DO RISK FACTORS DIFFER FOR CONCUSSION AND PROLONGED RECOVERY FOLLOWING CONCUSSION IN ELITE YOUTH ICE HOCKEY PLAYERS?
Bibliographic record
Abstract
Background Pediatric concussion risk factor identification will facilitate targeted injury prevention strategy development. Objective To examine risk factors for concussion and prolonged recovery amongst elite youth ice hockey players. Design Cohort study. Setting Community ice rinks and sport medicine clinic (2011/12 season). Participants Male and female elite Bantam (13–14 years) and Midget (15-17 years) ice hockey players (n=780). Assessment of risk factors Baseline age group, sex, previous concussion history and SCAT2 component scores [Total Symptom Score (TSS), Balance Error Score (BES) and Standardized Assessment of Concussion (SAC) score] were evaluated. Main outcome measurements Players with a suspected concussion were referred to a sport medicine physician by team therapists/trainers (n=137). Concussions with time loss of >10 days were defined as prolonged recovery. Results Concussion incidence rate ratios (IRR) were estimated using multivariate (concussion) and univariate (prolonged recovery) Poisson regression analyses (cluster and exposure hours adjusted). Males were at greater risk than females [IRR=1.44 (95% CI: 1.09–1.90)]. In females with no concussion history, Bantam players were at greater risk than Midget players [IRR=4.04 (95% CI: 1.24–13.19)]. In Midget players, those with a history of concussion were at greater risk than those with no concussion history [IRR=2.68 (95% CI: 1.61–4.46)]. Players with baseline TSS in the lowest 25th%ile were at greater risk of concussion [IRR=1.50 (95% CI: 1.03–2.18)] and prolonged recovery [IRR=1.88 (95% CI: 1.18–2.99)]. Players with a history of concussion were at increased risk for prolonged recovery [IRR=2.02 (95% CI: 1.29–3.16)]. SAC and BES were not risk factors. Conclusions Age group, sex, previous concussion history, and baseline symptom reporting affected the risk of concussion and prolonged recovery in elite youth ice hockey players. This study will inform the development of youth sport concussion prevention strategies.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".