Concussion in Hockey: Compliance with Return to Play Advice and Follow-up Status
Bibliographic record
Abstract
OBJECTIVES: To determine the compliance rate among hockey players with concussion or other head injuries who were advised by a physician about return to play. To assess compliance of hockey players with return to play advice and to assess the incidence of long-term post-concussion symptoms. METHODS: A retrospective chart review, telephone questionnaire and follow-up analysis of income, level of education and professional aspirations. The study examined 40 hockey players with concussion or other head injury treated at a neurosurgical ambulatory clinic, who had initial visits between 1995 and 2003, and had been seen at least two years prior to completing the questionnaire. RESULTS: There was a 58% (23 of 40) participation rate in the study. Fifteen (65%) of the 23 participants were advised to never return to play, and 5 (33%) were non-compliant and returned to play. Four (80%) of the five noncompliant players continued to suffer from post concussion symptoms. Overall, 15 (65%) of the 23 players participating in the study continued to suffer post concussion symptoms at least two years after the clinic visit. CONCLUSIONS: Five (33%) of 15 hockey players advised to never return to play were non-compliant and returned to play, and four continued to suffer from post concussion symptoms two or more years later. After repeated concussions, 65% of hockey players had long-term sequelae that prevented return to play and produced long-term post-concussion symptoms.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 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".