Neurodevelopment of children exposed in utero to lamotrigine, sodium valproate and carbamazepine
Bibliographic record
Abstract
OBJECTIVE: To establish the relative risks of in utero exposure to lamotrigine (LTG), sodium valproate (NaV) and carbamazepine (CBZ) monotherapy for neurodevelopment. DESIGN: Observational cohort study. PATIENTS AND METHODS: The study group consisted of children in Northern Ireland aged 9-60 months born to mothers who had enrolled with the UK Epilepsy and Pregnancy Register. The control group consisted of children identified from the Child Health System database across Northern Ireland. Data were gathered on covariates recognised as influencing child development. MAIN OUTCOME MEASURES: Neurodevelopment assessed using either the Bayley Scales of Infant Development or the Griffiths Mental Development Scales. RESULTS: 210 children underwent assessment by a single researcher blinded to antiepileptic drug exposure. 23 (39.6%) children exposed in utero to NaV, 10 (20.4%) exposed to CBZ and one (2.9%) exposed to LTG had evidence of mild or significant developmental delay, compared to two (4.5%) children in the control group. Multivariable analysis demonstrated that in utero exposure to NaV (OR 26.1, 95% CI 4.9 to 139; p<0.001) and to CBZ (OR 7.7, 95% CI 1.4 to 43.1; p<0.01) but not to LTG had a significant detrimental effect on neurodevelopment. CONCLUSION: In utero exposure to LTG did not have the detrimental effect on child development that was seen with NaV and with CBZ.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".