Exposure to Nitrofurantoin During the First Trimester of Pregnancy and the Risk for Major Malformations
Bibliographic record
Abstract
Antibacterial drugs are among the most common medications used by pregnant women. While medical literature generally defines nitrofurantoin as an antibiotic that is safe for use during the first trimester of pregnancy, new concerns about a possible association between congenital malformations following exposure to nitrofurantoin during the first trimester of pregnancy have recently surfaced. To address these concerns, we conducted a large population-based retrospective cohort study to assess this possible association (including cases of medical terminations of pregnancy or stillbirth) and congenital malformations. A computerized database for medications dispensed to pregnant women in southern Israel was linked with records from the district hospital. Associations between exposure to nitrofurantoin during the first trimester and major malformations were assessed. Our research included a total of 105,492 pregnancies, 1,112 of which involved pregnancy terminations for medical reasons. A total of 1,329 infants and abortuses had been exposed to nitrofurantoin during the first trimester of pregnancy. Exposure to nitrofurantoin was not associated with increased risk of major malformations in general (adjusted OR = 0.85, 95% CI 0.67-1.08) or with specific malformations. First trimester exposure to nitrofurantoin was not associated with increased risk for total major congenital malformations or with specific malformations.
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 | 0.005 |
| 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 | 0.001 |
| 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".