TRAINING VOLUME AND CONCUSSION RISK IN MALE YOUTH ICE HOCKEY PLAYERS: A PRIMARY PREVENTION PERSPECTIVE
Bibliographic record
Abstract
Background There is a growing body of evidence illustrating the contribution of training load to musculoskeletal injury risk. There is a gap in the literature, however, regarding the impact of training on concussion risk. Objective To evaluate the association between sport-specific participation volume and concussion risk in male youth ice hockey players. Design Cohort study. Setting Community ice rinks and sport medicine clinics (2011–15 hockey seasons). Patients (or Participants) Male Pee Wee (11–12 years old), Bantam (13–14 years old) and Midget (15–17 years old) ice hockey players were eligible. Players were excluded if they reported unhealed injuries at study entry, had missing/systematically incomplete hockey participation exposure data, or if they sustained a concussion but participation volume could not be estimated from the day of injury. Interventions (or Assessment of Risk Factors) Cumulative hockey participation volume (CPHV) was estimated based on participation exposure data reported by team designate. The association between concussion risk and total 7-day and 28-day CHPV was evaluated using multivariable logistic regression [OR (95%CI)]. Models were adjusted for concussion history and cluster by player (α<0.05). ORs with 95%CI that did not cross one were considered significant. Main Outcome Measurements Medically diagnosed concussion. Results Participants who met the inclusion criteria (n=1235/1990) sustained 34 medically diagnosed concussions. Increased concussion risk was associated with hourly increases in 7-day CHPV [OR=1.16 (95%CI: 1.08–1.25), p<0.05] and 28-day CHPV [OR=1.04 (95%CI: 1.01–1.06), p<0.05]. There was no evidence of effect modification or confounding by concussion history. Conclusions Increased hockey participation volume was associated with increased concussion risk in male youth ice hockey players. This is the first study to explore the association between training volume and concussion risk. Future research utilizing objective volume measurements and training response tools will be critical to the development of primary concussion prevention strategies that optimize the role of training load.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".