Psychotropic Drug Use before, during, and after Pregnancy: A Population-Based Study in a Canadian Cohort (2001-2013)
Bibliographic record
Abstract
OBJECTIVE: To describe the extent of increase in use and the rate of continuation versus discontinuation of psychotropic agents before, during, and after pregnancy. METHODS: Rates of psychotropic use (antidepressants, anxiolytic/sedative-hypnotics, antiepileptics, antipsychotics, lithium, stimulants) among women with a hospital-recorded pregnancy outcome were assessed using databases at the Manitoba Centre for Health Policy. Rate of use was defined as ≥1 prescription over the total number of pregnancies in the 3-12 months before pregnancy, 0-3 months before pregnancy, during pregnancy, or 3 months after pregnancy. Continued use was defined as ≥2 prescriptions with gap ≤14 days. Poisson regression was used to analyze trends. RESULTS: Over the study period, a psychotropic drug was used before, during, or after pregnancy in 41,923 of 224,762 pregnancies. From 2001 to 2013, psychotropic use increased 1.5-fold from 11.1% to 16.2% ( p < 0.0001) in the 3-12 months before pregnancy, 1.6-fold from 6.4% to 10.5% ( p < 0.0001) in the 3 months before pregnancy, 1.8-fold from 3.3% to 6.0% ( p < 0.0001) during pregnancy, and 1.5-fold from 6.2% to 9.5% ( p < 0.0001) in the 3 months postpartum. Among the 13,579 women who received at least 1 psychotropic agent in the 3 months prior to pregnancy, 38.5% stopped the agent prior to pregnancy and only 10.3% continued use throughout pregnancy. Continued use throughout pregnancy was higher (56.9%) among the 6693 women who received at least 2 prescriptions for a psychotropic agent and were at least 80% adherent in the 3 months prior to pregnancy. CONCLUSION: The use of psychotropic agents increased over 12 years. The safety of continuing versus discontinuing these agents during pregnancy remains uncertain, but we observed a decrease in psychotropic drug use during the pregnancy period.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".