Refined Multiscale Entropy Predicts Early Failure in Electrical Cardioversion of Atrial Fibrillation

dc.contributor.authorCirugeda Roldan, Eva María
dc.contributor.authorCalero, Sofía
dc.contributor.authorHidalgo , Víctor Manuel
dc.contributor.authorEneró, José
dc.contributor.authorRieta, José Joaquín
dc.contributor.authorAlcaraz, Raúl
dc.date.accessioned2025-08-01T07:27:46Z
dc.date.available2025-08-01T07:27:46Z
dc.date.issued2020-09-16
dc.description.abstractElectrical cardioversion (ECV) is a well-established strategy for atrial fibrillation (AF) management. Despite its high initial effectiveness, a high relapsing rate is also found. Hence, identification of patients at high risk of early AF recurrence is crucial for a rationale therapeutic strategy. For that purpose, a set of indices characterizing fibrillatory (f-) waves have been proposed, but they have not considered nonlinear dynamics present at different timescales within the cardiovascular system. This work thus explores whether a multiscale entropy (MSE) analysis of the f-waves can improve preoperative predictions of ECV outcome. Thus, two MSE approaches were considered, i.e., traditional MSE and a refined version (RMSE). Both algorithms were applied to the main f-waves component extracted from lead V1 and entropy values were computed for the first 20 time-scales. As a reference, dominant frequency (DF) and f-wave amplitude (FWA) were also computed. A total of 70 patients were analyzed, and all parameters but FWA showed statistically significant differences between those relapsing to AF and maintaining sinus rhythm during a follow-up of 4 weeks. RMSE reported the best results for the scale 19, improving predictive ability up to an 8% with respect to DAF and FWA. Consequently, investigation of nonlinear dynamics at large time-scales can provide useful insights able to improve predictions of ECV failure.
dc.identifier.citationE. M. Cirugeda, S. Calero, V. M. Hidalgo, J. Enero, J. J. Rieta and R. Alcaraz, "Refined Multiscale Entropy Predicts Early Failure in Electrical Cardioversion of Atrial Fibrillation," 2020 Computing in Cardiology, Rimini, Italy, 2020, pp. 1-4, doi: 10.22489/CinC.2020.369.
dc.identifier.doi10.22489/CinC.2020.369
dc.identifier.issn2325-887X
dc.identifier.urihttps://hdl.handle.net/10115/97357
dc.language.isoen
dc.publisherComputing in Cardiology
dc.rightsAttribution 4.0 Internationalen
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAtrial Activity
dc.subjectAtrial fribrillation
dc.subjectnonlinear analysis
dc.subjectelectrical cardioversion
dc.subjectrefined multiscale entropy
dc.subjectmultiscale entropy
dc.titleRefined Multiscale Entropy Predicts Early Failure in Electrical Cardioversion of Atrial Fibrillation
dc.typeArticle

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