Postpartum Hemorrhage and Use of Serotonin Reuptake Inhibitor Antidepressants in Pregnancy
Bibliographic record
Abstract
OBJECTIVE: To examine whether using selective serotonin reuptake inhibitors and selective serotonin-norepinephrine reuptake inhibitors in pregnancy is associated with an increased risk of postpartum hemorrhage. METHODS: We conducted a population-based cohort study including 225,973 women with 322,224 pregnancies in British Columbia, Canada, between 2002 and 2011. Women were categorized according to whether they had late-pregnancy exposure (at least 15 of the last 30 days of pregnancy), midpregnancy exposure (in the last 5 months of pregnancy but not the final 30 days), or no exposure. Postpartum hemorrhage was identified using International Classification of Diseases (9th and 10th Revisions) codes in data on all hospitalizations. RESULTS: We found an increased risk of postpartum hemorrhage associated with exposure to an serotonin-norepinephrine reuptake inhibitor in the final month of pregnancy after adjustment for potential confounders (n=1,390; adjusted odds ratio [OR] 1.76, 95% confidence interval [CI] 1.47-2.11, respectively) corresponding to 4.1 (95% CI 2.4-5.7) additional cases of postpartum hemorrhage per 100 people treated. There was no significant relationship between selective serotonin reuptake inhibitor use in the final month of pregnancy and postpartum hemorrhage (n=6,637; adjusted OR 1.09, 95% CI 0.98-1.21), except when confining the cohort to women with complete body mass index (BMI) information (n=235,031 [73%]) and controlling for BMI (adjusted OR 1.14, 95% CI 1.01-1.28) or when controlling for variables that are possibly on the causal pathway (adjusted OR 1.13, 95% CI 1.02-1.26). Midpregnancy exposure to a serotonin-norepinephrine reuptake inhibitor (n=242) or a selective serotonin reuptake inhibitor (n=1,507) was not associated with an increased postpartum hemorrhage risk. CONCLUSION: Serotonin-norepinephrine reuptake inhibitor exposure in late pregnancy was associated with a 1.6- to 1.9-fold increased risk of postpartum hemorrhage.
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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 | 0.000 | 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 | 0.001 |
| 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".