Higher reproducibility of phase derived metrics from electrocardiographic imaging during atrial fibrillation in patients remaining in sinus rhythm after pulmonary vein isolation


Por: Molero, R, Torro, J, Alzamora, N, Climent, A and Guillem, M

Publicada: 1 dic 2021 Ahead of Print: 1 oct 2021
Resumen:
Background: Electrocardiographic imaging (ECGI) allows evaluating the complexity of the reentrant activity of atrial fibrillation (AF) patients. In this study, we evaluated the ability of ECGI metrics to predict the success of pulmonary vein isolation (PVI) to treat AF. Methods: ECGI of 24 AF patients (6 males, 13 paroxysmal, 61.8 +/- 14 years) was recorded prior to PVI. Patients were distributed into two groups based on their PVI outcome 6 months after ablation (sinus vs. arrhythmia recurrence). Metrics derived from phase analysis of ECGI signals were computed for two different temporal segments before ablation. Correlation analysis and variability over time were studied between the two recorded segments and were compared between patient groups. Results: Temporal variability of both rotor duration and spatial entropy of the rotor histogram presented statistical differences between groups with different PVI outcome (p < 0.05). The reproducibility of reentrant metrics was higher (R-2 > 0.8) in patients with good outcome rather than arrhythmia recurrence patients (R-2 < 0.62). Prediction of PVI success based on ECGI temporal variability metrics allows for an increased specificity over the classification into paroxysmal or persistent (0.85 vs. 0.64). Conclusions: Patients with favorable PVI outcome present ECGI metrics more reproducible over time than patients with AF recurrence. These results suggest that ECGI derived metrics may allow selecting which patients would benefit from ablation therapies.

Filiaciones:
Molero, R:
 Univ Politecn Valencia, ITACA Inst, Valencia, Spain

:
 Univ Politecn Valencia, Dept Appl Stat & Operat Res & Qual, Valencia, Spain

Alzamora, N:
 Univ Politecn Valencia, Dept Appl Stat & Operat Res & Qual, Valencia, Spain

Climent, A:
 Univ Politecn Valencia, ITACA Inst, Valencia, Spain

Guillem, M:
 Univ Politecn Valencia, ITACA Inst, Valencia, Spain
ISSN: 00104825





COMPUTERS IN BIOLOGY AND MEDICINE
Editorial
Elsevier Ltd., THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, Reino Unido
Tipo de documento: Article
Volumen: 139 Número:
Páginas:
WOS Id: 000710567800004
ID de PubMed: 34688171
imagen Green Published

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