Intraoperative Flash Visual Evoked Potential Recording and Relationship to Visual Outcome
Bibliographic record
Abstract
OBJECTIVE: To determine the relationship between intraoperative flash visual evoked potential (FVEP) monitoring and visual function. METHODS: Intraoperative FVEPs were recorded from electrodes placed in the scalp overlying the visual cortex (Oz) after flashing red light stimulation delivered by Cadwell LED stimulating goggles in 89 patients. Restrictive filtering (typically 10-100 Hz), optimal reject window settings, mastoid reference site, total intravenous anesthetic (TIVA), and stable retinal stimulation (ensured by concomitant electroretinogram [ERG] recording) were used to enhance FVEP reproducibility. RESULTS: The relationship between FVEP amplitude change and visual outcome was determined from 179 eyes. One eye had a permanent intraoperative FVEP loss despite stable ERG, and this eye had new, severe postoperative visual dysfunction. Seven eyes had transient significant FVEP change (>50% amplitude decrease that recovered by the end of surgery), but only one of those had a decrease in postoperative visual acuity. FVEP changes in all eight eyes (one permanent FVEP loss plus seven transient FVEP changes) were related to surgical manipulation. In each case the surgeon was promptly informed of the FVEP deterioration and took remedial action. The other eyes did not have FVEP changes, and none of those eyes had new postoperative visual deficits. CONCLUSIONS: Our FVEP findings relate to visual outcome with a sensitivity and specificity of 1.0. New methods for rapidly acquiring reproducible FVEP waveforms allowed for timely reporting of significant FVEP change resulting in prompt surgical action. This may have accounted for the low postoperative visual deficit rate (1%) in this series.
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".