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[Value of aVR lead four steps algorithm on differential diagnosis of wide QRS complex tachycardia]
Tao Lin1, Yi-tong Ma, Yati Muhu
1Department of Cardiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China.
Objective:
The aVR lead four steps is a new algorithm for differential diagnosis of wide QRS complex tachycardia (WCT). The study explores the clinical value of this new algorithm on differential diagnosis of WCT.
Methods:
Application of aVR lead four steps to analysis the electrocardiogram of patients with WCT proved by electrophysiological study. Every step's accuracy rate, sensitivity and specificity to differential diagnosis of ventricular tachycardia (VT) were calculated. The first step diagnosed VT according to presence of an initial R wave in the aVR lead. The second step diagnosed VT according to width of an initial r or q wave > 40 ms in the aVR lead. The third step diagnosed VT according to notching on the initial downstroke of a predominantly negative QRS complex in the aVR lead. The fourth step diagnosis VT according to ventricular activation-velocity ratio (Vi/Vt) in the aVR lead, Vi/Vt ≤ 1 suggested VT. Results derived from aVR lead four steps algorithm were compared with results derived from Brugada and Vereckei four steps algorithm.
Results:
A total of 113 patients with WCT were analyzed (31 supraventricular tachycardia, SVT and 82 ventricular tachycardia, VT). The accuracy rate of differential diagnosis VT is 91.2%, sensitivity is 90.2% and specificity is 77.4%. The accuracy and sensitivity of the aVR lead four steps algorithm for differential diagnosis of WCT were superior to the Brugada Vereckei four steps algorithm (P < 0.05). The specificity of the Vereckei four steps algorithm was superior to aVR lead and Brugada four steps algorithm (P < 0.05), while the specificity of the aVR lead four steps algorithm was similar as Brugada four steps algorithm (P > 0.05).
Conclusions:
The aVR lead four steps algorithm is associated with excellent accuracy rate, sensitivity for differential diagnosis of WCT. This algorithm is simple and could be easily learned and applied by physician.
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