Efficiency of an active rehabilitation intervention in a slow-to-recover paediatric population following a sport-related concussion
Bibliographic record
Abstract
Objective The aim of this study was to identify whether the addition of an individualised Active Rehabilitation Intervention to standard care influences recovery of young patients who are slow to recover following a sport-related concussion and remain symptomatic at rest. Design Quasi-experimental, prospective study Setting: Interdisciplinary private concussion clinic Subjects Fifteen participants aged 15±2 years. Intervention Standard care and an individualised Active Rehabilitation Intervention which included: 1) low- to high-intensity aerobic training; 2) specific coordination exercises; and, 3) balance exercises. Outcome measures List of symptoms before and after the intervention, duration of symptoms, adherence to the individualised exercice program. Results The Active Rehabilitation Intervention lasted 49 (SD=17 days) days. The duration of the intervention was correlated to self-reported adherence (x=84.64 19.63%, r=−0.792, p<0.001). The average postconcussion symptom inventory (PCSI) score went from a total of 36.85±23.21 points to 4.31±5.04 points after the intervention (Z=−3.18, p=0.001). Conclusions A progressive sub-maximal Active Rehabilitation Intervention may represent an important asset in the recovery of young patients who are slow to recover following a sport-related concussion. Competing interests Phil Fait: Co-owner of the Cortex Mdecine et Radaptation clinic Sarah Imhoff, Frdrike Carrier-Toutant, Genevive Boulard: 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".