心脏植入式电子设备感染风险预测模型的系统评价  

Risk Prediction Models for Cardiac Implantable Electronic Device-related Infection:a Systematic Review

作　　者：张晓欣 张向毅 崔盈佳 裴志怡 林佳艺 岳雯静 王子涵 康晓凤[1] 祝捷[2] ZHANG Xiaoxin;ZHANG Xiangyi;CUI Yingjia;PEI Zhiyi;LIN Jiayi;YUE Wenjing;WANG Zihan;KANG Xiaofeng;ZHU Jie(School of Nursing,Peking Union Medical College,Chinese Academy of Medical Sciences,Beijing 100043,China;Cardiac Arrhythmia Center,National Center for Cardiovascular Diseases and Fuwai Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100037,China)

机构地区：[1]中国医学科学院北京协和医学院护理学院,北京100043 [2]中国医学科学院,北京协和医学院,国家心血管病中心,阜外医院心律失常中心,北京100037

出　　处：《中国循环杂志》2024年第4期370-377,共8页Chinese Circulation Journal

基　　金：北京协和医学院2022年中央高校教育教学改革专项资金支持项目(2022zlgc0112);2023年阜外医院护理部专项基金(HLZX2023003)。

摘　　要：目的:系统评价心脏植入式电子设备(CIED)植入术后设备感染(DRI)的风险预测模型。方法:通过计算机检索PubMed、Embase、Web of Science、Cochrane图书馆、CINAHL、中国生物医学文献数据库、中国知网、维普网、万方数据库中与CIED植入术后DRI风险预测模型相关的文献,检索时间为从建库至2023年12月2日。由2名研究者独立筛选文献、提取资料并完成纳入文献的偏倚风险与适用性评价。结果:共纳入16项研究,模型总体适用性较好,但偏倚风险较高,ROC曲线的AUC为0.67~0.96。11项研究完成了内部验证,5项研究进行了外部验证。囊袋和(或)电极重置/装置升级、肾功能不全或肾功能衰竭、年龄、植入埋藏式心脏复律除颤器或心脏再同步化治疗、使用抗凝药是DRI的预测因子。结论:目前CIED植入术后DRI风险预测模型整体性能较好,适用性较好,但偏倚风险较高。需在数据来源、变量筛选、模型评价等方面提高研究质量,开展前瞻性队列研究,完善现有模型的外部验证,并积极研发适用于我国人群的预测模型。Objectives:To systematically evaluate the risk prediction models of device-related infection(DRI)in cardiac implantable electronic device(CIED)patients after implantation,and to provide reference for clinical practice and future scientific research.Methods:A computer-based search was conducted from 2 December 2023 through PubMed,Embase,Web of Science,Cochrane Library,CINAHL,China Biology Medicine,China National Knowledge Infrastructure,Wanfang,and VIP database to identify literatures related to the risk prediction model of DRI in patients with CIED.Two researchers independently screened the literature,extracted data,and completed the risk of bias and applicability evaluation of the included literature.Results:A total of 16 studies were included.The overall applicability of the models was good,but the risk of bias was high,and the area under the curve(AUC)of the receiver operating characteristic(ROC)ranged from 0.67 to 0.96.Eleven studies completed internal validation,and five studies underwent external validation.Bag and or electrode reset/device upgrade,renal insufficiency or renal failure,age,implantable cardioverter-defibrillators(ICD)or cardiac resynchronization therapy(CRT),and use of anticoagulant medications were valid predictors of device infection in CIED patients.Conclusions:The overall performance of the DRI-related risk prediction models for CIED patients is good,with good applicability but high risk of bias.It is necessary to improve the quality of the study in terms of data sources,variable screening,and model evaluation,to conduct prospective cohort studies,to improve the external validation of the existing models,and to actively develop local prediction model tools applicable to Chinese population.

关 键 词：心脏植入式电子设备 设备感染 风险评估 预测模型 系统评价 

分 类 号：R54[医药卫生—心血管疾病]