New algorithm using only lead aVR for differential diagnosis of wide QRS complex tachycardia.
Publication/Presentation Date
1-1-2008
Abstract
BACKGROUND: We recently reported an ECG algorithm for differential diagnosis of regular wide QRS complex tachycardias that was superior to the Brugada algorithm.
OBJECTIVE: The purpose of this study was to further simplify the algorithm by omitting the complicated morphologic criteria and restricting the analysis to lead aVR.
METHODS: In this study, 483 wide QRS complex tachycardias [351 ventricular tachycardias (VTs), 112 supraventricular tachycardias (SVTs), 20 preexcited tachycardias] from 313 patients with proven diagnoses were prospectively analyzed by two of the authors blinded to the diagnosis. Lead aVR was analyzed for (1) presence of an initial R wave, (2) width of an initial r or q wave >40 ms, (3) notching on the initial downstroke of a predominantly negative QRS complex, and (4) ventricular activation-velocity ratio (v(i)/v(t)), the vertical excursion (in millivolts) recorded during the initial (v(i)) and terminal (v(t)) 40 ms of the QRS complex. When any of criteria 1 to 3 was present, VT was diagnosed; when absent, the next criterion was analyzed. In step 4, v(i)/v(t) >1 suggested SVT, and v(i)/v(t) < or =1 suggested VT.
RESULTS: The accuracy of the new aVR algorithm and our previous algorithm was superior to that of the Brugada algorithm (P = .002 and P = .007, respectively). The aVR algorithm and our previous algorithm had greater sensitivity (P
CONCLUSION: The simplified aVR algorithm classified wide QRS complex tachycardias with the same accuracy as standard criteria and our previous algorithm and was superior to the Brugada algorithm.
Volume
5
Issue
1
First Page
89
Last Page
98
ISSN
1547-5271
Published In/Presented At
Vereckei, A., Duray, G., Szénási, G., Altemose, G. T., & Miller, J. M. (2008). New algorithm using only lead aVR for differential diagnosis of wide QRS complex tachycardia. Heart rhythm, 5(1), 89–98. https://doi.org/10.1016/j.hrthm.2007.09.020
Disciplines
Medicine and Health Sciences
PubMedID
18180024
Department(s)
Department of Medicine
Document Type
Article
