Use of antibiotics during pregnancy and the risk of major congenital malformations: a population based cohort study
Bibliographic record
Abstract
AIMS: Few studies have investigated the link between individual antibiotics and major congenital malformations (MCMs) including specific malformations owing to small sample size. We aimed to quantify the association between exposure to gestational antibiotic and the risk of MCMs. METHODS: Using the Quebec pregnancy cohort (1998-2008), we included a total of 139 938 liveborn singleton alive whose mothers were covered by the "Régie de l'assurance maladie du Québec" drug plan for at least 12 months before and during pregnancy. Antibiotic exposure was assessed in the first trimester and MCMs were identified within the first year of life. RESULTS: After adjusting for potential confounders, clindamycin exposure was associated with an increased risk of MCMs (aOR 1.34, 95% CI 1.02-1.77, 60 exposed cases), musculoskeletal system malformations (aOR 1.67, 95% CI 1.12-2.48, 29 exposed cases) and ventricular/atrial septal defect (aOR 1.81, 95% CI 1.04-3.16, 13 exposed cases). Doxycycline exposure increased the risk of circulatory system malformation, cardiac malformations and ventricular/atrial septal defect (aOR 2.38, 95% CI 1.21-4.67, 9 exposed cases; aOR 2.46, 95% CI 1.21-4.99, 8 exposed cases; aOR 3.19, 95% CI 1.57-6.48, 8 exposed cases, respectively). Additional associations were seen with quinolone (1 defect), moxifloxacin (1 defect), ofloxacin (1 defect), macrolide (1 defect), erythromycin (1 defect) and phenoxymethylpenicillin (1 defect). No link was observed with amoxicillin, cephalosporins and nitrofurantoin. Similar results were found when penicillins were used as the comparator group. CONCLUSIONS: Clindamycin, doxycycline, quinolones, macrolides and phenoxymethylpenicillin in utero exposure were linked to organ-specific malformations. Amoxicillin, cephalosporins and nitrofurantoin were not associated with MCMs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".