Surgical site infection following abdominal surgery: a prospective cohort study
Bibliographic record
Abstract
Background: Surgical site infection (SSI) is one of the most common complications of abdominal surgery and is associated with substantial discomfort, morbidity and cost. The goal of this study was to describe the incidence, bacteriology and risk factors associated with SSI in patients undergoing abdominal surgery. Methods: In this prospective cohort study, all patients aged 14 years or more undergoing abdominal surgery between Feb. 1 and July 31, 2016, at a single large academic hospital were included. Patients undergoing vascular, gynecological, urological or plastic procedures were excluded. Patients were followed prospectively for 30 days. Wound assessment was done with the Centers for Disease Control and Prevention definition of SSI. We performed multivariate analysis to identify factors associated with SSI. Results: A total of 337 patients were included. The overall incidence of SSI was 16.3% (55/337); 5 patients (9%) had deep infections, and 25 (45%) had combined superficial and deep infections. The incidence of SSI in open versus laparoscopic operations was 35% versus 4% (p < 0.001). The bacteria most commonly isolated were extended-spectrum β-lactamase-producing Escherichia coli, followed by Enterococcus species. Only 23% of cultured bacteria were sensitive to the prophylactic antibiotic given preoperatively. The independent predictors of SSI were open surgical approach, emergency operation, longed operation duration and male sex. Conclusion: Potentially modifiable independent risk factors for SSI after abdominal surgery including open surgical approach, contaminated wound class and emergency surgery should be addressed systematically. We recommend tailoring the antibiotic prophylactic regimen to target the commonly isolated organisms in patients at higher risk for SSI.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".