Previous Cesarean Section and the Risk of Preeclampsia: A Meta-analysis
Bibliographic record
Abstract
Introduction: Preeclampsia is a common pregnancy complication with the multisystem variable disorder. Yet, the literature has not been systematically reviewed for the relationship between previous cesarean section and the risk of preeclampsia. Objective: This study aimed to identify the relationship between previous cesarean delivery and the risk of preeclampsia. Materials and Methods: This study was a systematic review and meta-analysis. PubMed, Scopus, ProQuest, and Web of Sciences were searched to identify eligible observational studies until May 25, 2019. The odds ratio (OR) and 95% confidence intervals (CI) were calculated as random effect estimates of association among studies. The quality of the included studies was examined based on the Newcastle-Ottawa scale. Results: This study included 7 eligible articles (2 studies with a case-control design, 4 with a cohort design, and 1 with a cross-sectional design). The meta-analysis results showed an increased risk of preeclampsia in the women with previous cesarean section compared to women without cesarean section (OR=1.28, 95% CI, 1.15%-1.41%, P=0.001), I2=37.2%. The quality of all studies except one study was high based on the Newcastle-Ottawa scale. The subgroup analysis was conducted based on the adjusted form of studies. The crude and adjusted studies were 1.29 (95% CI, 0.13%-2.46%, P=0.2) and 1.29 (95% CI, 1.22%-1.36%, P=0.001), respectively. Conclusion: These findings showed that previous cesarean section is a risk factor for preeclampsia. Therefore, education programs and interventions should be considered to reduce elective cesarean section on maternal requests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".