Cholesteatoma in Congenital Aural Atresia and External Auditory Canal Stenosis: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Patients with congenital external auditory canal (EAC) abnormalities are at risk of developing cholesteatoma and often undergo surveillance imaging to detect it. The aims of this systematic review are to determine the incidence of cholesteatoma in patients with congenital aural atresia (CAA) and patients with congenital EAC stenosis and to investigate the most common age of cholesteatoma diagnosis. This information will help clinicians decide which patients require surveillance scanning, as well as the timing of imaging. DATA SOURCES: Ovid MEDLINE, Embase, CENTRAL, and Web of Science databases. REVIEW METHODS: A systematic literature review following the PRISMA guidelines was performed. The data sources were searched by 2 independent reviewers, and articles were included that reported on CAA or congenital EAC stenosis with a confirmed diagnosis of cholesteatoma. The selected articles were screened separately by 3 reviewers before reaching a consensus on the final articles to include. Data collection on the number of patients with cholesteatoma and the age of diagnosis was performed for these articles. RESULTS: Eight articles met the inclusion criteria. The incidence of cholesteatoma was 1.7% (4/238) in CAA and 43.0% (203/473) in congenital EAC stenosis. The majority of patients with congenital EAC stenosis that developed cholesteatoma were diagnosed at age <12 years. CONCLUSION: CAA is associated with a low risk of cholesteatoma formation, and surveillance imaging is unnecessary in asymptomatic patients. EAC stenosis is strongly associated with cholesteatoma, and a surveillance scan for these patients is recommended prior to 12 years of age with close follow-up into adulthood.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".