11.26 Sex-based differences in symptoms with mouthguard use following pediatric sport-related concussion
Bibliographic record
Abstract
Objective To compare the association between mouthguard-use and symptom score stratified by sex at acute presentation, and 1-, 2-, and 4-weeks after pediatric sport-related concussion. Design Secondary analysis of 5P multicenter, prospective, cohort study. Setting Nine Canadian pediatric Emergency Departments (ED). Participants Children aged 5–18 years presenting ≤48 hours of concussion sustained during collision or contact sport. Assessment of Risk Factors Symptom score (0–6) was measured using the Post-Concussion Symptom Inventory. Outcome Measures Association of mouthguard use on symptoms was estimated using a fitted generalized least squares multivariable model. Main Results Of 1019 children (73% male; mean age=13.02[SD=2.82]), 42% wore mouthguards at time of injury. After adjusting for covariates, post-model fitting revealed no significant group by sex by time interaction for symptoms (χ23=0.27; p=.965). Males who wore mouthguards reported similar symptom scores in ED (diff=-0.07; 95%CI:-0.23,0.09), at week-1 (diff=-0.02; 95%CI:-0.18,0.14; p=.793), week-2 (diff=-0.03; 95%CI:-0.19,0.13), and week-4 (diff=-0.13; 95%CI:-0.29,0.04) compared with males who didn’t wear mouthguards. In contrast, female mouthguard wearers reported higher symptom scores at week-1 compared with non-mouthguard users (diff=0.29; 95%CI:0.01,0.56). Symptom scores were not significantly different for females who wore a mouthguard and those who didn’t in the ED (diff=0.22; 95%CI:-0.04,0.48; p=.098), at week-2 (diff=0.22; 95%CI:-0.06,0.51; p=.128), or week-4 (diff=0.08; 95%CI:-0.20,0.36; p=.581). Conclusions Wearing a mouthguard at time of injury is not associated with reduced symptoms after sport-related concussion in youth compared with non-mouthguard wearers. Mouthguards remain important to prevent dental injury and may play a role in concussion prevention.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".