A Pilot Randomised Double-Blind Study of the Tolerability and efficacy of repetitive Transcranial Magnetic Stimulation on Persistent Post-Concussion Syndrome
Bibliographic record
Abstract
This study investigates the effect of Repetitive Transcranial Magnetic Stimulation (rTMS) on persistent post-concussion syndrome (PCS). The study design was a randomized (coin toss), placebo controlled, and double-blind study. Thirty-seven participants with PCS were assessed for eligibility; 22 were randomised and 18 completed the study requirements. Half the participants with PCS were given an Active rTMS intervention and the other half given Sham rTMS over 3 weeks. Follow ups were at the end of treatment and at 30 and 60 days. The primary outcome measure was the Rivermead Post-Concussion Symptoms Questionnaire (RPQ3 & RPQ13). The results indicate participants with more recent injuries (<12 month), who received Active rTMS, showed significant improvements compared to those of: 1) the same subgroup who received Sham, and 2) those with a longer duration of injury (>14 months) who received Active rTMS. This improvement predominantly manifested in RPQ13 in the follow up periods 1 and 2 months after the intervention (RPQ13 change (mean ± SD): at 1 month, Active = -21.8 ± 6.6, Sham = -2.2 ± 9.8; at 2 months, Active = -21.2 ± 5.3, Sham = -5.4 ± 13.7). No improvement was found in the subgroup with longer duration injuries. The results support rTMS as a tolerable and potentially effective treatment option for individuals with a recent (<1 year) concussion.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".