Neuropsychological Society, US Department of Defense, and Australasian Faculties of Rehabilitation Medicine and Occupational and Environmental Medicine, and the Swiss Accident Insurance Fund. He has a clinical practice in forensic neuropsychology involving individuals who have sustained mild TBIs. He has received research funding from several test publishing companies, including ImPACT Applications, Inc., CNS Vital Signs, and Psychological Assessment Resources (PAR, Inc.). He has received honorariums for serving on research panels that provide scientific peer review of programs (eg, the Military Operational Medicine Research Program). He is a co-investigator, collaborator, or consultant on grants funded by several organizations, including, but not limited to, the Canadian Institute of Health Research, Alcohol Beverage Medical Research Council, Rehabilitation Research and Development (RR&D) Service of the US Department of Veterans Affairs, AstraZeneca Canada, Lundbeck Canada, and Pfizer Canada. He works part-time as a contractor, doing TBI in the military research, for the Defense and Veterans Brain Injury Center.
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 | 0,003 |
| 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 | 0,001 |
| Intégrité de la recherche | 0,000 | 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 ».