Accelerated repetitive transcranial magnetic stimulation in the treatment of post-concussion symptoms due to mild traumatic brain injury: a pilot study
Bibliographic record
Abstract
Objective: To investigate the feasibility, tolerability, and efficacy of twice-daily, low frequency (LF) repetitive transcranial magnetic stimulation (rTMS) over the right dorsolateral prefrontal cortex (DLPFC) in the reduction of chronic post-concussion symptoms (PCS) in patients who have suffered a mild traumatic brain injury (mTBI).Methods: 15 patients with mTBI received 30 sessions of twice-daily LF rTMS (1 Hz) over the right DLPFC. Post-concussion symptoms, pain, disability, fatigue, apathy, agitation, and mood were assessed by a psychiatrist pre- and post-treatment. Cognitive testing was also performed pre-, mid-, and post-rTMS.Results: All participants completed treatment with no serious adverse events. Significant improvements were observed in overall post-concussion symptoms, disability and pain ratings, as well as depression and anxiety symptoms. There was no significant change in overall executive functioning, fatigue severity, apathy, or agitation. Cognitive testing revealed improvements in verbal fluency, working memory, selective attention, and cognitive processing speed.Conclusions: This small-sample pilot study suggests that twice-daily, LF rTMS over the right DLPFC can be safely and tolerably applied and has the potential to improve post-concussion symptoms as well as elements of mood and cognition in patients with mTBI. Larger, sham-controlled studies will be important to confirm these observations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".