Does vigabatrin treatment for infantile spasms cause visual field defects? An international multicentre study
Bibliographic record
Abstract
AIM: The aim of this study was to examine whether vigabatrin treatment had caused visual field defects (VFDs) in children of school age who had received the drug in infancy. METHOD: In total, 35 children (14 males, 21 females; median age 11y, SD 3.4y, range 8-23y) were examined by static Humphrey perimetry, Goldmann kinetic perimetry, or Octopus perimetry. The aetiologies of infantile spasms identified were tuberous sclerosis (n=10), other symptomatic causes (n=3), or cryptogenic (n=22). RESULTS: Typical vigabatrin-attributed VFDs were found in 11 out of 32 (34%) children: in one out of 11 children (9%) who received vigabatrin for <1 year (group 1), in three out of 10 children (30%) who received vigabatrin for 12 to 24 months (group 2), and in seven out of 11 children (63%) who received vigabatrin treatment for longer than 2 years (group 3). VFDs were mild in five and severe in six children. Patients with tuberous sclerosis were at higher risk of VFDs (six out of 10 children). The mean cumulative doses of vigabatrin were 140.5, 758.8, and 2712g in group 1, 2, and 3, respectively. INTERPRETATION: VFDs were found in 34% of the cohort of children in this study. The rate of VFD increased from 9% to 63% as duration of treatment increased. The results of this study showed that the risk-benefit ratio should always be considered when using vigabatrin.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".