Development and validation of risk prediction score for incisional surgical site infection after appendectomy

Surgical site infection (SSI) is a challenging and resource-consuming healthcare problem. Predicting the onset of SSI beforehand can help prevent or minimize its incidence. The present study aimed to determine the independent predictors of incisional SSI after open appendectomy using a multivariate analysis and to establish a predictive risk score of SSI after appendectomy. Records of eligible patients who underwent open appendectomy were reviewed. The characteristics and treatment outcomes of patients were collected and analyzed. Significant association between different variables and SSI after appendectomy was examined by univariate analysis. Then, variables with a significant association with SSI were entered into a multivariate binary logistic regression analysis to determine the significant independent predictors of SSI. The study included 343 patients (51.3% female). Incisional SSI was recorded in 44 (12.8%) patients. Univariate analysis revealed five parameters with a significant association with SSI, including BMI > 30 kg/m2 (p < 0.0001), diabetes mellitus (DM) (p = 0.0001), total leukocyte count (p = 0.04), free intraperitoneal fluid (p < 0.0001), and perforated/gangrenous appendicitis (p < 0.0001). After identifying four significant independent predictors of incisional SSI by binary logistic regression analysis, a predictive risk score was developed. The independent predictors of SSI were DM (OR = 6.05, p = 0.005), free intraperitoneal fluid (OR = 6.94, p = 0.0001), obesity (OR = 8.94, p = 0.0001), and perforated/gangrenous appendicitis (OR = 24.64, p = 0.0001). Four independent predictors of incisional SSI after open appendectomy were found after multivariate analysis. A predictive risk score of SSI was developed and included obesity, DM, free intraperitoneal fluid, and perforated/gangrenous appendicitis as predictors of SSI.