Regional variations in incidence of surgical site infection and associated risk factors in women undergoing cesarean section: A systematic review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Surgical site infections (SSIs) are the most common postoperative complications after cesarean section (CS), with increased mortality, prolonged hospital stays, and increased healthcare costs. OBJECTIVE: To systematically estimate the global incidence and identify the risk factors associated with SSI, focusing on the variation between high- and low-income countries. SEARCH STRATEGY AND SELECTION CRITERIA: Observational studies reporting on the incidence of SSI after CS were systematically searched in PubMed, Embase and SCOPUS. DATA COLLECTION AND ANALYSIS: Multiple authors independently screened, extracted the data, and assessed therisk of bias. The primary outcome was the incidence of SSI within 30 days. Subgroup and sensitivity analyses and meta-regression examined SSI-related heterogeneity. MAIN RESULTS: 49 cohort studies with 271,954 participants met the inclusion criteria. We found with moderate certainty that the overall SSI incidence in CS patients was 7.0 % (95 % CI: 6.0 %-8.0 %). The SSI incidence in LMICs was 8.0 % (95 % CI: 6.0 %-10.0 %) with moderate certainty, while the incidence in HICs was 5.0 % (95 % CI: 4.0 %-7.0 %) with low certainty. Subgroup analysis indicated a significantly higher incidence in Africa and the Western Pacific. Meta-regression showed a significant decrease in SSI incidence in HICs. Maternal factors, procedural aspects, and care quality were associated with SSI. CONCLUSIONS: Our findings offer valuable insights into the global incidence of SSIs following CS and provide a reliable estimate for benchmarking and quality improvement. This study adds to the evidence on SSI determinants and highlights the need for targeted preventative measures across various regional and healthcare settings. IMPLICATIONS FOR CLINICAL PRACTICE: Higher SSI rates in LMICs call for targeted infection prevention strategies, including improved preoperative preparation, antibiotic prophylaxis, and enhanced antenatal care services. In HICs, addressing lifestyle factors, managing comorbidities, and refining surgical protocols can further mitigate risks, emphasizing the need for region-specific, evidence-based interventions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".