Prevalence and root causes of surgical site infection among women undergoing caesarean section in Ethiopia: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Surgical site infection is a common complication in women undergoing Caesarean section and the second most common cause of maternal mortality in obstetrics. In Ethiopia, prevalence and root causes of surgical site infection post-Caesarean section are highly variable. This systematic review and meta-analysis estimate the overall prevalence of surgical site infection and its root causes among women undergoing Caesarean section in Ethiopia. METHOD: Systematic review and meta-analysis were conducted to assess the prevalence and root causes of surgical site infection in Ethiopia. The articles were searched from the databases such as Medline, Google Scholar and Science Direct. A total of 13 studies from different regions of Ethiopia reporting the prevalence and root causes of surgical site infection among women undergoing Caesarean section were included. A random effect meta-analysis model was computed to estimate the overall prevalence. In addition, the association between risk factor variables and surgical site infection related to Caesarean section were examined. RESULTS: Thirteen studies in Ethiopia showed that the overall prevalence of surgical site infection among women undergoing Caesarean section was 8.81% (95% CI: 6.34-11.28). Prolonged labor, prolonged rupture of membrane, presence of anemia, presence of chorioamnionitis, presence of meconium, vertical skin incision, greater than 2 cm thickness of subcutaneous tissue, and general anesthesia were significantly associated with surgical site infection post-Caesarean section. CONCLUSION: Prevalence of surgical site infection among women undergoing Caesarean section was relatively higher in Ethiopians compared with the report of center of disease control guideline. Prolonged labor, prolonged rupture of membrane, presence of anemia, chorioamnionitis, presence of meconium, vertical skin incision, greater than 2 cm thickness of subcutaneous tissue and/or general anesthesia were significantly associated with surgical site infection post-Caesarean section.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.026 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".