The risk of major cardiac malformations associated with paroxetine use during the first trimester of pregnancy: a systematic review and meta‐analysis
Bibliographic record
Abstract
AIMS: The aim of this study was to perform an up-to-date meta-analysis on the risk of cardiac malformations associated with gestational exposure to paroxetine, taking into account indication, study design and reference category. METHOD: A systematic review of studies published between 1966 and November 2015 was conducted using embase and MEDLINE. Studies reporting major malformations with first trimester exposure to paroxetine were included. Potentially relevant articles were assessed and relevant data extracted to calculate risk estimates. Outcomes included any major malformations and major cardiac malformations. Pooled odds ratios and 95% confidence intervals were calculated using random-effects models. RESULTS: Twenty-three studies were included. Compared with non-exposure to paroxetine, first trimester use of paroxetine was associated with an increased risk of any major congenital malformations combined (pooled OR 1.23, 95% CI 1.10, 1.38; n = 15 studies), major cardiac malformations (pooled OR 1.28, 95% CI 1.11, 1.47; n = 18 studies), specifically bulbus cordis anomalies and anomalies of cardiac septal closure (pooled OR 1.42, 95% CI 1.07, 1.89; n = 8 studies), atrial septal defects (pooled OR 2.38, 95% CI 1.14, 4.97; n = 4 studies) and right ventricular outflow track defect (pooled OR 2.29, 95% CI 1.06, 4.93; n = 4 studies). Although the estimates varied depending on the comparator group, study design and malformation detection period, a trend towards increased risk was observed. CONCLUSIONS: Paroxetine use during the first trimester of pregnancy is associated with an increased risk of any major congenital malformations and cardiac malformations. The increase in risk is not dependent on the study method or population.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.040 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".