657 MEP041 – Fast-tracking concussion recovery in elite athletes: the power of early multidisciplinary secondary prevention
Bibliographic record
Abstract
Background Over the past two decades, guidelines for early recognition and management of sport-related concussions (SRC) have evolved, reflecting advances in evidence-based practices. Their specific impact on recovery in elite level athletes remains relatively unexplored. Objective to investigate the epidemiology of concussions in elite athletes emphasizing secondary prevention through unrestricted multidisciplinary care. Design observational cohort study Setting data obtained from athletes visiting a national sports institute medical clinic in Canada Participants a total of 161 concussions were recorded over four years (2018 to 2022) involving 87 females and 74 males (mean age 20.5±4.6 years old) across 28 sports. Seven sports groups had unrestricted access to the national sports institute’s concussion clinic. All participants competed in national or international events. Assessment of Risk Factors Data included concussion counts, sex, delay to first consultation, history of previous concussions, SCAT5 assessments including SCAT5 risk modifiers, and clinical expert consultations. Main Outcome Measurements Our primary focus was return to performance measured by days to complete stepwise rehabilitation (e.g., steps 1–6) and achieve symptom-free, physician-authorized competition return. Results athletes with unrestricted access to multidisciplinary care had a significantly shorter median return to performance of 26.0 days (IQR=25.0), compared to external visitors (50.0 days, IQR=63.5) (p<0.01). Delayed access affected external visitors more, with a median delay of 15.5 days (IQR=29.3) vs 4.0 days (IQR=11.0) for those with unrestricted access (p<0.01). Notably, known risk factors did not significantly affect return to performance, however males and females exhibited different clinical trajectories. Conclusions Elite athletes require longer recovery periods than previously reported in broader populations. Early multidisciplinary care access emerges as crucial in reducing concussion recovery times, underscoring the importance of prevention and rapid intervention in elite sports. Multidisciplinary care demonstrates potential for secondary prevention of SRC in elite athletes.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".