Maternal characteristics associated with pregnancy exposure to FDA category C, D, and X drugs in a Canadian population
Bibliographic record
Abstract
PURPOSE: To estimate the frequency of exposure to prescription Food and Drug Administration (FDA) category C, D, and X drugs in pregnant women, and to analyze the maternal characteristics associated with such an exposure. METHODS: A 50% random sample of women who gave a birth in Saskatchewan between January 1, 1997 and December 31, 2000 was chosen for the study. The rate of exposure to FDA category C, D, or X drugs recorded in the pharmacist database was estimated. Associations of exposure to FDA category C, D, and X drugs with maternal characteristics were evaluated using multiple logistical regression, with adjusted odds ratios (ORs) and its 95% confidence intervals (CIs) as the association measures. RESULTS: A total of 18 575 women were included in this study. Among them, 3604 (19.4%) had exposure to one or more FDA category C, D, and X drugs during pregnancy. Category C drugs were the most frequently used drugs (15.8%), followed by D drugs (5.2%), and X drugs (3.9%). Women with chronic health conditions had fourfold at increased risk of exposure than women without. Regardless of health status, women who were <20 years of age, who had a parity > or =3, and who were on social assistance plan were at increased risk of pregnancy exposure to these drugs. CONCLUSIONS: About 19.4% pregnant women are exposed to FDA C, D or X drugs during pregnancy. Women with chronic diseases, younger age, increased parity, and under social assistance are at increased risk of exposure to FDA C, D, or X drugs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".