Cochleovestibular Anomalies in Children With Cholesteatoma
Bibliographic record
Abstract
OBJECTIVE: To describe the cochleovestibular apparatus on computed tomography (CT) imaging in patients with cholesteatoma. We asked whether cochleovestibular anomalies coexist in individuals with cholesteatoma. STUDY DESIGN: Randomized, controlled, prospective measurement. METHODS: A database search yielded 145 children with cholesteatoma: 31 met inclusion criteria by not having sensorineural hearing loss, not having an associated syndrome, and having digitally stored temporal bone CT imaging available. Prospective measurement of 31 individuals (62 ears) with unilateral cholesteatoma and 32 normally hearing nonsyndromic controls (64 ears) was performed by a neuroradiologist blinded to the study objective. Twenty-six temporal bone aspects on axial imaging were evaluated (16 measurement, 10 calculated from measurement). RESULTS: The cholesteatoma group had a larger endolymphatic fossa and vestibular aqueduct, and there was a trend for the lateral semicircular canal vestibule to be smaller as compared with controls. Subgroup analysis revealed a gradient in prevalence of these findings being most common in the congenital cholesteatoma group, intermediate in the acquired cholesteatoma group, and least common in controls. There were no differences in measurements between ears with cholesteatoma and contralateral disease-free temporal bones. CONCLUSIONS: Children with cholesteatoma have abnormal vestibular anatomy. The gradient in prevalence of these findings may suggest a relationship between congenital and acquired cholesteatoma. These may include a generalized temporal bone anomaly that predisposes to cholesteatoma formation, or a third variable such as genetic mutation may predispose to both anomalous cochleovestibular formation and cholesteatoma.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".