Pharmacological Safety in Pregnancy: A Systematic Review On the Use of Potentially Teratogenic Drugs
Bibliographic record
Abstract
Objective: To assess the prevalence of potentially teratogenic drug utilization by pregnant women: overall and in the periconceptional period. Methods: The electronic database PubMed/Medline was searched for the following keywords: «pharmacoepidemiology», «pregnancy», «drug use», «safety», «pregnancy risk category», «fetal risk», «teratogen». The systematic analysis included 28 studies published in English from January 2006 to 23 December 2015. Results. The review shows that the study designs and the choices for data analysis and presentation of results differ largely across published studies. In the USA and Canada, measured rates of maternal use of contraindicated drugs (FDA category X) during pregnancy ranged from 2.4% to 5.3% (1.1–5.0% in the first trimester).The use of drugs with positive evidence of risk (FDA category D) ranged from 5.8% to 39.6% (2.7–6.0%). In European countries, proportions of women using drugs of risk categories X and D ranged from 1.0% to 4.9% (0.31–3.2%) and from 2.0% to 5.9% (1.6–3.7%), respectively. In developing countries, respective proportions of women ranged within 0.2–2.1% and 1.9–11.4%. In early pregnancy (the first trimester), the proportion of women taking potentially teratogenic drugs was high if compared with the second and third trimesters. The use of contraindicated drugs during pregnancy fastly decreases compared with the period before conception. Although the reduction of use of drugs with positive evidence of risk is less marked, possibly, with relation of their efficacy for the treatment of chronic conditions. On the base of analyzed studies, the reference list of potentially teratogenic drugs was formed. Conclusion. The results of published literature confirm differences in study methods that make it difficult to compare the application of potentially teratogenic drugs in pregnancy. The fundamental challenge remains an insufficiency or lack of available information on the evidence of risk to fetus cuased by the drugs that are most widely used in pregnancy.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".