ARE CLINICAL MEASURES OF CERVICAL SPINE STRENGTH AND CERVICAL FLEXOR ENDURANCE RISK FACTORS FOR CONCUSSION IN ELITE YOUTH ICE HOCKEY PLAYERS?
Bibliographic record
Abstract
Background Symptoms of dizziness, neck pain and headaches have previously been identified as risk factors for concussion. Clinical measures associated with these symptoms have not previously been evaluated as risk factors for concussion. Objectives To evaluate clinical measures of cervical endurance and strength as risk factors for concussion in elite youth ice hockey players. Design Prospective cohort study. Setting Community ice rinks and Sport Medicine Clinic. Participants Bantam (12-14 years) and Midget (15–17 years) male and female elite youth ice hockey players (n=466). Risk factor assessment Participants completed baseline clinical tests of cervical flexor endurance and cervical spine isometric strength at the beginning of the 2011–2012 season. Main outcome measurements Players with a suspected concussion (identified by team therapists) were referred to the study sport medicine physician for assessment (diagnosed as per the 3rdInternational Consensus on Concussion in Sport Guidelines). Results Concussion incidence rate ratios were estimated using Poisson regression (adjusted for cluster by team and exposure hours). 466 elite youth ice hockey players completed clinical baseline tests at the start of the 2011–2012 hockey season. Players performing in the lowest 25thpercentile were not at an increased risk of concussion during the season of play [cervical strength right sided IRR=1.33 (95%CI; 0.98–1.83); left IRR=1.07 (95% CI; 0.64–1.78] or cervical flexor endurance [IRR=1.27 (95% CI; 0.74–2.20)]. Conclusion Clinical tests of cervical flexor endurance and isometric cervical strength were not predictive of concussion risk. Further evaluation of other baseline clinical measures is necessary to inform future development of prevention strategies for concussion in youth.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".