广东医学2025，Vol.46Issue(11)：1722-1728,7.DOI:10.13820/j.cnki.gdyx.20250852
肾移植术后并发血流感染的因素分析及风险预警量化方案研究
Factors associated with postoperative bloodstream infections after kidney transplantation and the development of a quantitative risk prediction model
摘要
Abstract
Objective To analyze the risk factors associated with bloodstream infections(BSIs)after kidney transplantation,and to establish and validate a quantitative risk prediction model for postoperative BSI.Methods A to-tal of 248 patients who underwent kidney transplantation between December 2020 and December 2023 were retrospectively analyzed.Patients were followed up for six months and divided into BSI and non-BSI groups according to postoperative infection status.Candidate variables were initially screened using the least absolute shrinkage and selection operator(LASSO)regression model,and significant predictors were further analyzed using multivariate logistic regression to identi-fy independent factors associated with BSIs.Sensitivity analyses were performed to evaluate model robustness.A risk pre-diction model was constructed and assessed by receiver operating characteristic(ROC)curve analysis,calibration curve,and decision curve analysis(DCA)to evaluate discrimination,calibration,and clinical utility.Results Postoperative BSIs occurred in 26 of 248 patients(10.97％).LASSO regression identified three variables with non-zero coefficients:diabetes mellitus,serum albumin(ALB),and platelet count(PLT).Multivariate logistic regression showed that diabetes mellitus(OR=2.504,95％CI:1.307-4.794,P＜0.05)was an independent risk factor for postoperative BSIs,while ALB(OR=0.475,95％CI:0.310-0.726,P＜0.05)and PLT(OR=0.609,95％CI:0.398-0.932,P＜0.05)were protective factors.Sensitivity analyses confirmed the stability of the model.The established logistic regression equa-tion was:logit=-11.259+2.504x1-0.475x2-0.609x3.The model demonstrated excellent predictive performance,with an AUC of 0.925(95％CI:0.884-0.955,Z=18.379,P＜0.001),sensitivity of 96.15％,and specificity of 87.20％.The Hosmer-Lemeshow test indicated good calibration(x2=0.641,P=0.196),and DCA showed positive net clinical benefit within the risk threshold range of0.11-0.81.Conclusion Diabetes mellitus,serum albumin,and platelet count are independent factors influencing the occurrence of bloodstream infections after kidney transplantation.The established quantitative prediction model demonstrates high accuracy,good calibration,and strong clinical applicability,providing a valuable tool for early risk assessment and individualized prevention of BSIs in kidney transplant recipients.关键词
肾移植术/血流感染/列线图模型/预测Key words
kidney transplantation/bloodstream infection/nomogram model/risk prediction分类
医药卫生引用本文复制引用
崔勇,王雪颖,汤飞虎,张振涛,高远..肾移植术后并发血流感染的因素分析及风险预警量化方案研究[J].广东医学,2025,46(11):1722-1728,7.基金项目
潍坊市卫生健康委员会科研项目(WFWSJK-2022-191) （WFWSJK-2022-191）
