Patients Treated with Vigabatrin Exhibit Central Visual Function Loss
Bibliographic record
Abstract
PURPOSE: To investigate visual function in the central 10 degrees in patients who have undergone vigabatrin (VGB) antiepileptic drug (AED) therapy with the aim of identifying a clinical regimen for assessing central visual function. METHODS: The sample comprised 12 epilepsy patients (mean age, 38.6 +/- 11.7 years) who had been treated with VGB (either as monotherapy or polytherapy). A number of central visual-function tests were carried out for each eye, including high-contrast LogMAR visual acuity, short-wavelength automated perimetry (SWAP 10-2), spatial contrast sensitivity (CSV-1000), and Farnsworth-Munsell (FM) 100-hue colour discrimination. RESULTS: The group mean cumulative VGB dose was 5,086 +/- 3,245 g. The average SWAP 10-2 mean deviation (MD) for the group was -3.24 +/- 3.23 dB; 14 eyes of eight patients showed defects (range, -1.62 to -9.46 dB). The square root of the group mean total error score for FM 100-hue was 7.42 +/- 3.84; nine eyes of five patients were classified as abnormal with an unsolved colour axis suggestive of complex drug interactions. For contrast sensitivity, 15 eyes of eight patients yielded abnormal results in one or more spatial frequencies. Defects were more prominent at higher spatial frequencies. Overall, four patients had defects in all three visual-function tests, six patients had mixed defects, and two patients were normal. CONCLUSIONS: Visual-function deficits in epilepsy patients treated with VGB are present in the central 10 degrees of the retina. We recommend a battery of investigations, including SWAP 10-2 and spatial contrast sensitivity testing, to assess central visual function.
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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 | 0.001 |
| 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) | 0.001 | 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".