Sport concussion assessment tool-second edition in an emergency department setting
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".