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Estimation du risque de mort subite par arrêt cardiaque a l'aide de méthodes d'apprentissage artificiel

Abstract : Implantable cardioverter defibrillators (ICD) have been prescribed for prophylaxis since the early 2000?s, for patients at high risk of SCD. Unfortunately, most implantations to date appear unnecessary. This result raises an important issue because of the perioperative and postoperative risks. Thus, it is important to improve the selection of the candidates to ICD implantation in primary prevention. Risk stratification for SCD based on Holter recordings has been extensively performed in the past, without resulting in a significant improvement of the selection of candidates to ICD implantation. The present report describes a nonlinear multivariate analysis of Holter recording indices. We computed all the descriptors available in the Holter recordings present in our database. The latter consisted of labelled Holter recordings of patients equipped with an ICD in primary prevention, a fraction of these patients received at least one appropriate therapy from their ICD during a 6-month follow-up. Based on physiological knowledge on arrhythmogenesis, feature selection was performed, and an innovative procedure of classifier design and evaluation was proposed. The classifier is intended to discriminate patients who are really at risk of sudden death from patients for whom ICD implantation does not seem necessary. In addition, we designed an ad hoc classifier that capitalizes on prior knowledge on arrhythmogenesis. We conclude that improving prophylactic ICD-implantation candidate selection by automatic classification from Holter recording features may be possible. Nevertheless, that statement should be supported by the study of a more extensive and appropriate database.
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Submitted on : Wednesday, July 23, 2014 - 9:15:00 AM
Last modification on : Sunday, June 26, 2022 - 5:47:22 PM
Long-term archiving on: : Tuesday, April 11, 2017 - 4:12:57 PM


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  • HAL Id : pastel-00939082, version 2


Charles-Henri Cappelaere. Estimation du risque de mort subite par arrêt cardiaque a l'aide de méthodes d'apprentissage artificiel. Electronique. Université Pierre et Marie Curie - Paris VI, 2014. Français. ⟨NNT : 2014PA066014⟩. ⟨pastel-00939082v2⟩



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