The Risk of Postpartum Hemorrhage With Selective Serotonin Reuptake Inhibitors and Other Antidepressants
Bibliographic record
Abstract
OBJECTIVE: Limited evidence suggests that selective serotonin reuptake inhibitor (SSRI) antidepressants can hinder platelet aggregation and can increase the risk of hemorrhage. Because antenatal depression is common and is often treated with antidepressants, we sought to determine if exposure to SSRI antidepressants in late pregnancy is associated with an increased risk of postpartum hemorrhage compared with non-SSRI antidepressants. METHOD: This was a population-based nested case-control study of women aged 16 to 45 years in Ontario, Canada, who received government-funded prescription coverage within 2 years before delivery. We identified case patients with postpartum hemorrhage and matched controls (1:10) without postpartum hemorrhage from the same cohort. Controls were matched to cases on age, mode of delivery, parity, and calendar time. We linked prescription claims data to hospital and physician records for the study period (January 1999 to March 2005). Exclusion criteria included drugs and medical conditions that predispose to hemorrhage, and receipt of multiple antidepressants in the 6 months preceding delivery. Antidepressant drug exposure was classified as SSRI or other agents within 90 days before delivery. RESULTS: There were 2460 postpartum hemorrhage cases and 23,943 matched controls. The adjusted odds ratio for the association between postpartum hemorrhage and exposure to SSRIs within 90 days before index date was 1.30 (95% confidence interval, 0.98-1.72) as compared with 1.12 (95% confidence interval, 0.62-2.01) for non-SSRIs. CONCLUSIONS: Selective serotonin reuptake inhibitors confer no disproportionate risk of postpartum hemorrhage at the time of delivery compared with non-SSRI antidepressants. This information may help guide decisions regarding pharmacotherapy for depression during pregnancy.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".