Transcanal Endoscopic Ear Surgery for Congenital Cholesteatoma: A Multi‐institutional Series
Bibliographic record
Abstract
OBJECTIVE: To assess outcomes of transcanal endoscopic ear surgery (TEES) for congenital cholesteatoma. STUDY DESIGN: Case series with chart review of children who underwent TEES for congenital cholesteatoma over a 10-year period. SETTING: Three tertiary referral centers. METHODS: Cholesteatoma extent was classified according to Potsic stage; cases with mastoid extension (Potsic IV) were excluded. Disease characteristics, surgical approach, and outcomes were compared among stages. Outcomes measures included residual or recurrent cholesteatoma and audiometric data. RESULTS: Sixty-five cases of congenital cholesteatoma were included. The mean age was 6.5 years (range, 1.2-16), and the mean follow-up was 3.9 years (range, 0.75-9.1). There were 19 cases (29%) of Potsic stage I disease, 10 (15%) stage II, and 36 (55%) stage III. Overall, 24 (37%) patients underwent a second-stage procedure, including 1 with Potsic stage II disease (10%) and 21 (58%) with Potsic stage III disease. Eight cases (12%) of residual cholesteatoma occurred. One patient (2%) developed retraction-type ("recurrent") cholesteatoma. Recidivism occurred only among Potsic stage III cases. Postoperative air conduction hearing thresholds were normal (<25 dB HL) in 93% of Potsic stage I, 88% of stage II, and 36% of stage III cases. CONCLUSION: TEES is feasible and effective for removal of congenital cholesteatoma not extending into the mastoid. Recidivism rates were lower with the TEES approach in this large series than in previously reported studies. Advanced-stage disease was the primary risk factor for recidivism and worse hearing result. As minimally invasive TEES is possible in the youngest cases, children benefit from early identification and intervention.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".