Utility of Inferior Lead Q-waveforms in diagnosing Ventricular Tachycardia

Swathi Subramany; Ajoe John Kattoor; Swathi Kovelamudi; Subodh Devabhaktuni; Jawahar L Mehta; Srikanth Vallurupalli; Hakan Paydak; Naga Venkata K Pothineni

doi:10.1177/1179546820953416

Utility of Inferior Lead Q-waveforms in diagnosing Ventricular Tachycardia

Clin Med Insights Cardiol. 2020 Aug 30:14:1179546820953416. doi: 10.1177/1179546820953416. eCollection 2020.

Authors

Swathi Subramany¹, Ajoe John Kattoor², Swathi Kovelamudi³, Subodh Devabhaktuni³, Jawahar L Mehta³, Srikanth Vallurupalli³, Hakan Paydak³, Naga Venkata K Pothineni⁴

Affiliations

¹ Division of Internal medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
² Division of Cardiology, Cook County Health, Chicago, IL, USA.
³ Division of Cardiovascular medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
⁴ Division of Cardiovascular medicine, University of Pennsylvania, Philadelphia, PA, USA.

Abstract

Background: Electrocardiogram (ECG) differentiation of wide complex tachycardia (WCT) into ventricular tachycardia (VT) and supraventricular tachycardia with aberration (SVT-A) is often challenging.

Objective: 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.

Methods: 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.

Results: 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).

Conclusion: 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.

Keywords: Ventricular tachycardia; electrocardiogram.