Preoperative Emergency Surgery Score for Predicting Surgical Site Infection After Emergency Gastrointestinal Surgery
DOI:
https://doi.org/10.65761/pjcr.2026.3.1.33Keywords:
Surgical Site Infection, Gastrointestinal Diseases / surgery, Emergencies, Severity of Illness Index, Risk Assessment / methods, Prospective Studies.Abstract
Background: Surgical site infections (SSIs) are a major cause of postoperative morbidity following emergency gastrointestinal (GI) surgery. Although the Emergency Surgery Score (ESS) is validated for mortality prediction, its ability to predict infectious complications remains underexplored.
Objectives: To evaluate the predictive value of the Emergency Surgery Score (ESS) for 30-day postoperative surgical site infections after emergency GI surgery.
Methods: This prospective cohort study was conducted at tertiary care hospital between June 2023 and June 2025 and included 58 adults undergoing emergency GI surgery for perforation, obstruction, inflammation, or ischemia. Preoperative ESS was calculated for all patients. Individuals with early mortality, extra-gastrointestinal infections, or immunocompromised status were excluded. The primary outcome was 30-day SSI. Logistic regression and Receiver Operating Characteristic (ROC) curve analyses assessed ESS performance.
Results: The median age was 29 years, and 67.2% were male. Overall SSI incidence was 25.9% (15/58). SSI rates increased significantly across ESS categories: 10.0% (ESS 0), 22.2% (ESS 1-3), and 66.7% (ESS 4-29) (p = 0.018). ESS 4-29 (OR 22.1, 95% CI 1.18-412.3; p = 0.031) and open surgery (OR 21.8, 95% CI 3.52-134.7; p < 0.001) were independent predictors of SSI. ROC analysis showed moderate discrimination (AUC 0.712, p = 0.009). An ESS cutoff ≥3 achieved 91.0% specificity and 50.0% sensitivity. Each one-point increase in ESS increased SSI odds by 41%.
Conclusion: ESS is a practical preoperative tool with high specificity for identifying patients at increased risk of SSI following emergency GI surgery, supporting targeted infection prevention in resource-limited settings.
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