P.141 The value of using flash visual evoked potentials monitoring during minimally invasive endoscopic meningioma resection: a retrospective chart review
Bibliographic record
Abstract
Background: Endoscopic endonasal surgeries performed in areas involving the visual pathway are associated with postoperative visual dysfunction. We previously demonstrated that continued eye monitoring during surgery by flash visual evoked potential (FVEP) represents a good method to prevent/reduce visual deficit post-surgery. We wondered whether FVEP monitoring may be more beneficial in patients with meningioma, strongly associated with postoperative visual loss. The aim was to explore the visual capacity in patients subjected to meningioma resection at The Ottawa Hospital. Methods: A retrospective chart review of patients who underwent minimally invasive endoscopic skull base surgery and FVEP monitoring for meningioma resection (July 2018 to present) was conducted. Only patients with available pre- (up to 3 months) and post-surgery (1-9 months) visual evaluation were analyzed. Results: 40 eyes were included (20 patients). The median age was 61 years (range:43-84) and 90% of patients were female. The LogMAR visual acuity was not significantly modified post-surgery (from +0.25 to +0.21; p=0.7). Color vision (# errors reading Ishihara/16-plates) was not modified post-surgery (from 2.6 to 3.2; p=0.6). Visual field (Humphrey, 32-2) was not significantly modified post-surgery (from 78.1% to 81.9%; p=0.7). Conclusions: The prevention of visual pathway injury during surgery by FVEP monitoring prevents visual deficits after endoscopic meningioma resection.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".