First Department of Cardiology and Hypertension, University Hospital, Cracow, Poland.
Europace. 2012 Aug;14(8):1165-71. doi: 10.1093/europace/eus015. Epub 2012 Feb 14.
To compare the sensitivity (SN), specificity (SP), and diagnostic accuracy (ACC) for ventricular tachycardia (VT) diagnosis of five electrocardiographic methods for wide QRS-complex tachycardia (WCT) differentiation, specifically the Brugada, Bayesian, Griffith, and aVR algorithms, and the lead II R-wave-peak-time (RWPT) criterion.
We retrospectively analysed 260 WCTs from 204 patients with proven diagnoses. The SN, SP, ACC, and likelihood ratios (LRs) were determined for the five methods. Of the 260 tracings, there were 159 VTs and 101 supraventricular tachycardias. All five methods were found to have a similar ACC although the RWPT had a lower ACC than the Brugada algorithm (68.8 vs. 77.5%, P = 0.04). The RWPT had lower (60%) SN than the Brugada (89.0%), Griffith (94.2%), and Bayesian (89%) algorithms (P < 0.001). The Griffith algorithm showed lower (39.8%) SP than the RWPT (82.7%), Brugada (59.2%), and Bayesian (52.0%) algorithms (P< 0.05). The positive LRs for a VT diagnosis for the RWPT criterion and the Brugada, Bayesian, aVR, and Griffith algorithms were 3.46, 2.18, 1.86, 1.67, and 1.56, respectively.
The present study is the first independent 'head-to-head' comparison of several WCT differentiation methods. We found that all five algorithms/criteria had rather moderate ACC, and that the newer methods were not more accurate than the classic Brugada algorithm. However, the algorithms/criteria differed significantly in terms of SN, SP, and LR, suggesting that the value of a diagnosis may differ depending on the method used.
比较五种宽 QRS 心动过速（WCT）鉴别诊断室性心动过速（VT）的心电图方法的敏感性（SN）、特异性（SP）和诊断准确性（ACC），具体包括 Brugada、Bayesian、Griffith 和 aVR 算法以及 II 导联 R 波峰时间（RWPT）标准。
我们回顾性分析了 204 例确诊患者的 260 例 WCT。确定了五种方法的 SN、SP、ACC 和似然比（LR）。在 260 条记录中，有 159 条 VT 和 101 条室上性心动过速。尽管 RWPT 的 ACC 低于 Brugada 算法（68.8%比 77.5%，P=0.04），但所有五种方法的 ACC 均相似。RWPT 的 SN （60%）低于 Brugada（89.0%）、Griffith（94.2%）和 Bayesian（89%）算法（P<0.001）。Griffith 算法的 SP（39.8%）低于 RWPT（82.7%）、Brugada（59.2%）和 Bayesian（52.0%）算法（P<0.05）。RWPT 标准和 Brugada、Bayesian、aVR 和 Griffith 算法的 VT 诊断阳性 LR 分别为 3.46、2.18、1.86、1.67 和 1.56。
本研究是首次对几种 WCT 鉴别方法进行独立的“头对头”比较。我们发现，所有五种算法/标准的 ACC 都相当中等，而较新的方法并不比经典的 Brugada 算法更准确。然而，在 SN、SP 和 LR 方面，算法/标准存在显著差异，这表明诊断的价值可能因使用的方法而异。
