Repetitive Transcranial Magnetic Stimulation in Adolescents With Persistent Postconcussion Symptoms After Mild Traumatic Brain Injury: An Open Label Safety and Feasibility Study
Bibliographic record
Abstract
Introduction Although most children and adolescents with a mild traumatic brain injury (mTBI) recover quickly, a significant minority develop intractable headaches, cognitive difficulties, and/or mood disturbances known as persistent post-concussion symptoms (PPCS). Repetitive transcranial magnetic stimulation (rTMS) offers significant therapeutic potential in PPCS. Methods Fourteen adolescents (15.6 ± 1.5 years, 10 females) with PPCS ≥ 3 months post-injury (median: 4, 3-16 months) were recruited into an open label, single centre, safety/feasibility rTMS trial. Four weeks of once daily rTMS (20 visits, 10 Hz at 120% of resting motor threshold, 3000 stimulations per session) was applied to the left dorsolateral prefrontal cortex (DLPFC). Adverse events were monitored at every treatment. Additional outcomes included the Post-Concussion Symptom Inventory (PCSI) and Pediatric Quality of Life Inventory (PedsQL). Results No serious adverse events were observed. Headaches were the most frequent adverse event; but headaches tended to decrease in frequency over the treatment course. Twelve out of 14 participants attended 90% or more of the rTMS sessions. After four weeks of rTMS, PCSI total scores decreased from pre-rTMS values by 27.5 ± 20.9 points ( Z = -3.3, P < 0.001) and PedsQL total scores increased by 12 ± 12.6 points ( t 13 = -3.5, P = 0.004). One-month post-rTMS, PedsQL scores were still increased but PCSI scores were not different from baseline. Conclusions High frequency rTMS to the left DLPFC is safe/feasible for adolescents with PPCS. Results provide data to inform large randomised, sham-controlled trials to explore the efficacy of rTMS to treat pediatric 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".