Antidepressant use during pregnancy and gestational diabetes: a systematic review
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
A high number of women are exposed to antidepressants during pregnancy. Considering that an association between exposure to antidepressants and type 2 diabetes was found in the general population and pregnant women are inherently susceptible to insulin resistance, this study aimed to investigate data in the scientific literature on the association between antidepressant use during pregnancy and the risk of developing gestational diabetes mellitus (GDM). This systematic review was conducted according to the PRISMA guidelines. PubMed, Virtual Health Library (VHS), and Web of Science databases were searched to identify observational studies reporting the association between antidepressant use during pregnancy and GDM. Review articles, case reports, case series, clinical trials, and animal studies were excluded. In total, 67 studies were retrieved, of which 3 were included in the systematic review: one case-control and two cohort studies. According to the Newcastle-Ottawa Scale, the three studies were considered high-quality. Through this systematic review, selective serotonin reuptake inhibitors (SSRI) use during pregnancy is not significantly associated with a higher risk of developing GDM. There are still controversies about the association between serotonin and norepinephrine reuptake inhibitors (SNRI) and GDM. The use of tricyclic, tetracyclic, and atypical antidepressants by pregnant women appears to be associated with GDM. Therefore, the available information about the topic is scarce and the condition of further studies is needed.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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