Do findings differ across research design? The case of antidepressant use in pregnancy and malformations.
Bibliographic record
Abstract
BACKGROUND: Many studies examining the teratogenic potential of antidepressants have been published. A variety of observational designs have been used with apparent conflicting results, although odds ratios were rarely >2. OBJECTIVES: To examine whether these apparent differences were associated with research methods such as model, comparison groups, data source, data collection procedures, definition of malformations, outcome ascertainment or management of confounders. METHODS: Medline and Embase were searched using terms: pregnancy, antidepressants, serotonin uptake inhibitors OR SSRI, AND embryonic structures OR congenital malformations OR fetal development for observational studies with original data. Data were analyzed using a structured approach and narrative review. Designs that were compared, included prospective cohort, retrospective cohort, and case-control studies. Rates of major malformations and cardiac malformations were combined by study type using random effects meta-analytic models. RESULTS: We identified 150 papers; 127 were rejected, 23 were analyzed: 9 prospective cohort, 8 retrospective cohort, and 6 case-control studies. Sample sizes were large (1,818 exposed in case-control and 16,824 in cohort studies), providing relatively robust findings. Overall Odds Ratios for major malformations ranged from 1.03-1.24 and 0.81-1.32 for cardiac malformations. No discrepancies among research designs were identified. CONCLUSIONS: Diverse observational models with differing strengths and weaknesses produced remarkably similar non-significant results. Perceived conflicting results may be due to subsequent dissemination of results with attention given to small statistically differences with negligible clinical importance. Improved methods of knowledge transfer and translation are required to provide sound evidence-based information to assist in decision-making surrounding the use of antidepressants in 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 | 0.477 | 0.734 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".