Nomogram model of predicting postoperative surgical wound infection in patients with abdominal surgery

Abstract

Objective To explore the risk factors for abdominal surgical wound infection, and to establish a nomogram model for the prediction of the risk factors. Methods A total of 2 931 patients underwent abdominal surgery were enrolled in this study from June 2014 to June 2017. The clinical data were collected. The univariate and multivariate logistic regression were used to analyse the risk factors for abdominal surgical wound infection. A predictive nomogram model was established using the R software. Bootstrap method was used to validate the nomogram model and ROC curve was used to explore the predictive efficacy of the model in predicting the abdominal surgical wound infection. Results Of 2 931 enrolled patients, 84 of them had surgical wound infection and the infection rate was 2.87%. A total of 84 pathogens were detected, which approximately 59.52% of them were gram-negative bacteria. The multivariable logistic regression showed that age, malnutrition, diabetes mellitus, emergency operation, and unsuccessful rehabilitation education were independent risk factors for abdominal surgical wound infection (OR=4.196, 2.559, 2.949, 3.326, 1.198; P<0.05) . The nomogram model showed a C-index of 0.726 with good discrimination and accuracy. The ROC curve showed that the area under the curve (AUC) for the nomogram model was 0.735 (95%CI: 0.672-0.827) . Conclusions The established nomogram model has good discrimination and accuracy for predicting abdominal surgical wound infection. It is helpful for distinguishing high-risk populations and improving intervention strategies in clinical practice. Key words: Abdomen; Surgery; Surgical wound infection; Nomogram