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Comparative analysis of electrocardiographic imaging and ECG in predicting the origin of outflow tract ventricular arrhythmias
OBJECTIVES: The aim of this study was to investigate the accuracy of electrocardiographic imaging (ECGI) in localizing the origin of outflow tract ventricular arrhythmias (OTVAs) and compare its performance with that of seven published 12-lead electrocardiography (ECG) algorithms. METHODS: Patients...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132561/ https://www.ncbi.nlm.nih.gov/pubmed/32228331 http://dx.doi.org/10.1177/0300060520913132 |
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author | Zhou, Xinbin Fang, Lin Wang, Zhijun Liu, Huafeng Mao, Wei |
author_facet | Zhou, Xinbin Fang, Lin Wang, Zhijun Liu, Huafeng Mao, Wei |
author_sort | Zhou, Xinbin |
collection | PubMed |
description | OBJECTIVES: The aim of this study was to investigate the accuracy of electrocardiographic imaging (ECGI) in localizing the origin of outflow tract ventricular arrhythmias (OTVAs) and compare its performance with that of seven published 12-lead electrocardiography (ECG) algorithms. METHODS: Patients with OTVAs who were undergoing catheter ablation were prospectively investigated. The OVTA origins were localized using both ECGI and seven 12-lead ECG algorithms, with the successful ablation site set as the gold standard. The performance of the ECGI and 12-lead ECG algorithms were compared. RESULTS: Twenty-seven patients were enrolled into the study. The ECGI system correctly identified the chamber of OTVA origin in 27/27 (100%) patients and the sublocalization within the right ventricular outflow tract (RVOT) in 21/22 (95.5%) patients. However, the ECG algorithms correctly diagnosed the chamber and sublocalization in only 21/27 (77.8%) patients and 13/22 (59.1%) patients, respectively, which was significantly lower compared with the ECGI system. CONCLUSIONS: Non-invasive ECGI can accurately predict the origin of OTVAs in a manner that is superior to that of conventional 12-lead ECGs in differentiating the RVOT from the left ventricular outflow tract (LVOT) and septum from free wall in the RVOT. This provides a useful tool to guide catheter ablation. This trial has been registered in the Chinese Clinical Trial Registry (Registration number: ChiCTR1900025527). |
format | Online Article Text |
id | pubmed-7132561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-71325612020-04-13 Comparative analysis of electrocardiographic imaging and ECG in predicting the origin of outflow tract ventricular arrhythmias Zhou, Xinbin Fang, Lin Wang, Zhijun Liu, Huafeng Mao, Wei J Int Med Res Prospective Clinical Research Report OBJECTIVES: The aim of this study was to investigate the accuracy of electrocardiographic imaging (ECGI) in localizing the origin of outflow tract ventricular arrhythmias (OTVAs) and compare its performance with that of seven published 12-lead electrocardiography (ECG) algorithms. METHODS: Patients with OTVAs who were undergoing catheter ablation were prospectively investigated. The OVTA origins were localized using both ECGI and seven 12-lead ECG algorithms, with the successful ablation site set as the gold standard. The performance of the ECGI and 12-lead ECG algorithms were compared. RESULTS: Twenty-seven patients were enrolled into the study. The ECGI system correctly identified the chamber of OTVA origin in 27/27 (100%) patients and the sublocalization within the right ventricular outflow tract (RVOT) in 21/22 (95.5%) patients. However, the ECG algorithms correctly diagnosed the chamber and sublocalization in only 21/27 (77.8%) patients and 13/22 (59.1%) patients, respectively, which was significantly lower compared with the ECGI system. CONCLUSIONS: Non-invasive ECGI can accurately predict the origin of OTVAs in a manner that is superior to that of conventional 12-lead ECGs in differentiating the RVOT from the left ventricular outflow tract (LVOT) and septum from free wall in the RVOT. This provides a useful tool to guide catheter ablation. This trial has been registered in the Chinese Clinical Trial Registry (Registration number: ChiCTR1900025527). SAGE Publications 2020-03-31 /pmc/articles/PMC7132561/ /pubmed/32228331 http://dx.doi.org/10.1177/0300060520913132 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Prospective Clinical Research Report Zhou, Xinbin Fang, Lin Wang, Zhijun Liu, Huafeng Mao, Wei Comparative analysis of electrocardiographic imaging and ECG in predicting the origin of outflow tract ventricular arrhythmias |
title | Comparative analysis of electrocardiographic imaging and ECG
in predicting the origin of outflow tract ventricular
arrhythmias |
title_full | Comparative analysis of electrocardiographic imaging and ECG
in predicting the origin of outflow tract ventricular
arrhythmias |
title_fullStr | Comparative analysis of electrocardiographic imaging and ECG
in predicting the origin of outflow tract ventricular
arrhythmias |
title_full_unstemmed | Comparative analysis of electrocardiographic imaging and ECG
in predicting the origin of outflow tract ventricular
arrhythmias |
title_short | Comparative analysis of electrocardiographic imaging and ECG
in predicting the origin of outflow tract ventricular
arrhythmias |
title_sort | comparative analysis of electrocardiographic imaging and ecg
in predicting the origin of outflow tract ventricular
arrhythmias |
topic | Prospective Clinical Research Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132561/ https://www.ncbi.nlm.nih.gov/pubmed/32228331 http://dx.doi.org/10.1177/0300060520913132 |
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