Prevalence of Vestibular Dysfunction in Children With Neurological Disabilities: A Systematic Review
Bibliographic record
Abstract
Background: In children with neurological or neurodevelopmental conditions, vestibular disorders may co-exist with the primary condition and further contribute to disability and restriction in functional independence and participation. Awareness of their existence may favor an early diagnosis and better treatment outcomes. Objectives: To determine the prevalence of vestibular dysfunction in children and adolescents (3-21 years old) diagnosed with either cerebral palsy (CP), traumatic brain injury (TBI), sensorineural hearing loss (SNHL) or cochlear implantations (CI). Methods: Four researchers systematically reviewed the literature from three databases (EMBASE, MEDLINE, CINAHL) until June 2018. Results: Twenty-four studies were analyzed in this systematic review. A single, high-quality study reports a prevalence of 48.4% of spastic CP children having a saccular dysfunction. Three fair-quality studies report a prevalence of 14.6%-81%, 21 days post-TBI. Twelve poor-to-high quality studies demonstrate a prevalence of 18.7%-96.1% in children with SNHL. A prevalence range of 3%-84% of children with CI is reported by 9 fair-to-high quality studies. Conclusion: Clinicians should be aware of the prevalence of vestibular dysfunction in these populations and implement appropriate assessments to improve treatment outcomes.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".