Diagnostic accuracy of anatomic vs functional tests for coronary artery disease in patients with left bundle branch block and right ventricular pacing

REC: CardioClinics(2024)

引用 0|浏览2
暂无评分
摘要
Introduction and objectives A lower accuracy of functional tests for the diagnosis of significant coronary disease in patients with left bundle branch block (LBBB) has been described, due to a greater number of false positives. The aim of this study was to evaluate whether an anatomic test such as computerized tomography coronary angiogram (CTCA) outperforms SPECT myocardial perfusion imaging (SPECT-MPI) or dobutamine stress echocardiography (DSE) in the diagnosis of significant coronary artery disease in patients with LBBB and right ventricular pacing. Methods Observational study of 149 patients with LBBB and right ventricular pacing referred to SPECT-MPI, DSE or CTCA at three centers. Diagnostic performance (predictive accuracy, sensitivity, specificity, positive and negative predictive value) was evaluated using coronary angiography as the benchmark. Results The study included 77 patients who underwent SPECT-MPI, 39 who performed DSE and 33 who performed CTCA. The prevalence of obstructive coronary disease was similar in the three cohorts, with a higher rate of abnormal results on SPECT-MPI (84% vs 64% vs 61%; P=.009). Predicted accuracy was significantly lower in the SPECT-MPI group (39% vs 64% vs 67%; P=.006). DSE and CTCA showed a similar rate of abnormal results, as well as similar predictive accuracy (64% vs 67%; P>.999). Conclusions In patients with LBBB and right ventricular pacing, DSE and CTCA had similar accuracy and performed better than SPECT-MPI for the diagnosis of significant coronary artery disease.
更多
查看译文
关键词
Stress echocardiography,SPECT myocardial perfusion,Diagnostic imaging,Computed tomography angiography,Bundle branch block,Ecocardiografía de estrés,SPECT de perfusión miocárdica,Diagnóstico por imagen,Angiografía por tomografía computarizada,Bloqueo de rama
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要