目的:越来越多的证据表明,来自侵入性冠状动脉造影照片(CA-FFR)和冠状动脉计算机断层扫描血管造影衍生的FFR(CT-FFR)的血流储备分数(FFR)是有希望的替代方案。然而,尚不清楚哪种方法具有更好的诊断性能.本系统综述和荟萃分析旨在比较两种方法的诊断性能。
方法:Cochrane图书馆,PubMed,Embase,Medline(Ovid),中国国家知识基础设施数据库(CNKI),VIP,和万方数据数据库搜索相关研究,包括CA-FFR和CT-FFR之间的比较,从他们各自的数据库开始,直到2023年1月1日。进行了非侵入性FFR(包括CA-FFR和CT-FFR)和侵入性FFR(作为参考标准)的研究,以诊断缺血性冠状动脉疾病,并将其设计为前瞻性,成对的诊断研究,被拉了。诊断测试准确性方法和用于网络荟萃分析(NMA)的贝叶斯分层汇总接收器工作特征(ROC)模型(HSROC-NMADT)均用于对数据进行荟萃分析。
结果:本NMA纳入了26项研究。诊断测试准确性和HSROC-NMADT方法的结果表明,CA-FFR的诊断准确性高于CT-FFR。在灵敏度方面(Se;0.86vs.0.84),特异性(Sp;0.90vs.0.78),阳性预测值(PPV;0.83vs.0.70),和阴性预测值(NPV;0.91vs.0.89)用于心肌缺血的检测。累积排序曲线分析表明,在本研究中,CA-FFR比CT-FFR具有更高的诊断准确性。ROC曲线下面积较高(AUC;0.94vs.0.87)。
结论:尽管这两种常用的虚拟FFR方法均显示出高水平的诊断准确性,我们证明CA-FFR具有更好的Se,SP,PPV,NPV,和AUC比CT-FFR。然而,这项研究仅提供了间接比较;因此,有必要进行更大规模的研究来直接比较这两种方法的诊断性能.
OBJECTIVE: Accumulating evidence has demonstrated that fractional flow reserves (FFRs) derived from invasive coronary angiograms (CA-FFRs) and coronary computed tomography angiography-derived FFRs (CT-FFRs) are promising alternatives to wire-based FFRs. However, it remains unclear which method has better diagnostic performance. This systematic
review and meta-analysis aimed to compare the diagnostic performances of the two approaches.
METHODS: The Cochrane Library, PubMed, Embase, Medline (Ovid), the Chinese China National Knowledge Infrastructure Database (CNKI), VIP, and WanFang Data databases were searched for relevant studies that included comparisons between CA-FFR and CT-FFR, from their respective database inceptions until January 1, 2023. Studies where both noninvasive FFR (including CA-FFR and CT-FFR) and invasive FFR (as a reference standard) were performed for the diagnosis of ischemic coronary artery disease and were designed as prospective, paired diagnostic studies, were pulled. The diagnostic test accuracy method and Bayesian hierarchical summary receiver operating characteristic (ROC) model for network meta-analysis (NMA) of diagnostic tests (HSROC-NMADT) were both used to perform a meta-analysis on the data.
RESULTS: Twenty-six studies were included in this NMA. The results from both the diagnostic test accuracy and HSROC-NMADT methods revealed that the diagnostic accuracy of CA-FFR was higher than that of CT-FFR, in terms of sensitivity (Se; 0.86 vs. 0.84), specificity (Sp; 0.90 vs. 0.78), positive predictive value (PPV; 0.83 vs. 0.70), and negative predictive value (NPV; 0.91 vs. 0.89) for the detection of myocardial ischemia. A cumulative ranking curve analysis indicated that CA-FFR had a higher diagnostic accuracy than CT-FFR in the context of this study, with a higher area under the ROC curve (AUC; 0.94 vs. 0.87).
CONCLUSIONS: Although both of these two commonly used virtual FFR methods showed high levels of diagnostic accuracy, we demonstrated that CA-FFR had a better Se, Sp, PPV, NPV, and AUC than CT-FFR. However, this study provided only indirect comparisions; therefore, larger studies are warranted to directly compare the diagnostic performances of these two approaches.