Prevalence and correlates of postpartum PTSD following emergency cesarean sections: implications for perinatal mental health care: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The increasing awareness of the emotional consequences of emergency cesarean deliveries (C-sections) highlights their substantial role in fostering postpartum post-traumatic stress disorder (PTSD). This systematic review and meta-analysis aim to evaluate the prevalence and determinants of PTSD following emergency C-sections, as well as the implications of these events on maternal mental health and welfare. METHODS: Undertaking extensive searches of Scopus, PubMed, PsycINFO, and Google Scholar, we have incorporated studies published from 2013 onwards that examined the occurrence of PTSD following emergency C-sections. Our primary focus was on the prevalence of PTSD at 6 weeks and up to 12 months postpartum. To evaluate the quality of these studies, we employed the Newcastle-Ottawa Scale (NOS) and the CEBM Critical Appraisal Tools. FINDINGS: We included a total of 10 studies with 4,995 participants. The prevalence of PTSD following emergency C-sections ranged from 2.2 to 41.2%, compared to 0-20% in elective cesarean sections. A meta-analysis revealed a significant rise in the number of people with PTSD in the emergency C-section group compared to the elective C-section group six weeks after giving birth (OR = 2.74; 95% CI = 1.13 to 6.64; p = 0.03) and six weeks to 12 months later (OR = 3.68; 95% CI = 2.63 to 5.15; p < 0.00001). The emergency C-section group also had a higher PTSD prevalence compared to vaginal birth six weeks to 12 months after birth (OR 3.16; 95% CI 1.51 to 6.60; p = 0.02). Risk factors included poor social support, maternal and neonatal complications, and prior psychiatric history. CONCLUSIONS: Emergency C-sections are significantly associated with an increased risk of postpartum PTSD, necessitating targeted psychological support and interventions. Future research should aim for standardized diagnostic criteria and explore the long-term psychological outcomes of emergency C-sections.
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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 | 0.017 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.036 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".