The association between moderate and vigorous physical activity and time to medical clearance to return to play following sport-related concussion in youth ice-hockey players
Bibliographic record
Abstract
Objective The objective of this study was to determine if youth ice-hockey players who perform more moderate and vigorous physical activity (MVPA) during recovery take longer to achieve medical clearance to return to play (RTP). Design Cohort study. Setting Sport Medicine Centre, Alberta, Canada. Participants Thirty youth ice-hockey players [25 males, 5 females, median age 14 years (range 12–17)] presenting to a sport medicine clinic within 4 days (range 2–20 days) of sustaining a sport-related concussion diagnosed by a sport medicine physician. Exposure Participants MVPA during the first three days following their initial appointment was measured using a waist worn Actigraph accelerometer. MVPA was dichotomized into high (≥45 minutes) and low (<45 minutes) activity based on the median daily MVPA. Outcome The primary outcome was time (days) to medical clearance to RTP. Results All thirty participants performed at least some MVPA over the first three days, despite physician instruction to initially rest following the concussion. Players performing low levels of MVPA reached medical clearance in a median of 15 days (range: 10–30 days). Players performing high levels of MVPA reached medical clearance in a median of 19 days (range: 12–55 days). The low level MVPA group reached medical clearance significantly sooner than the high activity group (log-rank chi2=5.27, p=0.02). Conclusions More time in MVPA during the first three days after initial assessment is significantly associated with greater time to medical clearance to RTP. Future research is needed to better understand the optimal amount and timing of MVPA for concussion recovery. 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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".