Reproductive Safety of Second-Generation Antipsychotics
Bibliographic record
Abstract
Second-generation antipsychotics (SGAs) are prescribed for a wide range of indications in women of reproductive age. The National Pregnancy Registry for Atypical Antipsychotics (NPRAA) was established to determine the risk of major malformations among infants exposed to these medications during the first trimester relative to a comparison group of unexposed infants of mothers with histories of psychiatric morbidity. Women, aged 18-45 years, with histories of psychiatric illness were prospectively followed through pregnancy and during the postpartum period. Pediatric and maternal medical records were obtained and screened for evidence of major malformations. Potential cases were adjudicated by a dysmorphologist who was blinded to drug exposure.. Recruitment to the Registry, which is based at the Ammon-Pinizzotto Center for Women's Mental Health at Massachusetts General Hospital (MGH), includes nationwide provider referral, self-referral, and advertisement through the MGH Center for Women's Mental Health website. As of April 9, 2020, 1,906 women had enrolled, including 889 in the exposure group and 1,017 controls. A total of 1,311 women completed the study and were eligible for inclusion in the analysis. Medical records were obtained for 81.3% of participants. Among 640 live births in the exposure group, 16 (2.50%) had confirmed major malformations reported, and among 704 live births in the control group, 14 (1.99%) had confirmed major malformations reported. The estimated odds ratio for major malformations comparing exposed and unexposed infants was 1.48 (95% CI, 0.625-3.517). Data from the Registry assessing SGAs as a class indicate that they are unlikely to have a major teratogenic effect. These findings provide pertinent information for women and their health care providers regarding decisions about atypical antipsychotic use during pregnancy. ClinicalTrails.gov identifier: NCT01246765.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".