Vestibular Dysfunction Following Paediatric Traumatic Brain Injury – exploration of a novel diagnostic tool
Bibliographic record
Abstract
Background: It is well established that vestibular injury can occur with traumatic brain injury (TBI). Symptoms that could be related to vestibular dysfunction rather than a brain injury include vertigo, dizziness, and imbalance. Reports indicate that the incidence of dizziness or imbalance secondary to vestibular dysfunction may occur in up to 83% of adults following mild TBI but there are few studies examining this in children. It is difficult, but clinically very relevant, to differentiate symptoms due to vestibular injury as the treatment is very different. Objective: 1) To examine the symptom of dizziness in children with TBI and 2) Investigate the prevalence of vestibular dysfunction in children following a TBI using a novel diagnostic technique. Methods: Prospective cohort study. Population: Children aged 11-18 years with a) mild TBI presenting to the Emergency Department (ED) (acute/subacute); and b) mild to severe TBI symptomatic ≥1 month post-injury (chronic). Outcome measures: A new questionaire about dizziness for kids DizzyKids. Vestibular testing was performed using the Head Impulse test and ICS Impulse goggles, a novel diagnostic tool. Results: Thirty children (21 males), aged 14.3 (SD+/-2.3) years were enrolled. True “vertiginous” symptoms were not associated with semicircular canal dysfunction. There was a 10% prevalence of vestibular dysfunction in both groups. Conclusion: Vestibular dysfunction secondary to head trauma occurs in 10% of children with acute mild TBI and in those with chronic post-concussive symptoms. The DizzyKids Questionnaire and ICS Impulse goggles were useful and well tolerated in the pediatric population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".