Marek Jastrzebski1, Kenichi Sasaki2, Piotr Kukla3, Kamil Fijorek4, Sebastian Stec5, Danuta Czarnecka6. 1. First Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University, College of Medicine, ul. Kopernika 17, Cracow 31-501, Poland mcjastrz@cyf-kr.edu.pl. 2. Department of Cardiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan. 3. Department of Internal Medicine and Cardiology, H. Klimontowicz Specialistic Hospital, Gorlice, Poland. 4. Department of Statistics, Cracow University of Economics, Cracow, Poland. 5. Department of Medicine, University of Rzeszow, Rzeszow, Poland. 6. First Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University, College of Medicine, ul. Kopernika 17, Cracow 31-501, Poland.
Abstract
AIMS: Electrocardiographic diagnosis of wide QRS complex tachycardia (WCT) continues to be challenging as none one of the available methods is specific for ventricular tachycardia (VT) diagnosis. We aimed to construct a method for WCT differentiation based on a scoring system, in which ECGs are graded according to the number of VT-specific features. This novel method was validated and compared with Brugada algorithm and other methods. METHODS AND RESULTS: A total of 786 WCTs (512 VTs) from 587 consecutive patients with a proven diagnosis were analysed by two blinded observers. The VT score method was based on seven ECG features: initial R wave in V1, initial r > 40 ms in V1/V2, notched S in V1, initial R in aVR, lead II R wave peak time ≥50 ms, no RS in V1-V6, and atrioventricular dissociation. Atrioventricular dissociation was assigned two points, and each of the other features was assigned one point. The overall accuracy of VT score ≥1 for VT diagnosis (83%) was higher than that of the aVR (72%, P = 0.001) and Brugada (81%) algorithms. Ventricular tachycardia score ≥3 was present in 66% of VTs and was more specific (99.6%) than any other algorithm/criterion for VT diagnosis. Ventricular tachycardia score ≥4 was present in 33% of VTs and was 100% specific for VT. CONCLUSION: The new ECG-based method provides a certain diagnosis of VT in the majority of patients with VT, identifies unequivocal ECGs, and has superior overall diagnostic accuracy to other ECG methods. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: Electrocardiographic diagnosis of wide QRS complex tachycardia (WCT) continues to be challenging as none one of the available methods is specific for ventricular tachycardia (VT) diagnosis. We aimed to construct a method for WCT differentiation based on a scoring system, in which ECGs are graded according to the number of VT-specific features. This novel method was validated and compared with Brugada algorithm and other methods. METHODS AND RESULTS: A total of 786 WCTs (512 VTs) from 587 consecutive patients with a proven diagnosis were analysed by two blinded observers. The VT score method was based on seven ECG features: initial R wave in V1, initial r > 40 ms in V1/V2, notched S in V1, initial R in aVR, lead II R wave peak time ≥50 ms, no RS in V1-V6, and atrioventricular dissociation. Atrioventricular dissociation was assigned two points, and each of the other features was assigned one point. The overall accuracy of VT score ≥1 for VT diagnosis (83%) was higher than that of the aVR (72%, P = 0.001) and Brugada (81%) algorithms. Ventricular tachycardia score ≥3 was present in 66% of VTs and was more specific (99.6%) than any other algorithm/criterion for VT diagnosis. Ventricular tachycardia score ≥4 was present in 33% of VTs and was 100% specific for VT. CONCLUSION: The new ECG-based method provides a certain diagnosis of VT in the majority of patients with VT, identifies unequivocal ECGs, and has superior overall diagnostic accuracy to other ECG methods. Published on behalf of the European Society of Cardiology. All rights reserved.
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Authors: Karol Deutsch; Sebastian Stec; Piotr Kukla; Aleksandra Morka; Marek Jastrzebski; Artur Baszko; Maciej Pitak; Janusz Sledz; Kamil Fijorek; Mariusz Mazij; Bartosz Ludwik; Marcin Gubaro; Leslaw Szydlowski Journal: Medicine (Baltimore) Date: 2015-12 Impact factor: 1.817