The University of Toronto Concussion Symptom Scale: do initial symptoms predict outcome?
Bibliographic record
Abstract
Objective To explore symptoms during initial physician evaluation and time to return-to-play experienced by university level athletes. Design Prospective case series of concussions during three athletic seasons (2009–2012). Setting University of Toronto, Ontario, Canada. Subjects Athletes who sustained concussions while involved in inter-university sports (practice or competition) in the following sports: volleyball, fencing, rugby, basketball, track, hockey, soccer, cheerleading, football, lacrosse, field hockey, and figure skating. A total of 85 concussions were reported from 68 athletes (37 males, 31 females) Intervention David L. Macintosh Sport Medicine Clinic physicians documented athletes' post-concussion symptoms and recorded the date when a player was medically cleared to return to play. Main Outcome Measures Symptoms as measured by the University of Toronto Concussion Symptom Scale (UTCSS) scores, time loss from competition, loss of consciousness, amnesia, and history of concussion. Results 90.6% of athletes reported at least one symptom on the UTCSS at the first office-visit, with somatic symptoms most frequently reported. The average UTCSS score at 3 days following injury was 13.1 (range, 0–51), with female athletes reporting significantly more symptoms than males (p<0.01). Time loss was not significantly different between males and females. The only factor that predicted poor outcome (>14 days out) was endorsement of cognitive symptoms of the UTCSS (OR 1.30, 95% CI 1.03 to 1.68). Conclusions Female athletes reported significantly more symptoms than male athletes following concussion. Cognitive symptoms of the UTCSS were significant predictors of time loss among university level athletes. AcknowledgementsThe authors wish to acknowledge the David L. Macintosh Sport Medicine Clinic, The University of Toronto Varsity Blues athletes, therapists, and support staff. Competing interests None.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".