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High-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes
BACKGROUND: Persistent Atrial Fibrillation (PersAF) electrogram-based ablation is complex, and appropriate identification of atrial substrate is critical. Little is known regarding the value of the Average Complex Interval (ACI) feature for PersAF ablation. OBJECTIVE: Using the evolution of AF compl...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469913/ https://www.ncbi.nlm.nih.gov/pubmed/37663412 http://dx.doi.org/10.3389/fcvm.2023.1145894 |
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author | Squara, Fabien Scarlatti, Didier Bun, Sok-Sithikun Moceri, Pamela Ferrari, Emile Meste, Olivier Zarzoso, Vicente |
author_facet | Squara, Fabien Scarlatti, Didier Bun, Sok-Sithikun Moceri, Pamela Ferrari, Emile Meste, Olivier Zarzoso, Vicente |
author_sort | Squara, Fabien |
collection | PubMed |
description | BACKGROUND: Persistent Atrial Fibrillation (PersAF) electrogram-based ablation is complex, and appropriate identification of atrial substrate is critical. Little is known regarding the value of the Average Complex Interval (ACI) feature for PersAF ablation. OBJECTIVE: Using the evolution of AF complexity by sequentially computing AF dominant frequency (DF) along the ablation procedure, we sought to evaluate the value of ACI for discriminating active drivers (AD) from bystander zones (BZ), for predicting AF termination during ablation, and for predicting AF recurrence during follow-up. METHODS: We included PersAF patients undergoing radiofrequency catheter ablation by pulmonary vein isolation and ablation of atrial substrate identified by Spatiotemporal Dispersion or Complex Fractionated Atrial Electrograms (>70% of recording). Operators were blinded to ACI measurement which was sought for each documented atrial substrate area. AF DF was measured by Independent Component Analysis on 1-minute 12-lead ECGs at baseline and after ablation of each atrial zone. AD were differentiated from BZ either by a significant decrease in DF (>10%), or by AF termination. Arrhythmia recurrence was monitored during follow-up. RESULTS: We analyzed 159 atrial areas (129 treated by radiofrequency during AF) in 29 patients. ACI was shorter in AD than BZ (76.4 ± 13.6 vs. 86.6 ± 20.3 ms; p = 0.0055), and mean ACI of all substrate zones was shorter in patients for whom radiofrequency failed to terminate AF [71.3 (67.5–77.8) vs. 82.4 (74.4–98.5) ms; p = 0.0126]. ACI predicted AD [AUC 0.728 (0.629–0.826)]. An ACI < 70 ms was specific for predicting AD (Sp 0.831, Se 0.526), whereas areas with an ACI > 100 ms had almost no chances of being active in AF maintenance. AF recurrence was associated with more ACI zones with identical shortest value [3.5 (3–4) vs. 1 (0–1) zones; p = 0.021]. In multivariate analysis, ACI < 70 ms predicted AD [OR = 4.02 (1.49–10.84), p = 0.006] and mean ACI > 75 ms predicted AF termination [OR = 9.94 (1.14–86.7), p = 0.038]. CONCLUSION: ACI helps in identifying AF drivers, and is correlated with AF termination and AF recurrence during follow-up. It can help in establishing an ablation plan, by prioritizing ablation from the shortest to the longest ACI zone. |
format | Online Article Text |
id | pubmed-10469913 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104699132023-09-01 High-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes Squara, Fabien Scarlatti, Didier Bun, Sok-Sithikun Moceri, Pamela Ferrari, Emile Meste, Olivier Zarzoso, Vicente Front Cardiovasc Med Cardiovascular Medicine BACKGROUND: Persistent Atrial Fibrillation (PersAF) electrogram-based ablation is complex, and appropriate identification of atrial substrate is critical. Little is known regarding the value of the Average Complex Interval (ACI) feature for PersAF ablation. OBJECTIVE: Using the evolution of AF complexity by sequentially computing AF dominant frequency (DF) along the ablation procedure, we sought to evaluate the value of ACI for discriminating active drivers (AD) from bystander zones (BZ), for predicting AF termination during ablation, and for predicting AF recurrence during follow-up. METHODS: We included PersAF patients undergoing radiofrequency catheter ablation by pulmonary vein isolation and ablation of atrial substrate identified by Spatiotemporal Dispersion or Complex Fractionated Atrial Electrograms (>70% of recording). Operators were blinded to ACI measurement which was sought for each documented atrial substrate area. AF DF was measured by Independent Component Analysis on 1-minute 12-lead ECGs at baseline and after ablation of each atrial zone. AD were differentiated from BZ either by a significant decrease in DF (>10%), or by AF termination. Arrhythmia recurrence was monitored during follow-up. RESULTS: We analyzed 159 atrial areas (129 treated by radiofrequency during AF) in 29 patients. ACI was shorter in AD than BZ (76.4 ± 13.6 vs. 86.6 ± 20.3 ms; p = 0.0055), and mean ACI of all substrate zones was shorter in patients for whom radiofrequency failed to terminate AF [71.3 (67.5–77.8) vs. 82.4 (74.4–98.5) ms; p = 0.0126]. ACI predicted AD [AUC 0.728 (0.629–0.826)]. An ACI < 70 ms was specific for predicting AD (Sp 0.831, Se 0.526), whereas areas with an ACI > 100 ms had almost no chances of being active in AF maintenance. AF recurrence was associated with more ACI zones with identical shortest value [3.5 (3–4) vs. 1 (0–1) zones; p = 0.021]. In multivariate analysis, ACI < 70 ms predicted AD [OR = 4.02 (1.49–10.84), p = 0.006] and mean ACI > 75 ms predicted AF termination [OR = 9.94 (1.14–86.7), p = 0.038]. CONCLUSION: ACI helps in identifying AF drivers, and is correlated with AF termination and AF recurrence during follow-up. It can help in establishing an ablation plan, by prioritizing ablation from the shortest to the longest ACI zone. Frontiers Media S.A. 2023-08-17 /pmc/articles/PMC10469913/ /pubmed/37663412 http://dx.doi.org/10.3389/fcvm.2023.1145894 Text en © 2023 Squara, Scarlatti, Bun, Moceri, Ferrari, Meste and Zarzoso. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Squara, Fabien Scarlatti, Didier Bun, Sok-Sithikun Moceri, Pamela Ferrari, Emile Meste, Olivier Zarzoso, Vicente High-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes |
title | High-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes |
title_full | High-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes |
title_fullStr | High-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes |
title_full_unstemmed | High-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes |
title_short | High-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes |
title_sort | high-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469913/ https://www.ncbi.nlm.nih.gov/pubmed/37663412 http://dx.doi.org/10.3389/fcvm.2023.1145894 |
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