Should our treatments be gender-specific? effect of gender on recovery from persistent post-concussion symptoms in children and adolescents participating in an active rehabilitation intervention
Bibliographic record
Abstract
Objective To estimate the extent to which gender contributes to severity of post-concussion symptoms (PCS) in youth with concussion, who are slow to recover and who receive an active rehabilitation intervention as part of their standard care. Design A retrospective analysis of a prospective cohort Setting Concussion Clinic of a Paediatric Trauma Centre in Canada. Participants 355 youth with persistent PCS (188 girls; 167 boys). All Concussion patients’ information is entered prospectively in a clinical database and participants were selected for this study if they met the following criteria: 1) aged 6 to 17 years (mean=14.34, SD=2.22 years); 2) presenting with at least one PCS interfering with daily activities (mean total PCS score at initial assessment=24.50, SD=18.88), and 3) beginning an active rehabilitation intervention 4 weeks post injury (mean=30.46, SD=3.74 days). Outcome measures Severity of post-concussion symptoms, measured by the PCS scale included in the SCAT3, was the dependent variable. PCS were assessed 3 times over a 4-week follow-up period. Main results Boys presented with significantly less symptoms than girls 4 weeks post-injury, when starting the active rehabilitation intervention (PCSS total score mean; ♂=19.9, ♀=28.5, p<0.001, CI [−14.8, −6.4]). They continued to do so 2 and 4 weeks later, but the rate of recovery was slightly faster for girls over the follow-up period. Conclusions Although there are gender differences in the levels of PCS 4-weeks post-injury, and while boys may recover earlier from persistent PCS, both boys and girls benefit from participating in an active rehabilitation intervention. 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".