Vestibular Schwannoma Cerebellopontine Angle Position Impacts Facial Outcome
Bibliographic record
Abstract
Objectives/Hypothesis To determine the impact of vestibular schwannoma (VS) position relative to the internal auditory canal (IAC) on postoperative facial nerve function and extent of surgical resection. Study Design Retrospective chart review. Methods Retrospective review of patients undergoing resection of large (≥25 mm) VSs. Outcome measures included early (≤1 month) facial function, long‐term (≥1 year) facial function and extent of resection. Tumor measurements included the greatest dimension, dimension anterior to the IAC axis, dimension posterior to the IAC axis, and a ratio of posterior‐to‐anterior dimension (PA ratio). Results A total of 127 patients met inclusion criteria. In early follow‐up, 60% patients had good (House‐Brackmann I–II), and 40% patients had poor (House‐Brackmann III–VI) facial function. In long‐term follow‐up, 71% patients had good, and 29% patients had poor facial function. A total of 72% of patients underwent gross total resection (GTR) of their tumors. Patients with good facial function had significantly larger PA ratios than patients with poor function both early and long term; however, greatest dimension was the more clearly significant independent predictor of facial outcomes. A larger PA ratio was observed in patients in whom GTR was achieved, but this association was potentially confounded by surgeon preferences and was not statistically significant after controlling for surgical site. Conclusions This study demonstrates that VS position relative to the IAC axis can be used along with tumor size to predict postoperative facial outcomes. A greater proportion of tumor posterior to the IAC axis was associated with significantly better facial outcomes. Level of Evidence 4 Laryngoscope , 132:1093–1098, 2022
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".