Cortical excitability after pediatric mild traumatic brain injury
Bibliographic record
Abstract
INTRODUCTION: Mild traumatic brain injury (mTBI) outcomes are variable, and 10-15% may suffer from prolonged symptoms beyond 3 months that impair the child's return to normal activities. Neurophysiological mechanisms of mTBI are incompletely understood, particularly in children, but alterations in cortical excitability have been proposed to underlie post-concussion syndrome. Improved understanding is required to advance interventions and improve outcomes. OBJECTIVE/HYPOTHESIS: To determine if cortical excitability is altered in children with mTBI, and its association with clinical symptoms. METHODS: This was a cross-sectional controlled cohort study. School-aged children (8-18 years) with mTBI were compared to healthy controls. Cortical excitability was measured using multiple TMS paradigms in children with (symptomatic) and without (recovered) persistent symptoms one-month post-injury. Primary outcome was the cortical silent period (cSP), a potential neurophysiological biomarker of GABAergic inhibition. Secondary outcomes included additional TMS neurophysiology, safety and tolerability. Associations between neurophysiology parameters and clinical symptoms were evaluated. RESULTS: long interval intracortical inhibition (LICI) was reduced in symptomatic participants compared to healthy controls (F (2, 59) = 3.83, p = 0.027). Procedures were well tolerated with no serious adverse events. CONCLUSIONS: TMS measures of cortical excitability are altered at one month in children with mTBI. Long interval cortical inhibition is decreased in children who remain symptomatic at one month post-injury.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".