Automatic SVM classification of sudden cardiac death and pump failure death from autonomic and repolarization ECG markers
Resumen: Background
Considering the rates of sudden cardiac death (SCD) and pump failure death (PFD) in chronic heart failure (CHF) patients and the cost-effectiveness of their preventing treatments, identification of CHF patients at risk is an important challenge. In this work, we studied the prognostic performance of the combination of an index potentially related to dispersion of repolarization restitution (Δα), an index quantifying T-wave alternans (IAA) and the slope of heart rate turbulence (TS) for classification of SCD and PFD.
Methods
Holter ECG recordings of 597 CHF patients with sinus rhythm enrolled in the MUSIC study were analyzed and Δα, IAA and TS were obtained. A strategy was implemented using support vector machines (SVM) to classify patients in three groups: SCD victims, PFD victims and other patients (the latter including survivors and victims of non-cardiac causes). Cross-validation was used to evaluate the performance of the implemented classifier.
Results
Δα and IAA, dichotomized at 0.035 (dimensionless) and 3.73 μV, respectively, were the ECG markers most strongly associated with SCD, while TS, dichotomized at 2.5 ms/RR, was the index most strongly related to PFD. When separating SCD victims from the rest of patients, the individual marker with best performance was Δα ≥ 0.035, which, for a fixed specificity (Sp) of 90%, showed a sensitivity (Se) value of 10%, while the combination of Δα and IAA increased Se to 18%. For separation of PFD victims from the rest of patients, the best individual marker was TS ≤ 2.5 ms/RR, which, for Sp = 90%, showed a Se of 26%, this value being lower than Se = 34%, produced by the combination of Δα and TS. Furthermore, when performing SVM classification into the three reported groups, the optimal combination of risk markers led to a maximum Sp of 79% (Se = 18%) for SCD and Sp of 81% (Se = 14%) for PFD.
Conclusions
The results shown in this work suggest that it is possible to efficiently discriminate SCD and PFD in a population of CHF patients using ECG-derived risk markers like Δα, TS and IAA.

Idioma: Inglés
DOI: 10.1016/j.jelectrocard.2015.04.002
Año: 2015
Publicado en: JOURNAL OF ELECTROCARDIOLOGY 48, 4 (2015), 551-557
ISSN: 0022-0736

Originalmente disponible en: Texto completo de la revista

Factor impacto JCR: 1.29 (2015)
Categ. JCR: CARDIAC & CARDIOVASCULAR SYSTEMS rank: 93 / 124 = 0.75 (2015) - Q3 - T3
Factor impacto SCIMAGO: 0.559 - Cardiology and Cardiovascular Medicine (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA/FSE
Financiación: info:eu-repo/grantAgreement/ES/DGA/Grupo Consolidado BSICoS
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TEC2013-42140-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2013-41998-R
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)

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