The relationship between delivery mode and postpartum depression: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background: To assess the relationship between delivery mode and postpartum depression and to examine whether cesarean section (CS) has a higher risk of postpartum depression than vaginal delivery (VD). Methods: We searched the Cochrane Library, PubMed, and EMBASE from inception to 30 April 2019 without language limitations. Two authors independently selected studies, assessed the quality of included studies, and extracted data. Any disagreements were resolved by discussion with a third author. We used the Newcastle-Ottawa Scale and GRADE methods to assess the quality of the included studies and evidences. This study had four included cohort studies data and carried out fixed-effect model meta-analysis. Results: The findings demonstrated a significant difference in the risk of postpartum depression between CS and VD. Compared with the control group, the CS group was associated with a higher prevalence of postpartum depression symptoms (Risk Ratio =1.29; 95% CI: 1.11-1.51). Conclusions: The findings supported a relationship between delivery mode and postpartum depression. Particularly, we found that CS is associated with a higher risk of postpartum depression. Therefore, we ought to encourage pregnant women who are without medical indication of CS to select VD.r Trial registration: The protocol of this systematic review was registered in the PROSPERO under the number CRD42019148154.
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.022 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".