Quantification of Ventricular Repolarization Variation for Sudden Cardiac Death Risk Stratification in Atrial Fibrillation

Martín Yebra, Alba (Universidad de Zaragoza) ; Laguna, Pablo (Universidad de Zaragoza) ; Cygankiewicz, Iwona ; Bayés-de-Luna, Antoni ; Caiani, Enrico G. ; Martínez, Juan Pablo (Universidad de Zaragoza)

Resumen: Objective: Atrial fibrillation (AF) rhythm gives rise to an irregular response in ventricular activity, preventing the use of standard ECG-derived risk markers based on ventricular repolarization heterogeneity under this particular condition. In this study we proposed new indices to quantify repolarization variations in AF patients, assessing their stratification performance in a chronic heart failure (CHF) population with AF. Methods: We developed a method based on a selective bin averaging technique. Consecutive beats preceded by a similar RR interval were selected, from which the average variation within the ST-T complex for each RR range was computed.We proposed two sets of indices: (i) the 2-beat index of ventricular repolarization variation, (I_V2), computed from pairs of stable consecutive beats; and (ii) the 3-beat indices of ventricular repolarization variation, computed in triplets of stable consecutive beats (I_V3). Results: These indices showed a significant association with sudden cardiac death (SCD) outcome in the study population. In addition, risk assessment based on the combination of the proposed indices improved stratification performance compared to their individual potential. Conclusion: Patients with enhanced ventricular repolarization variation computed in terms of the proposed indices were successfully associated to a higher SCD incidence in our study population, evidencing their prognostic value. Significance: using a simple ambulatory ECG recording, it is possible to stratify AF patients at risk of SCD, which may help cardiologists in adopting most effective therapeutic strategies, with a positive impact in both the patient and healthcare systems.

Idioma: Inglés

DOI: 10.1109/JBHI.2018.2851299

Año: 2018

Publicado en: IEEE journal of biomedical and health informatics 23, 3 (2018), 1049 - 1057
ISSN: 2168-2194

Factor impacto JCR: 4.217 (2018)

Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 19 / 155 = 0.123 (2018) - Q1 - T1
Categ. JCR: MATHEMATICAL & COMPUTATIONAL BIOLOGY rank: 5 / 59 = 0.085 (2018) - Q1 - T1
Categ. JCR: MEDICAL INFORMATICS rank: 4 / 26 = 0.154 (2018) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 16 / 106 = 0.151 (2018) - Q1 - T1

Factor impacto SCIMAGO: 1.122 - Biotechnology (Q1) - Health Information Management (Q1) - Electrical and Electronic Engineering (Q1) - Computer Science Applications (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA-FEDER/T39-17R-BSICoS
Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2016-75458-R

Tipo y forma: Artículo (PrePrint)

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