Outcomes of infants exposed to multiple antidepressants during pregnancy: results of a cohort study.
Bibliographic record
Abstract
BACKGROUND: A single study has been published documenting an increased risk for adverse pregnancy outcomes following use of more than one antidepressant during pregnancy. OBJECTIVE: To examine whether multiple antidepressant use is associated with increased rates of major malformations, spontaneous abortions (SA), therapeutic abortions (TA), stillbirths, preterm birth, low birth weight, small for gestational age (SGA) and admission to the neonatal intensive care unit (NICU). METHODS: Information from the Motherisk Program's prospectively collected database of 1243 women with gestational exposure to antidepressants. We compared pregnancy outcomes of 89 women exposed to >1 antidepressants, 89 taking one antidepressant, and 89 women not exposed to antidepressants (n= 267). Women were matched for maternal age, smoking and alcohol use. Groups were compared using odds ratios and ANOVA. RESULTS: 11/89 (12%) took 3 and 78 (88%) took 2 antidepressants. There were no statistically significant differences in any of the outcomes analyzed among the 3 groups except for a lower mean gestational age at birth in the multi-antidepressant group (0.9 week, P=0.036). There were 9 admissions to NICU from the antidepressant groups and 3 from the non-exposed group; but this did not reach statistical significance. CONCLUSIONS: There is a small risk of preterm delivery that is associated with exposure to antidepressant therapy, although the clinical relevance remains to be determined.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".