Prise en Charge des Fistules Labyrinthiques Cholestéatomateuses: A Propos de 22 Cas
Bibliographic record
Abstract
OBJECTIVE: To study the incidence, location, pre- and postoperative symptoms (hearing loss, tinnitus, vertigo, facial palsy), preoperative diagnostic imaging, and surgical treatment of labyrinthine fistulae (LF). DESIGN: Retrospective case review. PATIENTS: Twenty-two cases of LF over 382 mastoid operations performed in a 168-month period. MAIN OUTCOME MEASURES: Clinical, imaging, and surgical correlation of extensive fistulae and bone fistulae. RESULTS: LF prevalence was 5.8%. The main primary symptoms were otorrhea and hypoacusis. Only four patients presented vertigo as their main complaint. All patients underwent preoperative computed tomographic (CT) scans and preoperative audiometry. LF diagnosis was made before surgery for 100% of patients on the basis of CT scan. A second fistula was, however, misdiagnosed by imaging in two patients. With respect to surgical technique, a canal wall down procedure was performed in 77% and a conservative procedure was performed in 23%. Fistula was located in the horizontal semicircular canal in 100% of cases, and in 9%, a second fistula was operatively diagnosed. In 91% of cases, the matrix was removed, whereas it was left in the course of a canal down procedure in 9%. With a follow-up of 5.7 years, hearing remained unchanged in 80% of patients. CONCLUSIONS: Surgery with removal of the cholesteatoma matrix and sealing of the fistula with temporalis fascia is a safe procedure that can help preserve cochlear function. The choice of a canal down procedure would be influenced by cholesteatoma characteristics rather than by the finding of an LF.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".