Neural Tube Defects in Relation to Use of Folic Acid Antagonists during Pregnancy
Bibliographic record
Abstract
Periconceptional folic acid supplementation reduces the risk of neural tube defects (NTDs). To determine whether periconceptional exposure to folic acid antagonists (FAAs) might therefore increase the risk of NTDs, the authors examined data from an ongoing case-control study of birth defects (1979-1998) in the United States and Canada. They compared data on 1,242 infants with NTDs (spina bifida, anencephaly, and encephalocele) with data from a control group of 6,660 infants with malformations not related to vitamin supplementation. Mothers were interviewed within 6 months of delivery about demographic, reproductive, medical, and behavioral factors and about medication use. The adjusted odds ratios of NTDs related to exposure to FAAs (including carbamazepine, phenobarbital, phenytoin, primidone, sulfasalazine, triamterene, and trimethoprim) during the first or second months after the last menstrual period, compared with no use in either month, were 2.8 (95% confidence interval: 1.7, 4.6) for FAAs as a group, 4.8 (95% confidence interval: 1.5, 16.1) for trimethoprim (based on five exposed cases), and 6.9 (95% confidence interval: 1.9, 25.7) for carbamazepine (six exposed cases). These results are adjusted for region, interview year, periconceptional folic acid supplementation, maternal age, weight, education, and infections early in pregnancy. These findings suggest that a number of FAAs may increase NTD risk, and they provide estimates of risk for selected drugs.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".