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Record W4407249979 · doi:10.1055/s-0045-1803242

Partial Labyrinthectomy Petrous Apicectomy for Large Petroclival Meningiomas: Hearing Preservation Rate and Quality-of-Life Outcomes

2025· article· en· W4407249979 on OpenAlexaff
David Chi Hau Tan, Jeremy Kam, Benjamin Brakel, Serge Makarenko, Brian D. Westerberg, Ryojo Akagami

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2025
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsUniversity of British ColumbiaVancouver General Hospital
Fundersnot available
KeywordsMedicineAudiology

Abstract

fetched live from OpenAlex

Background: The petroclival region is generally considered a challenging area to be accessible surgically due to the depth and the surrounding delicate neurovascular structures. Various operative techniques have been described for resection of tumors in this area including retrosigmoid, presigmoid retrolabyrinthine and translabyrinthine approaches. The partial labyrinthectomy petrous apicectomy (PLPA) approach involves removal of the superior and posterior semicircular canals following mastoidectomy, with preservation of the endolymph to maintain hearing. This is followed by skeletonization of the internal acoustic meatus and drilling of the petrous apex to increase exposure. Removal of the two semicircular canals increases the working angle whilst preserving hearing. We present hearing preservation rate and long-term quality of life outcomes for patients who underwent PLPA approach for removal of petroclival meningiomas. Methods: We carried out a retrospective review of all patients who had PLPA operation for petroclival meningoma resection between 2002 and 2024 at a large tertiary center. We collected data on patient demography, tumor size, pre- and postoperative hearing assessment by the Otolaryngologist and formal audiometry, quality of life data using the 36-Item Short Form Survey (SF-36). Results: Thirtyfour out of 41 patients had data available for collection (10 males, 24 females). The mean age was 53.8 years old and the average tumor size was 43.4 mm. Two patients had postoperative leak of cerebrospinal fluid (5.9%)—one resolved with the use of a lumbar drain, the other required return to theatre for repair. Majority of the patients had a World Health Organization (WHO) grade 1 meningioma, whilst six of them had a grade 2 meningioma. Six patients had poor, non-serviceable hearing preoperatively. Out of the 28 patients who had PLPA operation with the aim of preserving hearing, 9 patients did not have follow-up hearing assessment, 15 patients had preserved and serviceable hearing post-operatively, and four patients had worse hearing. Overall, the hearing preservation rate is 78.9% (15 out of 19) with an average follow-up of 14.1 months. Preoperative and postoperative SF-36 data were collected and scored for all eight domains of the physical and mental components. These were divided into short-term (up to 3 months), medium-term (3–12 months), and long-term (12–24 months) follow-up. The patients had transient reduction in the physical component scores during short-term reviews postoperatively, with subsequent improvement in all domains during medium-term and long-term follow-up. Conclusion: In conclusion, we achieved a hearing preservation rate of 78.9% for patients who underwent PLPA operation for large petroclival meningiomas, with two patients experiencing CSF leak postoperatively. These patients achieved satisfactory quality of life on medium and long-term follow-up. Publication History Article published online: 07 February 2025 © 2025. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.115
GPT teacher head0.344
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractno

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