FDA pregnancy risk categories and the CPS: do they help or are they a hindrance?
Bibliographic record
Abstract
QUESTION: My patient is taking a medication for a chronic condition and has just found out that she is 6 weeks pregnant. The US Food and Drug Administration (FDA) has assigned this medication to pregnancy risk category D, and the Compendium of Pharmaceuticals and Specialties provides no additional data. How should I interpret this information, and how does the Motherisk Program evaluate the safety or risks of drug use in pregnancy? ANSWER: Pregnancy safety data provided by the FDA pregnancy risk categories and the Compendium of Pharmaceuticals and Specialties are insufficient to guide clinical decisions on how to proceed with a pregnancy following exposure to a category D medication. The Motherisk Program creates peer-reviewed statements derived from the primary literature, and we examine fetal outcomes as well as the risk-benefit profile of maternal treatment when evaluating the safety of medication use in pregnancy. The FDA announced in May 2008 that it is dropping its pregnancy risk categories and adopting a method similar to the one we use at Motherisk.
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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 | 0.024 | 0.224 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.046 | 0.016 |
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".