一种后处理算法的发展,以区分由植入式心律转复除颤器检测到的室性心动过速

B. Gunderson, A.S. Patel, M.L. Brown, C. Swerdlow
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引用次数: 1

摘要

植入式心律转复除颤器(ICD)通过心房(A)和心室(V)心电图(EGMs)检测室性心动过速/颤动(VT/VF)。ICD算法将VT/VF与室上性心动过速(svt)区分开来,但将某些svt错误地分类为VT/VF。临床医生审查检测到的发作,以确定真正的SVT发作,并指导适当的临床行动。开发了一种后处理专家系统算法,对检测到的心动过速进行分类并存储在ICD存储器中。该算法被设计用于用V EGM和/或A/ V事件的时序诊断节律。不符合标准的节奏被归类为未知。该算法使用469集的数据集进行了测试。该算法正确分类了80%的剧集,准确率达到99%。这种准确性可能足以使医生复查可能只需要对未知的发作。
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Development of a post-processing algorithm to classify rhythms detected as ventricular tachyarrhythmias by Implantable Cardioverter Defibrillators
Implantable Cardioverter-Defibrillators (ICD) detect ventricular tachycardia /fibrillation (VT/VF) using atrial (A) and ventricular (V) electrograms (EGMs). ICD algorithms discriminate VT/VF from supraventricular tachycardias (SVTs), but misclassify some SVTs as VT/VF. Clinicians review detected episodes to identify true SVT episodes and guide appropriate clinical action. A post-processing, expert-system algorithm was developed to classify tachyarrhythmias detected and stored in ICD memory. The algorithm was designed to diagnose rhythms with V EGM and/or timing of A/ V events. Rhythms that did not fulfill the criteria were classified as Unknown. The algorithm was tested using a dataset of 469 episodes. The algorithm correctly classified 80% of the episodes with 99% accuracy. This accuracy may be sufficient that physician review may be required only for Unknown episodes.
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