Are there teratogenic risks associated with antidotes used in the acute management of poisoned pregnant women?
Bibliographic record
Abstract
OBJECTIVE: We reviewed evidence suggesting teratogenic risk associated with the use of antidotes in the acute management of poisoned pregnant women. METHODS: Medline, Toxline, and DART/ETIC searches; references of retrieved articles, pertinent databases and textbooks were also searched. RESULTS: There are case reports or case series of women who received antidotes for poisoning during (*) or after (+) the period of organogenesis who showed no fetal adverse effects. Some antidotes, however, have no teratogenic risk: atropine (cohort/surveillance studies)+, calcium (oral supplement: cohort study)+ and pyridoxine (Bendectin studies). Also, ethanol+, methylene blue (intra-amniotic injection but not oral) and penicillamine* can be considered teratogens but their risks in the treatment of poisonings are unknown. There is no epidemiologic study evaluating the risk of the following antidotes during pregnancy: N-acetylcysteine(*+), BAL (dimercaprol)+, black widow spider antivenin+, calcium EDTA+, crotalidae antivenin, crotalidae polyvalent immune FAB, cyanide antidote kit (amyl and sodium nitrate, sodium thiosulfate), deferoxamine(*+), digoxin immune FAB+, DMSA+, flumazenil+, fomepizole, methylene blue (IV), naloxone, physostigmine, pralidoxime+, protamine+; and parenteral pharmacologic doses of calcium+, folinic acid*, glucagon+, hydroxycobalamin, phytonadione (vitamin K), and pyridoxine. CONCLUSIONS: Despite the limited evidence supporting the risk of antidote use during pregnancy, antidotes should be used when there is a clear maternal indication to decrease the morbidity or mortality associated with poisoning. The only exception may be penicillamine, which is a teratogen. Better antidotes exist for most poisonings that penicillamine could potentially treat. At this time, there is no known fetal indication for all antidotes. Reporting the use of an antidote during pregnancy should be encouraged, especially if used during the critical period of organogenesis.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".