Ensuring the Safe and Effective Use of Medications During Pregnancy: Planning and Prevention Through Preconception Care
Bibliographic record
Abstract
Whether to use a medication during pregnancy can be a concern for both women and health care providers. It has been estimated that up to 10% of congenital anomalies may be caused by environmental exposures–that is, exposures to medications, alcohol, or other exogenous factors that have adverse effects on the developing embryo or fetus [1]. Avoiding all potentially adverse exposures can prevent these adverse effects. However, it is not always possible to avoid taking medications during pregnancy. Women who are pregnant continue to experience short-term and long-term health conditions that must be managed. Discontinuing treatment of a serious condition when a woman becomes pregnant can have profound, long-term implications both for her health and that of her baby. In a retrospective study from eight health maintenance organizations, researchers estimated that approximately 59% of pregnant women were prescribed a medication other than a vitamin or mineral supplement at some time during pregnancy [2]. Use of over-the-counter medications during pregnancy may be even higher, and many women take a dietary or herbal supplement other than multivitamins or folic acid while pregnant [3, 4]. Preconception care provides the opportunity to optimize a woman’s use of medications in preparation for pregnancy. Such care includes identifying patterns of medication use before pregnancy occurs; adjusting those patterns to avoid the use of nonessential medications; minimizing exposure to medications known to be harmful to the embryo or fetus; and adjusting the dose, route of administration, and timing of essential treatments to optimize maternal health at each stage of pregnancy while safeguarding the embryo, fetus, and infant. In this paper, we summarize the basic principles of teratology and the current state of knowledge about the effects of medication use during pregnancy; outline basic components of preconception care that can help minimize the risk of birth defects; and provide examples of approaches to planning for the safe and effective use of medications during pregnancy through preconception care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".