Bibliographic record
Abstract
PURPOSE OF REVIEW: The management of depression in pregnancy is complex, as it is based on balancing the risks with the benefits of treatment versus no treatment for both the mother and the fetus. The current literature in the field of reproductive psychiatry is difficult to navigate and at times contradictory. This article aims to review both nonpharmacological and pharmacological modalities in the treatment of perinatal depression. A literature review using PubMed and MEDLINE databases was used to collect literature from the past 2 years; however, given the relatively small amount of research in reproductive psychiatry, several salient articles from the past 5 years have also been included in this review. RECENT FINDINGS: Recent US Food and Drug Administration and Health Canada warnings regarding poor neonatal adaptation and adverse perinatal outcomes associated with antidepressant use in pregnancy have changed patterns of practice for prescribing physicians. Many physicians are now left with a sense of indecisiveness regarding the safety of treating their depressed, pregnant patients. Similarly, these warnings have changed patients' attitudes and their willingness to consider pharmacological treatment for depression. Although these warnings demand attention and careful consideration, research has also shown that exposure to mental illness in pregnancy has deleterious short-term and long-term effects for the exposed mother and fetus. SUMMARY: The field of reproductive psychiatry is rapidly evolving. Clinicians need to keep abreast of changes in the management of depression during pregnancy. Ongoing research in this field is important so that the most up-to-date recommendations may be provided to pregnant women.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.004 | 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".