Sanna Classification and Prognosis of Cholesteatoma of the Petrous Part of the Temporal Bone
Bibliographic record
Abstract
OBJECTIVE: To determine how classification of petrous bone cholesteatomas (PBCs) using the 5-point Sanna classification can predict major structural involvement, facial nerve outcomes, hearing outcomes, postoperative complications, and disease recurrence. STUDY DESIGN: Retrospective case series. SETTING: Tertiary referral center in Bergamo, Italy. PATIENTS: Eighty-one sequential patients with radiologic and surgically confirmed diagnoses of PBC treated at a single tertiary referral center during a 20-year period. MAIN OUTCOME MEASURES: Major structural involvement, facial nerve outcomes, hearing outcomes, postoperative cerebrospinal fluid leak, and disease recurrence were evaluated on the basis of Sanna classification. RESULTS: Using the Sanna classification, 70% (57) were supralabyrinthine, 12% (10) infralabyrinthine, 7% (6) infralabyrinthine-apical, 5% (4) apical, and 5% (4) massive. Massive classification was statistically significantly associated with cochlear involvement (p = 0.009) and internal auditory canal involvement (p = 0.02). The infralabyrinthine-apical class was associated with carotid canal involvement (p = 0.03). Facial nerve interruption was observed in 35% of patients and most frequently in the apical group (75%). Neither hearing nor facial nerve outcomes were associated with Sanna classification. House-Brackmann score improved or was maintained postoperatively in 89% of patients. CONCLUSION: The Sanna classification provides anatomic detail on location of PBCs and is predictive of IAC, cochlear, and carotid artery involvement. However, classification systems for this rare condition continue to pose a challenge in being able to accurately predict facial nerve and hearing outcomes in surgical obliteration of PBC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".