Abstract 2650: A New, Simple Algorithm for Diagnosing Wide QRS Complex Tachycardia: Comparison With Brugada, Vereckei and aVR Algorithms
For the differential diagnosis of wide QRS complex tachycardia (WCT), Brugada (Circulation 1991), Vereckei (Eur Heart J 2007) and Vereckei’s aVR (Heart Rhythm 2008) algorithms have been proposed. It is unclear which algorithm is more accurate. We applied these 3 algorithms to 107 WCT (71 ventricular tachycardia (VT) and 36 supraventricular tachycardia (SVT)) and examined the diagnostic accuracy. Based on the results, we revised these algorithms by proposing a new, simple algorithm, and compared its accuracy with the previous algorithms. Sensitivity and specificity for VT diagnosis were 86% and 67% by Brugada algorithm, 76% and 86% by Vereckei algorithm, and 86% and 53% by aVR algorithm, respectively. Among the diagnosing steps in the 3 algorithms, for diagnosing VT, atrioventricular dissociation had a low sensitivity (7%) and the assessment of bundle branch block morphology showed innegligible interobserver variation (10 to 20% by 3 independent observers). We then verified each diagnosing step in the 3 algorithms. The step with sensitivity ≥30% and specificity ≥90% for diagnosing VT included longest RS ≥100 msec (sensitivity, 37%; specificity, 97%), initial R in aVR (39% and 100%), and Vi/Vt ≤1.0 (49% and 90%). Evaluating Vi/Vt ≤1.0 indicative of slow initial ventricular activation in VT is complicated. Therefore, to simplify this step, we measured the duration of the initial r or q of any lead of WCTs and validated it. The duration was 55±27 msec in VT and 27±5 msec in SVT (P <0.05). Receiver operating curve revealed 40 msec as a cutoffpoint which showed 86% sensitivity and 97% specificity for diagnosing VT, both of which were greater than those of Vi/Vt ≤1.0. We proposed a new algorithm for diagnosing VT, including
initial R in aVR,
longest RS ≥100 msec, and
initial r or q ≥40 msec.
The accuracy of this new algorithm (86%) was superior to those of Brugada (79%), Vereckei (79%) and aVR (75%) algorithms (all P<0.05). For diagnosing VT, the new algorithm had greater sensitivity than Vereckei algorithm and greater specificity than Brugada and aVR algorithms (all P<0.05). Thus, this new algorithm with the 3 diagnosing steps is useful for diagnosing WCT accurately.