P.096 Hearing preservation and quality of life outcomes in partial labyrinthectomy petrous apicectomy for microsurgical resection of large posterior fossa skullbase tumors
Bibliographic record
Abstract
Background: The Partial Labyrinthectomy Petrous Apicectomy (PLPA) aims to give transpetrosal access whilst preserving hearing for challenging tumors such as petroclival meningioma. There are few studies assessing resection and morbidity and no large studies that document hearing preservation and quality of life (QOL). We present the first large series to do so. Methods: A retrospective review was performed of all PLPA cases between 2005 and 2023 at a tertiary center. Demographics, tumor characteristics, neuromonitoring, hearing and surgical outcomes were collected. QOL was measured with the 36-item short form survey (SF-36). Results: Of 73 PLPAs, data for 56 patients undergoing 57 surgeries was obtained. Petroclival meningioma (57.8%) and epidermoid tumors (21.0%) were common indications . The mean patient age and tumor size were 51.6 years and 44mm. Gross total resection was achieved in 40.3%, near total in 15.8% and subtotal in 43.8% of cases with no perioperative mortality and was not influenced by attempted hearing preservation (p=0.183). Of 39 hearing preservation cases, 27 (69.2%) were preserved, 10 (25.6%) were lost and 2 had unclear outcomes. Conclusions: Improved microsurgery and neuromonitoring during PLPA leads to decreased mortality and morbidity compared to historical cohorts while achieving a high rate of resection, hearing preservation and maintained QOL.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".