Antidepressant Use During Pregnancy: A Critical Systematic Review of the Literature
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
Over the past 15 years, the number of studies investigating the potential teratogenic effects of antidepressants has drastically increased. Prescribing antidepressants during pregnancy is becoming a challenge for health care providers because of conflicting data on their teratogenic potential. A critical systematic review of studies describing the relationship between antidepressant use during pregnancy and its impact on congenital malformations, prematurity, low birth weight (LBW), and child development was undertaken to summarize the current evidence-based findings. Most antidepressants do not pose a major teratogenic risk, although the data supporting this conclusion vary from one type to another. While SSRIs and tricyclics have been examined in a considerable number of studies, only scarce data is available on new antidepressants. The use of paroxetine during organogenesis has been linked to an increase in the risk of cardiovascular malformations. The impact of prenatal exposure to antidepressants on prematurity and LBW remains controversial, and most studies evaluating these outcomes are limited by their small sample size and lack of adequate reference group. Finally, information on the long-term effects of gestational antidepressant use on child development is only starting to emerge, and existing information is too limited to determine the risk.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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