Subramany Swathi, Kattoor Ajoe John, Kovelamudi Swathi, Devabhaktuni Subodh, Mehta Jawahar L, Vallurupalli Srikanth, Paydak Hakan, Pothineni Naga Venkata K
Division of Internal medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Division of Cardiology, Cook County Health, Chicago, IL, USA.
Clin Med Insights Cardiol. 2020 Aug 30;14:1179546820953416. doi: 10.1177/1179546820953416. eCollection 2020.
Electrocardiogram (ECG) differentiation of wide complex tachycardia (WCT) into ventricular tachycardia (VT) and supraventricular tachycardia with aberration (SVT-A) is often challenging.
To determine if the presence of Q-waveforms (QS, Qr, QRs) in the inferior leads (II, III, aVF) can differentiate VT from SVT-A in a WCT compared to Brugada algorithm. We studied 2 inferior lead criteria namely QWC-A where all the inferior leads had a similar Q wave pattern and QWC-B where only lead aVF had a Q-waveform.
A total of 181 consecutive cases of WCT were identified, digitally separated into precordial leads and inferior leads and independently reviewed by 2 electrophysiologists. An electrocardiographic diagnosis of VT or SVT-A was assigned based on Brugada and inferior lead algorithms. Results were compared to the final clinical diagnosis.
VT was the final clinical diagnosis in 24.9% of ECG cohort (45/181); 75.1% (136/181) were SVT-A. QWC-A and QWC-B had a high specificity (93.3% and 82.8%) and accuracy (78.2% and 71.0%), but low sensitivity (33.3% and 35.6%) in differentiating VT from SVT-A. The Brugada algorithm yielded a sensitivity of 82.2% and specificity of 68.4%. Area under the curve in ROC analysis was highest with Brugada algorithm (0.75, 95% CI 0.69-0.81) followed by QWC-A (0.63, 95% CI 0.56-0.70) and QWC-B (0.59, 95% CI 0.52-0.67).
QWC-A and QWC-B criteria had poor sensitivity but high specificity in diagnosing VT in patients presenting with WCT. Further research combining this simple criterion with other newer diagnostic algorithms can potentially improve the accuracy of the overall diagnostic algorithm.
将宽QRS波心动过速(WCT)心电图(ECG)鉴别为室性心动过速(VT)和伴差异性传导的室上性心动过速(SVT-A)通常具有挑战性。
确定下壁导联(II、III、aVF)中Q波形(QS、Qr、QRs)的存在与Brugada算法相比,能否在WCT中鉴别VT和SVT-A。我们研究了2种下壁导联标准,即QWC-A(所有下壁导联具有相似的Q波形态)和QWC-B(仅aVF导联有Q波形)。
共识别出181例连续的WCT病例,将其数字化分离为胸前导联和下壁导联,并由2名电生理学家独立审查。根据Brugada算法和下壁导联算法对VT或SVT-A进行心电图诊断。将结果与最终临床诊断进行比较。
在心电图队列中,24.9%(45/181)的最终临床诊断为VT;75.1%(136/181)为SVT-A。在鉴别VT和SVT-A时,QWC-A和QWC-B具有较高的特异性(分别为93.3%和82.8%)和准确性(分别为78.2%和71.0%),但敏感性较低(分别为33.3%和35.6%)。Brugada算法的敏感性为82.2%,特异性为68.4%。ROC分析中,曲线下面积以Brugada算法最高(0.75,95%CI 0.69-0.81),其次是QWC-A(0.63,95%CI 0.56-0.70)和QWC-B(0.59,95%CI 0.52-0.67)。
QWC-A和QWC-B标准在诊断WCT患者的VT时敏感性较差,但特异性较高。将这个简单标准与其他更新的诊断算法相结合的进一步研究可能会提高整体诊断算法的准确性。