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Contributing factors concerning inconsistencies in persistent atrial fibrillation ablation outcomes

Contributing factors concerning inconsistencies in persistent atrial fibrillation ablation outcomes
Contributing factors concerning inconsistencies in persistent atrial fibrillation ablation outcomes
Background: We investigated current clinical methods for complex fractionated atrial electrogram (CFAE) classification during persistent atrial fibrillation (persAF). In particular, factors that directly influence the low reproducibility of CFAE-guided ablation outcomes in persAF therapy, such as inconsistencies in automated CFAE classification performed by different systems, the co-existence of different types of atrial electrograms (AEGs), and insufficient AEG duration for CFAE detection. Methods: 797 bipolar AEGs were exported from NavX (St. Jude Medical) from 18 persAF patients undergoing pulmonary vein isolation and roof line ablation (PVI+RL). CFE-Mean, CFE-StdDev and peak-to-peak were exported from NavX, while the interval confidence level, average and shortest complex interval – as defined by CARTO (Biosense Webster) – were calculated offline using a validated MATLAB script. Sample entropy, dominant frequency and organization index were also calculated offline. Results: First, we show that CFAE classification varies for the same individual, depending on the commercial system being used. Revised thresholds were found for the indices calculated by each system to minimize the differences in automated CFAE detection performed independently by them. Second, our results show that some AEGs are affected by PVI+RL in persAF, while others remain unaffected by it. Different types of AEGs might correlate with distinct underlying persAF mechanisms. Multivariate analysis using the multiple descriptors measured from the AEGs effectively discriminated the different types of AEGs. Finally, we show that consecutive AEGs with 2.5 s resulted in different ablation target identification using the CARTO criterion, which would affect the ablation strategy and contribute to conflicting outcomes in AEGguided ablation in persAF. Our results suggest that CARTO should consider AEGs with longer duration to measure CFAEs. Conclusions: A thorough re-evaluation of the definition of CFAE is necessary in order to refine the identification of critical atrial regions responsible for the perpetuation of the arrhythmia in patients with persAF.
Almeida, Tiago
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Chu, Gavin
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Li, Xin
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Salinet, Joao
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Dastagir, Nawshin
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Bell, Michael
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Vanheusden, Frederique
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Tuan, Jiun
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Stafford, Peter
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Ng, G. Andre
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Schlindwein, Fernando
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Almeida, Tiago
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Chu, Gavin
eeefa5a7-0f96-43ee-bd2f-50798bc49167
Li, Xin
50870cd7-3ec3-434e-a43a-b10d50e3d5b3
Salinet, Joao
885d6515-29d0-4fec-87e9-0f56768f0bc8
Dastagir, Nawshin
44943be8-3dd1-479c-b0fe-4149f1ef2aa9
Bell, Michael
a762d32a-e6f9-452a-845d-6b139e0275e6
Vanheusden, Frederique
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Tuan, Jiun
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Stafford, Peter
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Ng, G. Andre
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Schlindwein, Fernando
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Almeida, Tiago, Chu, Gavin, Li, Xin, Salinet, Joao, Dastagir, Nawshin, Bell, Michael, Vanheusden, Frederique, Tuan, Jiun, Stafford, Peter, Ng, G. Andre and Schlindwein, Fernando (2016) Contributing factors concerning inconsistencies in persistent atrial fibrillation ablation outcomes. Computing in Cardiology, Vancouver, Canada. 11 - 14 Sep 2016.

Record type: Conference or Workshop Item (Other)

Abstract

Background: We investigated current clinical methods for complex fractionated atrial electrogram (CFAE) classification during persistent atrial fibrillation (persAF). In particular, factors that directly influence the low reproducibility of CFAE-guided ablation outcomes in persAF therapy, such as inconsistencies in automated CFAE classification performed by different systems, the co-existence of different types of atrial electrograms (AEGs), and insufficient AEG duration for CFAE detection. Methods: 797 bipolar AEGs were exported from NavX (St. Jude Medical) from 18 persAF patients undergoing pulmonary vein isolation and roof line ablation (PVI+RL). CFE-Mean, CFE-StdDev and peak-to-peak were exported from NavX, while the interval confidence level, average and shortest complex interval – as defined by CARTO (Biosense Webster) – were calculated offline using a validated MATLAB script. Sample entropy, dominant frequency and organization index were also calculated offline. Results: First, we show that CFAE classification varies for the same individual, depending on the commercial system being used. Revised thresholds were found for the indices calculated by each system to minimize the differences in automated CFAE detection performed independently by them. Second, our results show that some AEGs are affected by PVI+RL in persAF, while others remain unaffected by it. Different types of AEGs might correlate with distinct underlying persAF mechanisms. Multivariate analysis using the multiple descriptors measured from the AEGs effectively discriminated the different types of AEGs. Finally, we show that consecutive AEGs with 2.5 s resulted in different ablation target identification using the CARTO criterion, which would affect the ablation strategy and contribute to conflicting outcomes in AEGguided ablation in persAF. Our results suggest that CARTO should consider AEGs with longer duration to measure CFAEs. Conclusions: A thorough re-evaluation of the definition of CFAE is necessary in order to refine the identification of critical atrial regions responsible for the perpetuation of the arrhythmia in patients with persAF.

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Published date: 11 September 2016
Venue - Dates: Computing in Cardiology, Vancouver, Canada, 2016-09-11 - 2016-09-14
Organisations: Inst. Sound & Vibration Research

Identifiers

Local EPrints ID: 401101
URI: http://eprints.soton.ac.uk/id/eprint/401101
PURE UUID: f63a66e6-7336-4a39-a56c-b69dd82ce08b
ORCID for Frederique Vanheusden: ORCID iD orcid.org/0000-0003-2369-6189

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Date deposited: 04 Oct 2016 16:01
Last modified: 15 Mar 2024 02:38

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Contributors

Author: Tiago Almeida
Author: Gavin Chu
Author: Xin Li
Author: Joao Salinet
Author: Nawshin Dastagir
Author: Michael Bell
Author: Frederique Vanheusden ORCID iD
Author: Jiun Tuan
Author: Peter Stafford
Author: G. Andre Ng
Author: Fernando Schlindwein

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