A Retrospective Cohort Study on Postoperative Surgical Site Infections Following Open Appendectomy: Predictive Factors and Development and Validation of a Risk Prediction Model

TL;DR

This study identifies risk factors for surgical site infections after open appendectomy and creates a risk prediction model to help prevent infections in resource-limited settings.

Contribution

A new risk prediction model for surgical site infections after open appendectomy, validated with strong discrimination and stratification into risk groups.

Findings

The overall surgical site infection rate was 13.9%.

Perforated appendicitis and longer operative time were significant risk factors.

The model showed good discrimination (AUC = 0.82) and stratified patients into low, moderate, and high-risk groups.

Abstract

Background

Surgical site infections (SSIs) are a common complication after open appendectomy, increasing postoperative morbidity and healthcare costs. While laparoscopic appendectomy is standard in high-resource settings, open appendectomy remains prevalent in many resource-limited environments. The lack of validated risk stratification tools hinders targeted prevention and antimicrobial stewardship. This study aimed to determine SSI prevalence, identify independent risk factors, and develop a practical risk prediction model for patients undergoing open appendectomy.

Patients and methods

We conducted a retrospective cross-sectional study of 245 consecutive open appendectomy cases at hospitals affiliated with Ibb University from March 2024 to April 2025. SSIs were defined per CDC criteria and monitored during 30-day postoperative surveillance. SSI prevalence was calculated, and multivariable logistic regression identified demographic, clinical, and operative predictors. Model discrimination was assessed using receiver operating characteristic (ROC) curve analysis and calibration with the Hosmer-Lemeshow test. A risk scoring system was derived from standardized β-coefficients and internally validated with 1,000 bootstrap resamples.

Results

The overall SSI rate was 13.9% (n = 34). Independent predictors included perforated appendicitis (adjusted odds ratio (aOR) = 5.8; 95% confidence interval (CI): 2.6-12.9), symptom duration >48 hours (aOR = 3.9; 95% CI: 1.4-8.9), American Society of Anesthesiologists (ASA) class ≥ III (aOR = 3.1; 95% CI: 1.3-7.4), and operative time >60 minutes (aOR = 2.7; 95% CI: 1.2-6.1). The model showed excellent discrimination (area under the ROC curve (AUC) = 0.82; 95% CI: 0.76-0.88) and good calibration (Hosmer-Lemeshow p = 0.42), explaining 48% of SSI variance. Patients were stratified into low (0-1 points; SSI probability: 3.2%), moderate (2-3 points; 18.7%), and high-risk groups (4-5 points; 52.4%). The high-risk group had a 22.1-fold increased SSI likelihood (positive likelihood ratio = 22.1) and an 82% post-test probability.

Conclusions

This validated risk prediction model, based on four routinely available clinical variables, effectively stratifies SSI risk following open appendectomy. Its strong discrimination and ease of use make it valuable in resource-constrained settings where open appendectomy predominates. External validation in larger, multicenter cohorts is warranted. Future research should evaluate the model’s impact on clinical decision-making and infection prevention.

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