An artificial intelligence-enabled Holter algorithm to identify patients with ventricular tachycardia by analysing their electrocardiogram during sinus rhythm.

IF 3.9 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
European heart journal. Digital health Pub Date : 2024-04-03 eCollection Date: 2024-07-01 DOI:10.1093/ehjdh/ztae025
Sheina Gendelman, Eran Zvuloni, Julien Oster, Mahmoud Suleiman, Raphaël Derman, Joachim A Behar
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引用次数: 0

Abstract

Aims: Ventricular tachycardia (VT) is a dangerous cardiac arrhythmia that can lead to sudden cardiac death. Early detection and management of VT is thus of high clinical importance. We hypothesize that it is possible to identify patients with VT during sinus rhythm by leveraging a continuous 24 h Holter electrocardiogram and artificial intelligence.

Methods and results: We analysed a retrospective Holter data set from the Rambam Health Care Campus, Haifa, Israel, which included 1773 Holter recordings from 1570 non-VT patients and 52 recordings from 49 VT patients. Morphological and heart rate variability features were engineered from the raw electrocardiogram signal and fed, together with demographical features, to a data-driven model for the task of classifying a patient as either VT or non-VT. The model obtained an area under the receiving operative curve of 0.76 ± 0.07. Feature importance suggested that the proportion of premature ventricular beats and beat-to-beat interval variability was discriminative of VT, while demographic features were not.

Conclusion: This original study demonstrates the feasibility of VT identification from sinus rhythm in Holter.

一种人工智能 Holter 算法,通过分析窦性心律时的心电图来识别室性心动过速患者。
目的:室性心动过速(VT)是一种危险的心律失常,可导致心脏性猝死。因此,早期发现和处理室性心动过速具有重要的临床意义。我们假设,利用连续 24 小时的 Holter 心电图和人工智能,有可能在窦性心律期间识别出 VT 患者:我们分析了以色列海法兰巴姆医疗保健中心的 Holter 回顾性数据集,其中包括 1570 名非 VT 患者的 1773 次 Holter 记录和 49 名 VT 患者的 52 次记录。从原始心电图信号中提取了形态学特征和心率变异性特征,并与人口统计学特征一起输入数据驱动模型,用于将患者分类为 VT 或非 VT。该模型的接收操作曲线下面积为 0.76 ± 0.07。特征重要性表明,室性早搏的比例和搏动间期变异性对 VT 有鉴别作用,而人口统计学特征则没有:这项原创性研究证明了从 Holter 中的窦性心律识别 VT 的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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