DEPRESSION AND ANTIDEPRESSANT USE IN PREGNANCY AND ADVERSE MATERNAL AND FETAL/CHILDREN OUTCOMES: A SYSTEMATIC REVIEW AND META-ANALYSIS
Bibliographic record
Abstract
Abstract Background Antidepressant use during pregnancy has been increasing in the last few decades. Many evidences have indicated the high risks of adverse health outcomes for both pregnant women and their offspring. Aims & Objectives The association may be biased by uncontrolled confounding of maternity depression or mental health status. We performed a systematic review and meta-analysis to generate precise estimates of the association between depression, antidepressants, and reproductive outcomes. Methods The PubMed and Embase were searched from database inception to Sep 23, 2022, for longitudinal cohort studies of pregnant women with exposure to antidepressants or depression, we assessed the risk of adverse maternal and children outcomes. The Newcastle-Ottawa Scale was used for assessing the methodological quality of included studies. Pooled estimates of risk ratio (RR) were conducted by random effects or fixed effects model by comparing adverse pregnant outcomes in women who took antidepressants versus those who did not, or in women with or without a depressive disorder. Further investigations were conducted to compare the effects of depression (pregnant women with untreated depression compared with control women without depression) and antidepressant use (only in women with depression) on 19 adverse pregnancy outcomes including six maternal and fetal outcomes during eight newborn and five childhood or adolescent period. And association were examined in subgroups stratified by different study designs and income levels. Results A total of 134 studies with 40,864,148 participants were included. Compared with pregnant women who did not take antidepressants, those who were exposed had a higher risk for the 16 majority of the focused adverse outcomes in our study, such as abortion (RR,1.33; 95%CI, 1.18-1.49), gestational diabetes (1.24, 1.13- 1.35), 5-minute Apgar score <7 (RR,2.07; 95%CI, 1.95-2.20), ASD (1.69, 1.58-1.80), ADHD (1.30, 1.15- 1.48), depression (2.61, 1.59-4.28), and anxiety (1.74, 1.16-2.61) etc. Compared with women without depression disorder, depressed pregnancy was also associated with increased risks of 8 adverse outcomes, such as low birth weight (LBW) (1.74, 1.24-2.43), preterm birth (1.53, 1.30-1.80), abortion (1.52, 1.45-1.60),. However, when comparing women exposed to antidepressants with those not exposed in the participants of depressed pregnancy, the risks of 2 adverse outcome including preterm birth (1.14, 1.12-1.17) and admission to NICU (1.44,1.33-1.56) were found to be significantly increased. Discussion & Conclusion The adverse outcome of antidepressant use manly come from perinatal depression, which was associated with adverse reproductive outcomes, but antidepressants use in depressed pregnancy did not cause more adverse events except for preterm birth and admission to NICU. Higher risks of most adverse outcomes of antidepressants are mainly associated by the onset of depression itself. More attention should be paid to depression, and health professionals should estimate the risk of depression and antidepressant comprehensively during counseling and prenatal health care.
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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".