A survey of pregnant women using isotretinoin
Bibliographic record
Abstract
BACKGROUND: Isotretinoin is a known human teratogen, causing birth defects and/or subnormal cognitive performance in prenatally-exposed children. METHODS: A survey was conducted among women who called teratology information services throughout North America. Using a structured questionnaire, women with an isotretinoin-exposed pregnancy were prospectively interviewed before the outcome of the pregnancy was known. RESULTS: Almost 1/4 of the women surveyed (24%; 8/34) did not recall having contraception counseling before starting their medications. Once therapy was initiated, 62% (21/34) recalled using a birth control method, but only 29% (6/21) recalled using 2 forms of birth control, as specified by the voluntary pregnancy prevention programs. Monthly pregnancy tests were not always conducted during treatment, as recalled by the surveyed women (56%; 19/34). As many as 24% (8/34) of the women surveyed recalled that they were not screened using 2 pregnancy tests before receiving a prescription, another recommendation of the programs. Only a small number of the women (30%; 6/20) in the United States recalled being enrolled in any manufacturers' voluntary pregnancy prevention survey. CONCLUSIONS: Results demonstrate that essential components of voluntary pregnancy prevention programs were not consistently followed, which resulted in fetal exposures.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".