Incidence and Risk Factors for Surgical Site Infection following Emergency Cesarean Section: A Retrospective Case-Control Study
Bibliographic record
Abstract
OBJECTIVE: To assess the incidence, risk, and associated factors that contribute to an acquired surgical site infection (SSI) after emergency cesarean section (CS). METHODS: This retrospective case-control study was conducted in an acute district general hospital in England with 206 patients (101 SSI patients and 105 non-SSI patients) who had an emergency CS in 2017. Grade of surgeon, smoking status, preoperative vaginal swab status (positive or negative), diabetes status, age, body mass index, membrane rupture to delivery interval, and length of surgery were recorded. Risk factors were identified using simple and multiple logistic regression. RESULTS: Body mass index was significantly associated with SSI (odds ratio, 1.17; 95% confidence interval, 1.11 to 1.24; P < .001). Further, substantive nonsignificant associations were recorded between SSI and patient age and vaginal swab status. CONCLUSIONS: Body mass index was the only significant risk factor for the development of an SSI after emergency CS, possibly because of the impact of excessive adipose tissue on the immune system and reduced effectiveness of antibiotics. Diabetes status, patient age, and preoperative vaginal swab status were not significantly associated with SSI. Improved guidelines and strategies for managing at-risk patients would enable clinicians to reduce the risk of SSI development. The importance of wound management including frequent wound cleaning, appropriate dressings, dressing changes, and education is highlighted. Future research on larger samples should be conducted to validate these findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".