GABA enhancing antiepileptic drug safer for human developing vs. mature retina
Bibliographic record
Abstract
Purpose: Infantile spasms (IS) is an age-specific epilepsy. The GABA enhancing drug vigabatrin (VGB) is used commonly for treatment. 30–40% adults incur vigabatrin attributed visual toxicity expressed as concentric visual field constriction. The surrogate marker for vigabatrin attributed toxicity in infants is reduction of ERG 30Hz flicker amplitude. Our purpose was to determine, in human infants, if age of onset of vigabatrin treatment contributes to the incidence of retinal toxicity. Methods: Prospective, longitudinal study including 130 patients with infantile spasms treated with VGB (age drug started 1–15 months of age). Sequential ERGs (ISCEV standards) were recorded at 3 or 6 month intervals. Contrast sensitivity and grating acuity were assessed with sweep visual evoked potentials. All data were age-corrected. Results: Sustained reduction of 30 Hz flicker was evident in approximately 1/3 of this cohort. At baseline (before drug treatment) contrast sensitivity was reduced. The highest prevalence of ERG dysfunction was in those treated after 9 vs. less than 9 months of age. Discussion: IS may be associated with less GABA in the CNS during early development. The lowered GABA levels might be associated with less lateral inhibition and reduced contrast sensitivity. Early treatment with VGB increases GABA in the brain and retina possibly compensating for early GABA deficiency. Later treatment may be associated with increased levels of retinal GABA which might be a contributing factor to VGB attributed toxicity.
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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) | 0.003 | 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".