Babies exposed to newer-generation antiepileptic drugs (compared with no antiepileptic drug exposure) in the first-trimester of pregnancy are not at increased risk of major birth defects
Bibliographic record
Abstract
Commentary on: Mølgaard-Nielsen D, Hviid A. Newer-generation antiepileptic drugs and the risk of major birth defects. JAMA 2011;305:1996–2002.[OpenUrl][1][CrossRef][2][PubMed][3] In the last few years, more information has been published regarding birth defects associated with the use of the new generation of antiepileptic drugs (AEDs). Some recent reports from different registries have shown a lower rate of major birth defects associated with the use of new generation AEDs compared with some of the first-generation AEDs. For example, an Australian registry showed no increase in major birth defects with the use of lamotrigine in the first trimester.1 But a North American registry reported a significant increase in the presence of oral clefts in infants exposed to lamotrigine during pregnancy, in contrast with a European registry which showed no association between rate of birth defects and the use of lamotrigine.2 3 Another study from Finland reported no increase in the rate of congenital malformations with the use of oxcarbazepine.4 Molgaard-Nielsen et al published a new study exploring the rate of birth defects associated with the use of some of the new AEDs. This study was based on the Danish medical birth registry. The study included 837 795 live born infants from January 1, 1996 through September 30, 2008. The patient information included in the registry … [1]: {openurl}?query=rft.jtitle%253DJAMA%26rft.stitle%253DJAMA%26rft.issn%253D0002-9955%26rft.aulast%253DMolgaard-Nielsen%26rft.auinit1%253DD.%26rft.volume%253D305%26rft.issue%253D19%26rft.spage%253D1996%26rft.epage%253D2002%26rft.atitle%253DNewer-Generation%2BAntiepileptic%2BDrugs%2Band%2Bthe%2BRisk%2Bof%2BMajor%2BBirth%2BDefects%26rft_id%253Dinfo%253Adoi%252F10.1001%252Fjama.2011.624%26rft_id%253Dinfo%253Apmid%252F21586715%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1001/jama.2011.624&link_type=DOI [3]: /lookup/external-ref?access_num=21586715&link_type=MED&atom=%2Febmed%2F17%2F2%2F66.atom
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.006 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".