Effectiveness of Non-Pharmacological Therapy on Physical Symptoms in Patients With Persistent Concussion Symptoms: A Systematic Review
Bibliographic record
Abstract
, Cochrane library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Embase were searched from January 1, 2012 to September 1, 2023 using terms related to physical post-concussion symptoms. Eligible articles were critically appraised using the Scottish Intercollegiate Guidelines Network (SIGN) and the Quality Assessment Tool. The Grading of Recommendations Assessment, Development, and Evaluation system was applied to rate the quality of evidence. Thirty-two articles were included. Preliminary evidence suggests that transcranial magnetic stimulation improves symptoms in adults, specifically headaches. Young adults reported a significant decrease in physical symptoms following sub-symptom aerobic training as well as cervical spine manual therapy. Tentatively, adults demonstrated improvements in headache symptoms following neurofeedback sessions, and progressive muscle relaxation resulted in a decrease in monthly headaches. Multimodal therapy in adults produced significant change in physical symptoms when compared with usual care. However, no further reduction in physical symptoms was observed when adult patients received a program of care that afforded cervicovestibular rehabilitation with symptom-limited exercise compared with a symptom-limited exercise program alone. Cognitive behavioral therapy demonstrated inconsistent findings for its effects on physical symptoms, specifically headaches. Veterans had a significant change in post-concussive symptoms, specifically headaches, following 3-month use of an interactive smartphone application as compared with standard care. Finally, in a pediatric population, the use of melatonin did not produce any changes in physical persistent concussion symptoms as compared with placebo. Preliminary evidence suggests that various forms of rehabilitative therapies can improve persistent physical concussive symptoms. However, given the methodological limitations in the majority of trials, the results need to be interpreted with caution.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".