Paroxetine Use During Pregnancy and Perinatal Outcomes Including Types of Cardiac Malformations in Quebec and France: A Short Communication
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Antidepressants, more specifically SSRIs, represent one example of a widely prescribed class of medications in pregnant women for which less than adequate pregnancy data have been available since the first drug in this class was marketed 20 years ago. Moreover, findings from studies performed after 2005, when health governmental authorities issued warnings regarding first trimester exposure to paroxetine and the risk of cardiac malformations, may be the result of detection bias if physicians were investigating more their pregnant patients that used paroxetine than the others. OBJECTIVES: To estimate the prevalence of 1) paroxetine use during pregnancy, and 2) diagnosed cardiac malformations in the Quebec and France populations. METHODS: Two distinct pregnancy databases were used for this ecologic study: the Quebec Pregnancy Registry and the French EFEMERIS database. RESULTS: In Quebec, among the 109,344 eligible pregnancies, 1,612 (1.5%) were exposed to paroxetine. Prevalence of paroxetine use during pregnancy increased from 0.7% to 1.2% between 1998 and 2003, simultaneously to the increase of the prevalence of cardiac malformation diagnoses. In France, among 40,317 eligible pregnancies, 173 (0.4%) were exposed to paroxetine; between 2004 and 2008 the number of paroxetine fillings and cardiac malformation diagnoses remained constant. CONCLUSIONS: Despite differences in the Quebec and French healthcare systems, increase in paroxetine prevalence use during pregnancy was already consistent with an increase in the prevalence of cardiac malformations, even before the warning on the risk of cardiac malformations in newborns in 2005-2006, limiting the possibility of detection bias.
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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) | 0.000 | 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 it