Analysis of risk factors for postoperative infection in patients with jaw cysts and construction and validation of nomogram prediction model
Objective:To explore the risk factors for postoperative infection in patients with jaw cysts,and to con-struct and validate a nomogram prediction model.Methods:The clinical data of 257 patients with jaw cysts who visited our hospital from May 2020 to January 2024 were reviewed.According to the infection status,the patients were grouped into an infected group of 54 cases and an uninfected group of 203 cases.Multivariate Logistic regres-sion analysis was applied to screen for independent risk factors.R software was applied to construct a nomogram prediction model for postoperative infection in patients with jaw cysts.Hosmer-Lemeshow test was applied to test the model fit,the calibration curve was used to test the model calibration,and the receiver operating characteristic(ROC)curve was used to test the model discrimination.Results:92 strains of pathogenic bacteria were isolated from 54 patients with postoperative infections,including 41 strains of gram-negative bacteria(44.57％),48 strains of gram-positive bacteria(52.17％),and 3 strains of fungi(3.26％).There were significant differences between the uninfected group and the infected group in diabetes,operation time,intraoperative bleeding,non sterile opera-tion,postoperative white blood cell count(WBC),and postoperative procallcitonin(PCT)(P＜0.05).Diabetes,long operation time,large amount of intraoperative blood loss,non sterile operation,and high postoperative WBC were independent risk factors for postoperative infection in patients with jaw cysts(P＜0.05).The Hosmer-Leme-shau test results of the nomogram prediction model showedx2=5.745 and P=0.146,the model had a high degree of fit.The calibration curve results showed that the predicted infection probability of the model was basically con-sistent with the actual infection probability,indicating a high degree of model calibration.ROC curve results showed that the model had an AUC of 0.915(95％CI:0.868-0.962),indicating high model discrimination.When the probability range of the high-risk threshold was 0.04-0.98,the nomogram prediction model had a high clinical net benefit.Conclusion:The nomogram prediction model based on the risk factors,including diabetes,operation time,intraoperative blood loss,non sterile operation,and postoperative WBC,has a high prediction efficiency,and a high degree of differentiation and calibration.
jaw cystpostoperative infectionrisk factorsnomogram prediction model
万方数据
维普
