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Record W4221086009 · doi:10.1055/s-0042-1743654

Outcomes in Vestibular Schwannoma Treated with Primary Microsurgery: Clinical Landscape

2022· article· en· W4221086009 on OpenAlexaff
Alexander Landry, Kaiyun Yang, Justin Z. Wang, Andrew Gao, Gelareh Zadeh

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2022
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSchwannomaVestibular systemCerebellopontine angleMicrosurgeryMedicineRadiologySurgeryMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Objective: Vestibular schwannoma (VS) is the most common tumor of the cerebellopontine angle. Owing to complex anatomy and high rates of morbidity, surgical management of large tumors is challenging. In this study, we seek to explore the clinical landscape of VS in order to identify predictors of outcome and help guide surgical decision making. Methods: We retrospectively reviewed charts of patients who underwent surgery as the initial treatment modality for VS between 2005 and 2020 at a quaternary referral center in Toronto, Canada. Mined data includes patient demographics, clinical presentation, radiological features, and treatment details. Regression modeling was used to identify predictors of tumor control, postoperative morbidity, and correlates of progression free survival (PFS). Results: Two hundred and five tumors, all of which underwent initial operative treatment and contained sufficient data for meaningful analysis, were included in our study. Syndromic NF2, larger tumors (>3 cm), subtotal resection (as compared to gross-total resection), presence of edema on preoperative MRI, and preoperative trigeminal symptoms were all predictors of postoperative progression/recurrence or need for further treatment, and the latter four were also significant correlates of a shorter progression free survival ([ Fig. 1A ]). Extent of resection (EOR), tumor size, and Koos’ grade were independently predictive of postoperative progression/recurrence or secondary intervention in multivariate models; however, only EOR was independently predictive of progression-free survival ([ Fig. 1B ]). EOR, tumor size, and patient age are each independently predictive of facial nerve outcome. A small group of Koos’ grade 4 tumors were treated with subtotal resection and planned adjuvant radiotherapy ( n = 5); all experienced tumor control with minimal morbidity. Conclusion: We comprehensively explore the clinical landscape of surgically treated vestibular schwannoma and find extent of resection to be significantly associated with tumor control and facial nerve dysfunction in large tumors. Additional correlates of key outcome measures include preoperative trigeminal symptoms, preoperative edema, and tumor size. This may have important implications in risk stratifying these challenging cases. Fig. 1 Kaplan Meier curves of progression/recurrence. An event is defined as progression after initial surgery, without intervening therapy. ( A ) Univariate Kaplan Meier curves of preoperative edema on MRI, EOR, preoperative trigeminal dysfunction, and preoperative size. ( B ) Effect of EOR on PFS, stratified by preoperative edema (top), preoperative trigeminal symptoms (middle), and preoperative size (bottom). Publication History Article published online: 15 February 2022 © 2022. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 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)0.003
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.279
Teacher spread0.230 · 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
Published2022
Admission routes1
Has abstractyes

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