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dc.contributor.author | Cirugeda, Eva M. | es_ES |
dc.contributor.author | Calero, Sofia | es_ES |
dc.contributor.author | Quesada, Aurelio | es_ES |
dc.contributor.author | Hidalgo, Victor M. | es_ES |
dc.contributor.author | Rieta, J J | es_ES |
dc.contributor.author | Alcaraz, Raul | es_ES |
dc.date.accessioned | 2021-12-20T08:38:58Z | |
dc.date.available | 2021-12-20T08:38:58Z | |
dc.date.issued | 2020-09-16 | es_ES |
dc.identifier.issn | 2325-887X | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/178544 | |
dc.description.abstract | [EN] Electrical cardioversion (ECV) is an effective and low-cost rhythm control strategy for persistent atrial fibrillation (AF). Because of its limited mid- and long-term success rates, prediction of early failure could avoid patients with reduced chance to maintain sinus rhythm (SR). To this end and due to its proximity to the right atrium, several indices characterizing atrial activity have been proposed based on lead V1. However, information from other leads has been discarded to date. Hence, this work studies how effective some common indices computed over the whole set of 12 standard ECG leads are in predicting ECV outcome. Precisely, amplitude, dominant frequency, and sample entropy were computed from the fibrillatory (f-) waves extracted for each one of 12 standard leads acquired before ECV from 58 patients in persistent AF. The classification between the patients who relapsed to AF and maintained sinus rhythm after a follow-up of 4 weeks achieved by these parameters was better from limb lead II than from V1, thus reporting improvements about 6 and 12%. As a consequence, characterization of f-waves from the more accessible limb lead II has proven to be the best choice to improve AF ECV outcome prediction from the ECG. | es_ES |
dc.description.sponsorship | This research was funded by the projects DPI2017-83952C3 from MINECO/AEI/FEDER EU, SBPLY/17/180501/000411 from "Junta de Castilla La Mancha" and AICO/2019/036 from "Generalitat Valenciana". | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | IEEE | es_ES |
dc.relation.ispartof | CinC 2020. Computing in Cardiology, vol. 47 | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.subject.classification | TECNOLOGIA ELECTRONICA | es_ES |
dc.title | Limb Versus Precordial ECG Leads as Improved Predictors of Electrical Cardioversion Outcome in Persistent Atrial Fibrillation | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.22489/CinC.2020.373 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2017-83952-C3-1-R/ES/ESTUDIO MULTICENTRICO PARA LA EVALUACION DEL SUSTRATO ARRITMOGENICO EN PACIENTES CON FIBRILACION AURICULAR. APLICACION A LA ABLACION POR CATETER/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/JCCM//SBPLY%2F17%2F180501%2F000411//Caracterización del sustrato auricular mediante análisis de señal como herramienta de asistencia procedimental en ablación por catéter de fibrilación auricular/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement///AICO%2F2019%2F036//METODOS DE DIAGNOSTICO Y TERAPIA PERSONALIZADA EN ABLACION POR CATETER DE ARRITMIAS CARDIACAS/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario Mixto Tecnológico de Informática - Institut Universitari Mixt Tecnològic d'Informàtica | es_ES |
dc.description.bibliographicCitation | Cirugeda, EM.; Calero, S.; Quesada, A.; Hidalgo, VM.; Rieta, JJ.; Alcaraz, R. (2020). Limb Versus Precordial ECG Leads as Improved Predictors of Electrical Cardioversion Outcome in Persistent Atrial Fibrillation. IEEE. 1-4. https://doi.org/10.22489/CinC.2020.373 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.conferencename | 47th Computing in Cardiology Conference (CinC 2020) | es_ES |
dc.relation.conferencedate | Septiembre 13-16,2020 | es_ES |
dc.relation.conferenceplace | Rimini, Italia | es_ES |
dc.relation.publisherversion | https://doi.org/10.22489/CinC.2020.373 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 4 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.relation.pasarela | S\433028 | es_ES |
dc.contributor.funder | Junta de Comunidades de Castilla-La Mancha | es_ES |