实体器官移植受者术后早期感染预测模型构建
Construction of a predictive models for early postoperative infection in solid organ transplant recipients
边沁 1谈锦艳 1陆雯静 1潘凡祺 1陈志强 1李奕 1黄怡2
作者信息
- 1. 海军军医大学第一附属医院疾病预防控制科,上海 200433
- 2. 海军军医大学第一附属医院呼吸与危重症医学科,上海 200433
- 折叠
摘要
目的 构建实体器官移植受者术后早期感染的预测模型.方法 回顾性分析海军军医大学第一附属医院2020年1月-2023年7月157例器官移植受者的临床及实验室资料,利用逐步回归模型构建实体器官移植患者早期感染的预测模型.结果 157例移植受者中,31例发生术后感染,感染率为19.75％;共检出病原菌57株,标本类型以痰为主(40.35％),检出病原菌以肠杆菌目、假单胞菌属、不动杆菌属和寡养单胞菌属为主;基于逐步回归结果构建感染预测模型:Logit(P)=-2.411+0.050×中心静脉插管时长+0.027×术后抗菌药物使用时长+0.064×导尿管使用时长-0.146X器官移植类型-0.398×高血压史;感染预测模型及Bootstrap内部验证的曲线下面积(AUC)为 0.762(95％CI:0.684～0.840)和 0.764(95％CI:0.686～0.843),当 cutoff 值为 0.209 时诊断灵敏度为83.33％、特异度为66.67％.结论 实体器官移植术后早期感染以肠杆菌目感染为主,多指标联合诊断提高了模型预测性能.
Abstract
OBJECTIVE To construct a predictive model for early postoperative infection in solid organ transplant recipients.METHOD The clinical and laboratory data of 157 organ transplant recipients at the First Affiliated Hos-pital of Naval Medical University from Jan.2020 to Jul.2023 were retrospectively analyzed,and a stepwise regres-sion model was used to construct a predictive model for early infection in solid organ transplant patients.RESULTS Among the 157 transplant recipients,31 cases developed postoperative infections,with an infection rate of 19.75％.A total of 57 strains of pathogenic bacteria were detected,with sputum being the main type of specimen(40.35％).The top three pathogenic bacteria detected were Enterobacteriaceae(24.56％),Pseudomonas(17.54％),Acinetobacter(15.79％),and Stenotrophomonas(15.79％),respectively.An infection prediction model was constructed based on stepwise regression.RESULTS Logit(P)=-2.411+0.050 X central venous cath-eterization duration+0.027 X postoperative antibiotic use duration+0.064 X catheter use duration-0.146 X organ transplantation type-0.398 X hypertension history.The area under the curve(AUC)of the infection prediction model and Bootstrap internal validation were 0.762(95％CI:0.684-0.840)and 0.764(95％CI:0.686-0.843),respectively.When the cutoff value was 0.209,the diagnostic sensitivity was 83.33％and the specificity was 66.67％.CONCLUSION Early postoperative infections after solid organ transplantation were mainly caused by Enterobacteriaceae infection,and the combination of multiple indicators improved the prediction performance of the model.
关键词
器官移植/早期感染/病原菌/列线图/预测模型/评价Key words
Organ transplantation/Early infection/Pathogen/Nomogram/Predictive models/Evaluation引用本文复制引用
基金项目
国家重点研发计划基金资助项目(2017YFC1309704)
出版年
2024
NETL
NSTL
万方数据