Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation

Saiz Vivó, Javier ; Corino, Valentina D. A. ; Martín Yebra, Alba (Universidad de Zaragoza) ; Mainardi, Luca T. ; Hatala, Robert ; Sörnmo, Leif

Resumen: Methods for characterization of atrial fibrillation (AF) episode patterns have been introduced without establishing clinical significance. This study investigates, for the first time, whether post-ablation recurrence of AF can be predicted by evaluating episode patterns. The dataset comprises of 54 patients (age 56 ± 11 years; 67% men), with an implantable cardiac monitor, before undergoing the first AF catheter ablation. Two parameters of the alternating bivariate Hawkes model were used to characterize the pattern: AF dominance during the monitoring period (log(mu)) and temporal aggregation of episodes (beta1). Moreover, AF burden and AF density, a parameter characterizing aggregation of AF burden, were studied. The four parameters were computed from an average of 29 AF episodes before ablation. The risk of AF recurrence after catheter ablation using the Hawkes parameters log(mu) and beta1, AF burden, and AF density was evaluated. While the combination of AF burden and AF density is related to a non-significant hazard ratio, the combination of log(mu) and beta1 is related to a hazard ratio of 1.95 (1.03–3.70; p < 0.05). The Hawkes parameters showed increased risk of AF recurrence within 1 year after the procedure for patients with high AF dominance and high episode aggregation and may be used for pre-ablation risk assessment.

Idioma: Inglés

DOI: 10.1007/s11517-022-02713-x

Año: 2023

Publicado en: MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING 61, 2 (2023), 317-327
ISSN: 0140-0118

Factor impacto JCR: 2.6 (2023)

Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 80 / 169 = 0.473 (2023) - Q2 - T2
Categ. JCR: MATHEMATICAL & COMPUTATIONAL BIOLOGY rank: 20 / 65 = 0.308 (2023) - Q2 - T1
Categ. JCR: MEDICAL INFORMATICS rank: 26 / 44 = 0.591 (2023) - Q3 - T2
Categ. JCR: ENGINEERING, BIOMEDICAL rank: 71 / 122 = 0.582 (2023) - Q3 - T2

Factor impacto CITESCORE: 6.0 - Biomedical Engineering (Q2) - Computer Science Applications (Q2)

Factor impacto SCIMAGO: 0.641 - Computer Science Applications (Q2) - Biomedical Engineering (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group
Financiación: info:eu-repo/grantAgreement/EC/H2020/766082/EU/MultidisciplinarY training network for ATrial fibRillation monItoring, treAtment and progression/MY-ATRIA
Financiación: info:eu-repo/grantAgreement/ES/MICINN-FEDER/PID2019-104881RB-I00
Financiación: info:eu-repo/grantAgreement/ES/MICINN/FJC-2018-037369-I

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)