7.15 Observations of return to participation timelines of patients with persistent concussion symptoms at a community physiotherapy clinic based on sport injury mechanism
Bibliographic record
Abstract
Objective To compare patient demographics, injury phase (IP; time-to-assessment), total symptom severity score (TSS) changes and return to participation (RTP; cognitive/physical) timelines. Design Retrospective chart review. Setting Community physiotherapy clinic providing secondary care. Participants 108 multi-ethnic sport concussion patients (age: 10–70 years; male: n=42; female: n=66) receiving treatment between 01/09/2016–31/08/2018. Age groups (years): children 8–12, youth 13–17, young adult 18–29, adult 30–64, senior 65+. IP: acute (<72 hours), subacute (72 hours-2 weeks adults, 72 hours-4 weeks children/youth), persistent (2 weeks-3 months adults, 4 weeks-3 months children/youth), chronic (>3 months). Interventions Multimodal physiotherapy (cervico-vestibular, exertion, education); referral to specialist physician, psychology and/or neuropsychology. Outcome Measures Treatments (number, timeframe), weeks to recovery (WTR), TSS changes, and RTP. Main Results Patients averaged 5.56 treatments (95% CI [4.86, 6.27]) over 7.54 weeks (95% CI [5.65, 9.43]). Patient WTR averaged 19.63 weeks (95% CI [14.21, 25.05]). Acute IP had WTR consistent with current literature. For other IPs, WTR was longer regardless of age or sex (p<0.05). Females averaged longer treatment timeframes than males (p<0.05), regardless of IP. TSS decreased in 87% of patients; 83% achieved full cognitive RTP; 64% achieved full physical RTP. Conclusions Concussion patients receiving community physiotherapy experienced symptom, cognitive, and physical recovery. All IPs except acute had longer treatment and recovery timelines than previously reported in literature. Results will enable implementation of pragmatic physiotherapy interventions for concussion. Community-delivered therapy timeframes and treatment effects may inform injury surveillance prevention models.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".