AIMS: Patients with non-ischaemic cardiomyopathy (NICM) and ventricular tachycardia can be categorized as anteroseptal (AS) or inferolateral (IL) scar sub-types based on imaging and voltage mapping studies. The aim of this study was to correlate the baseline electrocardiogram (ECG) with endo-epicardial voltage maps created during ablation procedures and identify the ECG characteristics that may help to distinguish the scar as AS or IL. METHODS AND RESULTS: We assessed 108 baseline ECGs; 72 patients fulfilled criteria for dilated cardiomyopathy whereas 36 showed minimal structural abnormalities. Based on the unipolar low-voltage distribution, the scar pattern was classified as predominantly AS (n = 59) or IL (n = 49). Three ECG criteria (PR interval < 170 ms or QRS voltage in inferior leads <0.6 mV or a lateral q wave) resulted in 92% sensitivity and 90% specificity for predicting an IL pattern in patients with preserved ejection fraction (EF). The four-step algorithm for dilated cardiomyopathy included a paced ventricular rhythm or PR > 230 ms or QRS > 170 ms or an r ≤ 0.3 mV in V3 having 92 and 81% of sensitivity and specificity, respectively, in predicting AS scar pattern. A significant negative correlation was found between the extension of the endocardial unipolar low voltage area and left ventricular EF (rs = -0.719, P < 0.001). The extent of endocardial AS unipolar low voltage was correlated with PR interval and QRS duration (rs = 0.583 and rs = 0.680, P < 0.001, respectively) and the IL epicardial unipolar low voltage with the mean voltage of the limb leads (rs = -0.639, P < 0.001). CONCLUSION: Baseline ECG features are well correlated with the distribution of unipolar voltage abnormalities in NICM and may help to predict the location of scar in this population. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: Patients with non-ischaemic cardiomyopathy (NICM) and ventricular tachycardia can be categorized as anteroseptal (AS) or inferolateral (IL) scar sub-types based on imaging and voltage mapping studies. The aim of this study was to correlate the baseline electrocardiogram (ECG) with endo-epicardial voltage maps created during ablation procedures and identify the ECG characteristics that may help to distinguish the scar as AS or IL. METHODS AND RESULTS: We assessed 108 baseline ECGs; 72 patients fulfilled criteria for dilated cardiomyopathy whereas 36 showed minimal structural abnormalities. Based on the unipolar low-voltage distribution, the scar pattern was classified as predominantly AS (n = 59) or IL (n = 49). Three ECG criteria (PR interval < 170 ms or QRS voltage in inferior leads <0.6 mV or a lateral q wave) resulted in 92% sensitivity and 90% specificity for predicting an IL pattern in patients with preserved ejection fraction (EF). The four-step algorithm for dilated cardiomyopathy included a paced ventricular rhythm or PR > 230 ms or QRS > 170 ms or an r ≤ 0.3 mV in V3 having 92 and 81% of sensitivity and specificity, respectively, in predicting AS scar pattern. A significant negative correlation was found between the extension of the endocardial unipolar low voltage area and left ventricular EF (rs = -0.719, P < 0.001). The extent of endocardial AS unipolar low voltage was correlated with PR interval and QRS duration (rs = 0.583 and rs = 0.680, P < 0.001, respectively) and the IL epicardial unipolar low voltage with the mean voltage of the limb leads (rs = -0.639, P < 0.001). CONCLUSION: Baseline ECG features are well correlated with the distribution of unipolar voltage abnormalities in NICM and may help to predict the location of scar in this population. Published on behalf of the European Society of Cardiology. All rights reserved.
Authors: Philip M Gemmell; Karli Gillette; Gabriel Balaban; Ronak Rajani; Edward J Vigmond; Gernot Plank; Martin J Bishop Journal: Comput Biol Med Date: 2020-07-04 Impact factor: 4.589
Authors: Giovanni Peretto; Andrea Villatore; Stefania Rizzo; Antonio Esposito; Giacomo De Luca; Anna Palmisano; Davide Vignale; Alberto Maria Cappelletti; Moreno Tresoldi; Corrado Campochiaro; Silvia Sartorelli; Marco Ripa; Monica De Gaspari; Elena Busnardo; Paola Ferro; Maria Grazia Calabrò; Evgeny Fominskiy; Fabrizio Monaco; Giulio Cavalli; Luigi Gianolli; Francesco De Cobelli; Alberto Margonato; Lorenzo Dagna; Mara Scandroglio; Paolo Guido Camici; Patrizio Mazzone; Paolo Della Bella; Cristina Basso; Simone Sala Journal: J Clin Med Date: 2021-05-04 Impact factor: 4.241