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. 2007 Mar;28(5):589-600.
doi: 10.1093/eurheartj/ehl473. Epub 2007 Feb 1.

Application of a new algorithm in the differential diagnosis of wide QRS complex tachycardia

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Application of a new algorithm in the differential diagnosis of wide QRS complex tachycardia

András Vereckei et al. Eur Heart J. 2007 Mar.

Abstract

Aims: The Brugada criteria proposed to distinguish between regular, monomorphic wide QRS complex tachycardias (WCT) caused by supraventricular (SVT) and ventricular tachycardia (VT) have been reported to have a better sensitivity and specificity than the traditional criteria. By incorporating two new criteria, a new, simplified algorithm was devised and compared with the Brugada criteria.

Methods and results: A total of 453 WCTs (331 VTs, 105 SVTs, 17 pre-excited tachycardias) from 287 consecutive patients with a proven electrophysiological (EP) diagnosis were prospectively analysed by two of the authors blinded to the EP diagnosis. The following criteria were analysed: (i) presence of AV dissociation; (ii) presence of an initial R wave in lead aVR; (iii) whether the morphology of the WCT correspond to bundle branch or fascicular block; (iv) estimation of initial (v(i)) and terminal (v(t)) ventricular activation velocity ratio (v(i)/v(t)) by measuring the voltage change on the ECG tracing during the initial 40 ms (v(i)) and the terminal 40 ms (v(t)) of the same bi- or multiphasic QRS complex. A v(i)/v(t) >1 was suggestive of SVT and a v(i)/v(t) <or=1 of VT. An initial R wave in lead aVR suggested VT. The overall test accuracy of the new algorithm was superior (P = 0.006) to that of the Brugada criteria. The new algorithm had a greater sensitivity (P < 0.001) and (-) predictive value (NPV) for VT diagnosis, and specificity (P = 0.0471) and (+) predictive value (PPV) for SVT diagnosis than those of the Brugada criteria [both NPV for VT diagnosis and PPV for SVT diagnosis were: 83.5% (95% confidence interval = CI 75.9-91.1%) for the new vs. 65.2% (95% CI 56.5-73.9%) for the Brugada algorithms].

Conclusion: The new algorithm is a highly accurate tool for correctly diagnosing the cause of WCT ECGs.

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