BACKGROUND: Previously presented new electrocardiography (ECG) algorithm for localization of arrhythmogenic focus (AFo) in right ventricular outflow tract (RVOT) was based on spontaneous arrhythmia QRS morphology analysis. The aim of this study was to estimate the clinical value of our RVOT algorithm in a prospective study. METHODS AND RESULTS: Algorithm validation was made on 62 patients with RVOT arrhythmias (45 women), mean age 41.6 ± 14.3 years, scheduled for transcatheter ablation. Results of preablation ECG analysis with RVOT algorithm were matched with successful ablation sites and statistical indices: sensitivity (sens), specificity (spec), and positive and negative predictive values (PPV, NPV) were calculated for algorithm and for each of 9 RVOT zones (septal and free wall). An algorithm precisely localized AFo in 57 out of 62 patients (sens 91.3%, spec 99%, PPV 91%, NPV 98.8%). Sensitivity values for superior RVOT aspect (71% patients) varied from 88% to 100%, specificity from 95.9% to 100%; PPV values from 85.7% to 100%, NPV from 92.5% to 100%. Although the total number of patients was relatively small in the 2 remaining RVOT aspects (29% patients) high values (sens, spec, PPV, NPV) were gained for intermediate and inferior zones. CONCLUSIONS: On the basis of spontaneous arrhythmia QRS analysis, a novel algorithm was built for preablation localization of RVOT arrhythmia in 1 of the 9 RVOT zones. Prospective analysis of our ECG algorithm confirmed that it is a valuable tool to predict the site of successful ablation in patients with RVOT arrhythmias.
BACKGROUND: Previously presented new electrocardiography (ECG) algorithm for localization of arrhythmogenic focus (AFo) in right ventricular outflow tract (RVOT) was based on spontaneous arrhythmia QRS morphology analysis. The aim of this study was to estimate the clinical value of our RVOT algorithm in a prospective study. METHODS AND RESULTS: Algorithm validation was made on 62 patients with RVOT arrhythmias (45 women), mean age 41.6 ± 14.3 years, scheduled for transcatheter ablation. Results of preablation ECG analysis with RVOT algorithm were matched with successful ablation sites and statistical indices: sensitivity (sens), specificity (spec), and positive and negative predictive values (PPV, NPV) were calculated for algorithm and for each of 9 RVOT zones (septal and free wall). An algorithm precisely localized AFo in 57 out of 62 patients (sens 91.3%, spec 99%, PPV 91%, NPV 98.8%). Sensitivity values for superior RVOT aspect (71% patients) varied from 88% to 100%, specificity from 95.9% to 100%; PPV values from 85.7% to 100%, NPV from 92.5% to 100%. Although the total number of patients was relatively small in the 2 remaining RVOT aspects (29% patients) high values (sens, spec, PPV, NPV) were gained for intermediate and inferior zones. CONCLUSIONS: On the basis of spontaneous arrhythmia QRS analysis, a novel algorithm was built for preablation localization of RVOT arrhythmia in 1 of the 9 RVOT zones. Prospective analysis of our ECG algorithm confirmed that it is a valuable tool to predict the site of successful ablation in patients with RVOT arrhythmias.