David Andreu1, Juan Fernández-Armenta2, Juan Acosta3, Diego Penela4, Beatriz Jáuregui4, David Soto-Iglesias4, Vladimir Syrovnev4, Elena Arbelo5, José María Tolosana5, Antonio Berruezo6. 1. Institut Clínic Cardiovascular, Hospital Clínic, Barcelona, Spain. 2. Hospital Universitario Puerta del Mar, Cádiz, Spain. 3. Hospital Universitario Virgen del Rocío, Sevilla, Spain. 4. Institut Clínic Cardiovascular, Hospital Clínic, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain. 5. Institut Clínic Cardiovascular, Hospital Clínic, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red Cardiovascular (CIBERCV), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. 6. Cardiology Department, Heart Institute, Teknon Medical Center, Barcelona, Spain. Electronic address: antonio.berruezo@quironsalud.es.
Abstract
BACKGROUND: Previously proposed algorithms to predict the ventricular tachycardia (VT) exit site have been based on diverse left ventricular models, but none of them identify the precise region of origin in the electroanatomic map. Moreover, no electrocardiographic (ECG) algorithm has been tested to predict the region of origin of scar-related VTs in patients with nonischemic cardiomyopathy. OBJECTIVE: The purpose of this study was to validate a simple ECG algorithm to identify the segment of origin (SgO) of VT relative to the 17-segment American Heart Association model in patients with structural heart disease (SHD). METHODS: The study included 108 consecutive patients with documented VT and SHD [77 (71%) with coronary artery disease]. A novel frontal plane axis-based ECG algorithm (highest positive or negative QRS voltage) together with the polarity in leads V3 and V4 was used to predict the SgO of VT. The actual SgO of VT was obtained from the analysis of the electroanatomic map during the procedure. Conventional VT mapping techniques were used to identify the VT exit. RESULTS: In total, 149 12-lead ECGs of successfully ablated VT were analyzed. The ECG-suggested SgO matched with the actual SgO in 122 of the 149 VTs (82%). In 21 of the 27 mismatched ECG-suggested SgOs (77.8%), the actual SgO was adjacent to the segment suggested by the ECG. There were no differences in the accuracy of the algorithm based on the SgO or the type of SHD. CONCLUSION: This novel QRS axis-based algorithm accurately identifies the SgO of VT in the 17-segment American Heart Association model in patients with SHD.
BACKGROUND: Previously proposed algorithms to predict the ventricular tachycardia (VT) exit site have been based on diverse left ventricular models, but none of them identify the precise region of origin in the electroanatomic map. Moreover, no electrocardiographic (ECG) algorithm has been tested to predict the region of origin of scar-related VTs in patients with nonischemic cardiomyopathy. OBJECTIVE: The purpose of this study was to validate a simple ECG algorithm to identify the segment of origin (SgO) of VT relative to the 17-segment American Heart Association model in patients with structural heart disease (SHD). METHODS: The study included 108 consecutive patients with documented VT and SHD [77 (71%) with coronary artery disease]. A novel frontal plane axis-based ECG algorithm (highest positive or negative QRS voltage) together with the polarity in leads V3 and V4 was used to predict the SgO of VT. The actual SgO of VT was obtained from the analysis of the electroanatomic map during the procedure. Conventional VT mapping techniques were used to identify the VT exit. RESULTS: In total, 149 12-lead ECGs of successfully ablated VT were analyzed. The ECG-suggested SgO matched with the actual SgO in 122 of the 149 VTs (82%). In 21 of the 27 mismatched ECG-suggested SgOs (77.8%), the actual SgO was adjacent to the segment suggested by the ECG. There were no differences in the accuracy of the algorithm based on the SgO or the type of SHD. CONCLUSION: This novel QRS axis-based algorithm accurately identifies the SgO of VT in the 17-segment American Heart Association model in patients with SHD.
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