Challenges in assessing the use of antibiotics during pregnancy and risk of congenital malformations
Bibliographic record
Abstract
In a 2017 issue of Br J Clin Pharmacol, Muanda et al1 published an outstanding study titled “Use of antibiotics during pregnancy and the risk of major congenital malformations: a population based cohort study.” The objective of this study was to quantify the association between exposure to gestational antibiotics and the risk of major congenital malformations (MCMs) using the Quebec pregnancy cohort (1998-2008). They found that “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).” The authors concluded that “in utero exposure to clindamycin, doxycycline, macrolide, quinolone and phenoxymethylpenicillin increased the risk of organ-specific MCMS in infants.”1 There are no competing interests to declare.
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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 | 0.011 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".