Risk of Miscarriage in Women Receiving Antidepressants in Early Pregnancy, Correcting for Induced Abortions
Bibliographic record
Abstract
BACKGROUND: Earlier studies on the association between antidepressant use and miscarriage have obtained conflicting results after accounting for the role of depression, and none have taken into account the high risk of induced abortions in women using antidepressants. METHODS: We identified 41,964 pregnant women delivering between 1998 and 2002 using Quebec's health administration databases. We compared women prescribed antidepressants in the first trimester and with a recorded diagnosis of depression before pregnancy to (1) women with neither antidepressant use nor a depression diagnosis before or during pregnancy; (2) women with a depression diagnosis before pregnancy, but no antidepressants prescribed in the first trimester; and (3) women prescribed hypothyroid medication in the first trimester, but not antidepressants. We used log binomial regression to assess the adjusted relative risk of miscarriage, corrected for induced abortion risk. RESULTS: The miscarriage risk uncorrected for induced abortions was 16%, 10%, and 9% for depressed women exposed to antidepressants; unexposed depressed women; and unexposed, nondepressed women, respectively. These decreased to 11%, 8%, and 7% after correction for induced abortions. In multivariable analysis, the corrected risk of miscarriage relative to unexposed, nondepressed women was 1.3 (1.1-1.5) for antidepressant-exposed women and 1.1 (1.0-1.2) for unexposed depressed women. The miscarriage relative risk for antidepressant users compared with unexposed depressed women was thus 1.2 (1.0-1.4). CONCLUSIONS: Antidepressant use in the first trimester is associated with an increased risk of miscarriage when compared with either nondepressed or depressed unexposed women, even after accounting for induced abortions.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".