International Pediatric Otolaryngology Group (IPOG) Consensus Recommendations: Congenital Cholesteatoma
Bibliographic record
Abstract
OBJECTIVE: To provide recommendations to otolaryngologists and allied physicians for the comprehensive management of children who present with signs and symptoms of congenital cholesteatoma. METHODS: A two-iterative Delphi method questionnaire was used to establish expert recommendations by the members of the International Pediatric Otolaryngology Group, on the preoperative work-up, the perioperative considerations, and follow-up. RESULTS: Twenty-two members completed the survey, in 14 tertiary-care center departments representing 5 countries. The main consensual recommendations were: a precise otoscopic description of the quadrants involved, extensive audiological workup (bilateral tonal, vocal audiometry, and BERA), and a CT scan are required. Facial nerve monitoring and a combination of microscope and telescope are recommended for surgical removal. Clinical and audiological follow-up should be pursued yearly for at least 5 years. First MRI follow-up should be done at 18 months postoperatively if the removal violated the matrix. MRI follow-up duration depends on the initial extent of the cholesteatoma. CONCLUSION: The goal of preoperative and follow-up consensus from International Pediatric Otolaryngology Group participants is to help manage infants and children with congenital cholesteatoma. The operative techniques may vary, and experienced surgeons must perform these procedures.
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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 | 0.027 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".