Predictive Model Construction And Prevention Strategies Of Surgical Site Infection In Laparoscopic Appendectomy.

Objective:To construct a nomogram model for predicting the occurrence of the laparoscopic appendectomy surgical site infection (LASSI) and explore prevention strategies. Methods:A total of 995 patients who underwent laparoscopic appendectomy in Shanxi Bethune Hospital from October 2017 to August 2022 were selected. According to whether there was incision infection within 30 days after operation, the patients were divided into the LASSI (97 cases) and non-LASSI (898 cases) group. The following clinicopathological data from these two groups of patients were collected: gender, age, body mass index, ect. The subjects were randomly divided into training group and verification group according to the 7:3 ratio. Univariate and multivariate analysis was used to screen the related influencing factors and construct a nomogram model to predict the occurrence of LASSI. Rreceiver operating characteristic (ROC) curves and the calibration curve were used to evaluate the predictive value of the model. For patients with LASSI, a more effective preventive measure was explored. Results:Multivariate logistic regression analysis showed that operation time >1h (OR: 1.891; 95% CI: 1.07 to 3.36; P = .029), perforated and gangrenous appendix (OR: 4.078; 95% CI: 1.84 to 9.86; P = .001), free intraperitoneal fluid (OR: 2.836; 95% CI: 1.57 to 5.35; P = .001), BMI>30 kg/m2 (OR: 2.828; 95% CI:1.54 to 5.12; P = .001), diabetes mellitus (DM) (OR: 2.795; 95% CI: 1.54 to 5.28; P = .001) were the independent prognostic factors of LASSI. The prediction nomogram model showed satisfactory performance in predicting the occurrence of LASSI, ROC curve area value of the training and verification groups were respectively 0.753 (95 % CI: 0.688 ~ 0.818) and 0.772 (95 % CI: 0.691-0.852). In the event of LASSI, we took out appendix specimens in sections and sterilized surgical site, which effectively prevented it. Conclusion:This study evaluated the risk factors related to the occurrence of LASSI and established a prediction model for LASSI. The prediction model provides a convenient and fast risk assessment tool for clinicians to predict the occurrence of LASSI. Combined with the newly discovered prevention strategy of segmental removal of appendix and incision disinfection, it can effectively avoid the occurrence of LASSI and potentially reduce the hospitalization time and costs.