40 (20A) Multidisciplinary treatment for paediatric persisting post-concussion physical symptoms – a randomized controlled trial
Bibliographic record
Abstract
Purpose To investigate if a targeted multidisciplinary treatment for children and adolescents with persisting post-concussion symptoms (pPCS) is more beneficial than usual care in reducing physical symptoms.Methods Children aged 8 – 18 years who sustained a concussion were recruited from the Royal Children’s Hospital Melbourne emergency department or community health practitioners in Melbourne between 13 August 2019 and 15 July 2024. Children were screened for pPCS and included in the study if they remained symptomatic at 3 weeks. Throughout the trial, parents and children completed the Post Concussion Symptom Inventory (PCSI). They attended for face to face secondary physical and psychological measures. Participants were then randomized into Concussion Essentials (CE) or usual care (UC). UC consisted of routine follow up. The CE multidisciplinary team included a neuropsychologist and physiotherapist who delivered an individualised symptom-directed program that included a combination of education, psychological management and physiotherapy treatment. Participants underwent weekly treatment for up to 8 weeks. At 12 weeks post injury participants were reassessed.Results 140 children were recruited into the study with randomization of 67 into CE and 73 into UC. The mean age was 13.1 (range 8–18) years of age with 56.4% male. Pre-treatment PCSI physical symptom mean scores (maximum 48) were UC 12.18 (95% CI 9.94–14.42) and CE 12.44 (95% CI 10.11–14.76), (p=0.876). Post-treatment mean scores at 12 week follow up were UC 7.80 (95% CI 5.29 – 10.31) and CE 2.31 (1.53–3.09), (p<0.001) see figure 1.Abstract 40 (20A) Figure 1Conclusion Individualised multi-disciplinary treatment is effective in reducing physical symptoms in children and adolescents with pPCS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".