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Record W3158488189 · doi:10.1177/23259671211013370

Factors Associated With Clinical Recovery After Concussion in Youth Ice Hockey Players

2021· article· en· W3158488189 on OpenAlexaffabout
Carolyn A. Emery, Vineetha Warriyar KV, Amanda M. Black, Luz Palacios‐Derflingher, Stacy Sick, Chantel T. Debert, Brian L. Brooks, Keith Owen Yeates, Martin Mrázik, Constance Lebrun, Brent Hagel, Sean P. Dukelow, Kathryn Schneider

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsHotchkiss Brain InstituteAlberta Children's HospitalUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsConcussionIce hockeyMedicinePhysical medicine and rehabilitationPhysical therapyYouth sportsAthletesInjury preventionPoison controlMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: The identification of factors associated with clinical recovery in youth after sports-related concussion could improve prognostication regarding return to play (RTP). PURPOSE: To assess factors associated with clinical recovery after concussion in youth ice hockey players. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: Participants were part of a larger longitudinal cohort study (the Safe to Play study; N = 3353). Included were 376 ice hockey players (age range, 11-17 years) from teams in Calgary and Edmonton, Canada, with 425 physician-diagnosed ice hockey-related concussions over 5 seasons (2013-2018). Any player with a suspected concussion was referred to a sports medicine physician for diagnosis, and a Sport Concussion Assessment Tool (SCAT) form was completed. Time to clinical recovery was based on time between concussion and physician clearance to RTP. Two accelerated failure time models were used to estimate days to RTP clearance: model 1 considered symptom severity according to the SCAT3/SCAT5 symptom evaluation score (range, 0-132 points), and model 2 considered responses to individual symptom evaluation items (eg, headache, neck pain, dizziness) of none/mild (0-2 points) versus moderate/severe (3-6 points). Other covariates were time to physician first visit (≤7 and >7 days), age group (11-12, 13-14, and 15-17 years), sex, league type (body checking and no body checking), tandem stance (modified Balance Error Scoring System result ≥4 errors out of 10), and number of previous concussions (0, 1, 2, and ≥3). RESULTS: The complete case analysis (including players without missing covariates) included 329 players (366 diagnosed concussions). The median time to clinical recovery was 18 days. In model 1, longer time to first physician visit (>7 days) (time ratio [TR], 1.637 [95% confidence interval (CI), 1.331-1.996]) and greater symptom severity (TR, 1.016 [95% CI, 1.012-1.020]) were significant predictors of longer clinical recovery. In model 2, longer time to first physician visit (TR, 1.698 [95% CI, 1.399-2.062]), headache (moderate/severe) (TR, 1.319 [95% CI, 1.110-1.568]), and poorer tandem stance (TR, 1.249 [95% CI, 1.052-1.484]) were significant predictors of longer clinical recovery. CONCLUSION: Medical clearance to RTP was longer for players with >7 days to physician assessment, poorer tandem stance, greater symptom severity, and moderate/severe headache at first visit.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.100
GPT teacher head0.354
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2021
Admission routes2
Has abstractyes

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