ECG identification of scar-related ventricular tachycardia with a left bundle-branch block configuration

Adrianus P Wijnmaalen, William G Stevenson, Martin J Schalij, Michael E Field, Kent Stephenson, Usha B Tedrow, Bruce A Koplan, Hein Putter, Lawrence M Epstein, Katja Zeppenfeld
Circulation. Arrhythmia and Electrophysiology 2011, 4 (4): 486-93

BACKGROUND: A left bundle-branch block (LBBB)-like pattern with a dominant S-wave in V(1) is common in idiopathic ventricular arrhythmias (VA). Discrimination between idiopathic and scar-related LBBB pattern VA has important clinical implications. We hypothesized that the VA QRS morphology is influenced by the presence of ventricular scar, allowing ECG discrimination of VA arising from structurally normal versus scarred myocardium.

METHODS AND RESULTS: Twelve-lead ECGs of 297 LBBB pattern monomorphic VA were recorded during catheter ablation procedures. QRS morphology characteristics associated with scar-related VA were identified in retrospective analysis of 118 LBBB pattern VA (95 scar-related, 23 idiopathic) to develop a stepwise algorithm that was prospectively tested in 179 LBBB pattern VA (120 scar-related, 59 idiopathic). The diagnosis of scar was based on sinus rhythm surface ECG, cardiovascular imaging, and electroanatomic catheter mapping. A precordial transition beyond V₄, notching of the S-wave downstroke in lead V₁ or V₂, and a duration from the onset of QRS to the S-nadir in V₁ >90 ms were independent predictors for scar-related VA. The proposed algorithm classified a VA as scar-related if any of these criteria was met. If none of the criteria was present, a VA was classified as idiopathic. In prospective validation, the algorithm was highly sensitive (96%) and specific (83%) for the identification of scar-related LBBB pattern VA.

CONCLUSIONS: The QRS morphology of VA is different between scar-related and idiopathic VA. A simple ECG algorithm is sensitive for identifying scar-related LBBB VA, which could be helpful in guiding further evaluation of these patients.

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