Theuns Dominic A M J, Rivero-Ayerza Maximo, Goedhart Dick M, van der Perk Ronald, Jordaens Luc J
Department of Cardiology, Erasmus MC, Rotterdam, The Netherlands.
Heart Rhythm. 2006 Nov;3(11):1332-8. doi: 10.1016/j.hrthm.2006.06.034. Epub 2006 Jul 8.
To reduce inappropriate therapy from implantable cardioverter-defibrillators (ICDs), electrogram morphology discrimination has been developed to improve arrhythmia discrimination without compromising device safety.
The purpose of this study was to determine the accuracy of the morphology discrimination algorithm for detecting ventricular tachycardia (VT).
Stored electrograms of 795 tachyarrhythmias from 106 patients with a St. Jude Medical ICD (51 single-chamber and 55 dual-chamber) were analyzed by the investigators. The data were analyzed for morphology discrimination alone, sudden onset and stability, and morphology discrimination in combination with sudden onset and stability. Data were corrected for multiple episodes within a patient with the generalized estimating equation method.
Using the nominal template match of 60%, morphology discrimination alone provided sensitivity and specificity of 78% and 95% for single-chamber ICDs and 63% and 92% for dual-chamber ICDs, respectively. Based on the receiver operator characteristic curve, the optimal-match percent threshold was 80% to 85% but at the expense of specificity. Morphology discrimination combined with sudden onset and stability increased sensitivity to 98% with specificity of 86% in single-chamber devices. In dual-chamber devices, the loss in sensitivity is compensated by rate branch analysis, yielding a sensitivity of 98%.
Arrhythmia discrimination based on electrogram morphology has the potential to reject atrial tachyarrhythmias. However, there is a risk for underdetection of ventricular tachyarrhythmias if arrhythmia discrimination is primarily based on morphology. To guarantee patient safety in single-chamber devices, the morphology discrimination algorithm must be programmed in combination with established detection algorithms. In dual-chamber devices, loss of sensitivity is compensated by the V > A rate branch.
为减少植入式心脏复律除颤器(ICD)的不适当治疗,已开发出心电图形态辨别技术,以在不影响设备安全性的情况下改善心律失常辨别能力。
本研究旨在确定用于检测室性心动过速(VT)的形态辨别算法的准确性。
研究人员分析了106例使用圣犹达医疗ICD(51例单腔和55例双腔)患者的795次快速心律失常的存储心电图。对数据单独进行形态辨别分析、突发和稳定性分析,以及结合突发和稳定性进行形态辨别分析。采用广义估计方程法对同一患者的多次发作数据进行校正。
使用60%的标称模板匹配,单独的形态辨别对单腔ICD的敏感性和特异性分别为78%和95%,对双腔ICD分别为63%和92%。根据受试者工作特征曲线,最佳匹配百分比阈值为8至85%,但会牺牲特异性。形态辨别与突发和稳定性相结合,单腔设备的敏感性提高到98%,特异性为86%。在双腔设备中,通过速率分支分析补偿了敏感性的损失,敏感性达到98%。
基于心电图形态的心律失常辨别有可能排除房性快速心律失常。然而,如果心律失常辨别主要基于形态,则存在室性快速心律失常检测不足的风险。为确保单腔设备患者的安全,形态辨别算法必须与既定的检测算法结合编程。在双腔设备中,V > A速率分支补偿了敏感性的损失。