Pregnancy Outcomes Following In Utero Exposure to Second-Generation Antipsychotics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Second-generation antipsychotics (SGAs) are increasingly used for a variety of mental illnesses; however, the data regarding the safety of these medications during pregnancy are inconclusive and contradictory. We examined the risk of adverse pregnancy outcomes associated with in utero exposure to SGAs by conducting a systematic review and meta-analysis. We searched the databases EMBASE and MEDLINE from January 1990 to December 2014. Eligible studies had to report pregnant women who took SGAs during pregnancy (first trimester exposure if analyzing congenital malformations), follow a healthy comparison group in a similar manner, and report data on pregnancy outcomes. There was no restriction on language, sample size, or publication date. The primary outcome analyzed was major congenital malformations, and secondary outcomes included miscarriages, stillbirths, preterm births, small or large for gestational age neonates, and differences in gestational ages and birth weights. A total of 12 studies met our inclusion criteria, totalling 1782 cases and 1,322,749 controls. The use of SGA during the first trimester of pregnancy was associated with a significant increased risk for major congenital malformations (odds ratio, 2.03; 95% confidence interval, 1.41-2.93); however, no specific pattern of malformations was found. An increased risk was also found for preterm births (odds ratio, 1.85; 95% CI, 1.20-2.86). The use of SGA during pregnancy was not found to be associated with an increased risk for secondary outcomes analyzed. The absence of a specific pattern of malformations makes it difficult to identify an explicit risk posed by SGAs, and therefore, further studies sufficiently controlling for confounding factors are needed to validate these findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it