The Impact of Maternal Depression During Pregnancy on Perinatal Outcomes
Bibliographic record
Abstract
OBJECTIVE: Depression often remains undertreated during pregnancy and there is growing evidence that untoward perinatal outcomes can result. Our systematic review and meta-analysis was conducted to determine whether maternal depression during pregnancy is associated with adverse perinatal and infant outcomes. DATA SOURCES: MEDLINE, EMBASE, CINAHL, and PsycINFO were searched from their start dates to June 2010. Keywords utilized included depressive/mood disorder, postpartum/postnatal, pregnancy/pregnancy trimesters, prenatal or antenatal, infant/neonatal outcomes, premature delivery, gestational age, birth weight, NICU, preeclampsia, breastfeeding, and Apgar. STUDY SELECTION: English language studies reporting on perinatal or child outcomes associated with maternal depression were included, 3,074 abstracts were reviewed, 735 articles retrieved, and 30 studies included. DATA EXTRACTION: Two independent reviewers extracted data and assessed article quality. All studies were included in the primary analyses, and between-group differences for subanalyses are also reported. RESULTS: Thirty studies were eligible for inclusion. Premature delivery and decrease in breastfeeding initiation were significantly associated with maternal depression (odds ratio [OR] = 1.37; 95% CI, 1.04 to 1.81; P = .024; and OR = 0.68; 95% CI, 0.61 to 0.76; P < .0001, respectively). While birth weight (mean difference = -19.53 g; 95% CI, -64.27 to 25.20; P = .392), low birth weight (OR = 1.21; 95% CI, 0.91 to 1.60; P = .195), neonatal intensive care unit admissions (OR = 1.43; 95% CI, 0.83 to 2.47; P = .195), and preeclampsia (OR = 1.35; 95% CI, 0.95 to 1.92; P = .089) did not show significant associations in the main analyses, some subanalyses were significant. Gestational age (mean difference = -0.19 weeks; 95% CI, -0.53 to 0.14; P = .262) and Apgar scores at 1 (mean difference = -0.05; 95% CI, -0.28 to 0.17; P = .638) and 5 minutes (mean difference = 0.01; 95% CI, -0.08 to 0.11; P = .782) did not demonstrate any significant associations with depression. For premature delivery, a convenience sample study design was associated with higher ORs (OR = 2.43; 95% CI, 1.47 to 4.01; P = .001). CONCLUSIONS: Maternal depression during pregnancy is associated with increased odds for premature delivery and decreased breastfeeding initiation; however, the effects are modest. More research of higher methodological quality is needed.
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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 | 0.014 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".