Long term health and neurodevelopment in children exposed to antiepileptic drugs before birth
Bibliographic record
Abstract
OBJECTIVE: To investigate the frequency of neonatal and later childhood morbidity in children exposed to antiepileptic drugs in utero. DESIGN: Retrospective population based study. SETTING: Population of the Grampian region of Scotland. PARTICIPANTS: Mothers taking antiepileptic drugs in pregnancy between 1976 and 2000 were ascertained from hospital obstetric records and 149 (58% of those eligible) took part. They had 293 children whose health and neurodevelopment were assessed. MAIN OUTCOME MEASURES: Frequencies of neonatal withdrawal, congenital malformations, childhood onset medical problems, developmental delay, and behaviour disorders. RESULTS: Neonatal withdrawal was seen in 20% of those exposed to antiepileptic drugs. Congenital malformations occurred in 14% of exposed pregnancies, compared with 5% of non-exposed sibs, and developmental delay in 24% of exposed children, compared with 11% of non-exposed sibs. After excluding cases with a family history of developmental delay, 19% of exposed children and 3% of non-exposed sibs had developmental delay, 31% of exposed children had either major malformations or developmental delay, 52% of exposed children had facial dysmorphism compared with 25% of those not exposed, 31% of exposed children had childhood medical problems (13% of non-exposed sibs), and 20% had behaviour disorders (5% of non-exposed). CONCLUSION: Prenatal antiepileptic drug exposure in the setting of maternal epilepsy is associated with developmental delay and later childhood morbidity in addition to congenital malformation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".