Shome Shibaji, Li Dan, Thompson Julie, McCabe Aaron
Research and Technology, Boston Scientific Corporation, St. Paul, MN 55112, USA.
J Electrocardiol. 2010 Nov-Dec;43(6):503-8. doi: 10.1016/j.jelectrocard.2010.06.009. Epub 2010 Aug 17.
Implantable cardioverter-defibrillators (ICDs) have been shown in various clinical trials to prevent mortality from sudden cardiac death due to unstable rhythms or ventricular fibrillation. Modern ICDs use sophisticated algorithms to not only deliver therapy on the detection of a malignant rhythm but also reduce the incidence of inappropriate shocks through rhythm discrimination. Current algorithms for detection of malignant rhythms use sophisticated techniques such as real-time processing and analysis of electrograms from a transvenous lead system. The Rhythm ID feature in Boston Scientific ICDs is an example of one such algorithm used for rhythm discrimination. Rhythm ID uses the vector timing and correlation algorithm, which incorporates both timing as well as morphology information for supraventricular tachycardia discrimination. Clinical trials demonstrated high sensitivity and specificity of this feature in discriminating between ventricular tachycardia and supraventricular tachycardia (results published previously). On detection of the unknown rhythm (when the ventricular tachycardia rate detection criteria is met), the vector timing and correlation algorithm compares the unknown rhythm beat-by-beat to a stored template of normal sinus rhythm. The feature correlation coefficient computed over more than 8 points in the time-aligned signals is used for the comparison. The specific discrimination procedure of Rhythm ID depends on the mode (VR or DR) and on whether the test rhythm is an initial detected rhythm or a postshock rhythm. The normal sinus rhythm template against which the suspected rhythm is compared can be periodically updated. This article will cover some of the key aspects of the Rhythm ID feature's decision-making process and the algorithm for template update. The results of previously published clinical studies involving the algorithm's performance also will be reviewed.
在各种临床试验中已表明，植入式心脏复律除颤器（ICD）可预防因不稳定心律或室颤导致的心脏性猝死。现代ICD使用复杂的算法，不仅能在检测到恶性心律时提供治疗，还能通过心律鉴别降低不适当电击的发生率。当前用于检测恶性心律的算法采用复杂技术，如对经静脉导联系统的心电信号进行实时处理和分析。波士顿科学公司ICD中的心律识别（Rhythm ID）功能就是用于心律鉴别的此类算法之一。心律识别使用向量定时和相关算法，该算法结合了定时以及形态学信息来鉴别室上性心动过速。临床试验表明，该功能在鉴别室性心动过速和室上性心动过速方面具有高灵敏度和特异性（此前已发表结果）。在检测到未知心律（当满足室性心动过速速率检测标准时），向量定时和相关算法会逐搏将未知心律与存储的正常窦性心律模板进行比较。在时间对齐信号中超过8个点计算得到的特征相关系数用于该比较。心律识别的具体鉴别程序取决于模式（VR或DR）以及测试心律是初始检测到的心律还是电击后心律。用于与疑似心律进行比较的正常窦性心律模板可以定期更新。本文将涵盖心律识别功能决策过程和模板更新算法的一些关键方面。还将回顾先前发表的涉及该算法性能的临床研究结果。
