摘要
Abstract
Objective Postoperative infection(PI)is one of the serious complications that may arise following lower limb fracture surgery.Perioperative glycemic variability(GV)is closely associated with the risk of PI.This study aims to construct and validate a PI risk prediction model based on periopera-tive glycemic variability,with the goal of providing a more scientific tool for PI risk assessment in clinical practice,optimizing perioperative management strategies,reducing infection rates,and improving patient outcomes.Methods Clinical data from 198 diabetic patients with lower limb fractures who underwent surgical treatment at Hainan Hospital Affiliated to Hainan Medical University(Hainan Provincial People's Hospital)between January 2022 and December 2023 were collected.Based on the presence or absence of postoperative infection,patients were divided into an infection group(148 cases)and a non-infection group(50 cases).Multivariate logistic regression analysis was performed to identify factors associated with postoperative infection.A nomogram model was constructed,and the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,decision curve analysis(DCA),and clinical im-pact curve(CIC)were used to evaluate the model's stability and validity.Results There were statisti-cally significant differences in multiple baseline indicators between the two groups(P<0.05),suggesting obvious heterogeneity in their clinical characteristics.Multivariate logistic regression analysis revealed that gender,diabetes duration,preoperative hemoglobin,postoperative ESR,postoperative day 2 fasting blood glucose,and standard deviation of blood glucose(SDBG)from preoperative to postoperative day 3 were inde-pendent risk factors for PI in diabetic patients with lower limb fractures(P<0.05).ROC analysis showed that the area under the curve(AUC)for the training group was0.842(95%CI:0.773～0.910),and the AUC for the validation group was 0.852(95%CI:0.737～0.967).The Hosmer-Lemeshow goodness-of-fit test P-values for the training and validation group was 0.119 and 0.111,respectively.Conclusion Perioperative GV significantly increases the risk of PI in diabetic patients with lower limb fractures and can serve as an important indicator for preoperative evaluation and perioperative management.This model aids in the individual-ized prediction of PI occurrence in diabetic patients with lower limb fractures and assists clinicians in adopting personalized treatment strategies.关键词
下肢骨折/糖尿病/术后感染/预测模型/列线图Key words
lower limb fractures/diabetes/postoperative infection/predictive model/nomogram
