Reproductive Safety of Lurasidone and Quetiapine: Update from the National Pregnancy Registry for Psychiatric Medications
Bibliographic record
Abstract
Background: Second-generation antipsychotics (SGAs), also called atypical antipsychotics, are common therapies for women with a spectrum of psychiatric disorders. No systematically ascertained human reproductive safety data are available for lurasidone, and prospective data for quetiapine are limited, making decisions regarding use of these medications during pregnancy complicated. Materials and Methods: The National Pregnancy Registry for Psychiatric Medications is a prospective cohort study designed to collect reproductive safety data relative to SGAs. Pregnant women aged 18–45 years, with psychiatric illness and prenatal psychotropic medication exposure completed three phone interviews during pregnancy and the postpartum period. Cases of presumed malformations are abstracted from medical records for adjudication by a teratologist blinded to medication exposure. Results: Of 2,293 women enrolled at the time of analysis, 134 in the lurasidone group, 264 in the quetiapine group, and 886 controls completed the postpartum interview and were therefore eligible for inclusion. Dropped or lost-to-follow-up participants (13%) and those currently pregnant were excluded. Participants were predominantly White, college-educated, and married (lurasidone = 88.1%, 76.9%, 77.6%; quetiapine = 89.8%, 71.2%, 75.0%; controls = 92.7%, 86.7%, 89.1%). Absolute risks of major malformations were 2.19% (lurasidone), 1.85% (quetiapine), and 1.77% (controls). Odds ratios comparing lurasidone and quetiapine with controls were 1.24 (95% confidence interval [CI] = 0.36–4.32) and 1.04 (95% CI = 0.38–2.85), respectively. Conclusions: No specific patterns of malformations were observed in infants exposed to the medications of interest. Lurasidone and quetiapine did not appear to be major teratogens, but further information is needed to refine risk estimates. Food and Drug Administration guidance underscores the importance of pregnancy registries. Clinical trial number: 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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".