一项初步研究，考察用于植入式设备中节律判别的多项式模型心室电击电图的性能。
A pilot study examining the performance of polynomial-modeled ventricular shock electrograms for rhythm discrimination in implantable devices.
作者信息
Williams Jeffrey L, Shusterman Vladimir, Saba Samir
机构信息
Division of Cardiac Electrophysiology, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA.
出版信息
Pacing Clin Electrophysiol. 2006 Sep;29(9):930-9. doi: 10.1111/j.1540-8159.2006.00465.x.
BACKGROUND
Inappropriate shocks continue to be a problem for patients with implantable defibrillators (ICD). We evaluated the performance of polynomial-modeled ventricular electrograms (EGM) to discriminate between supraventricular tachycardia (SVT) and ventricular tachycardia (VT).
METHODS
Seven sets of EGM from patients having both SVT and VT documented during a single ICD interrogation were included. The cardiac cycle was analyzed off-line in two parts, QR and RQ segments, which were modeled separately using third-order and sixth-order polynomial equations, respectively. These segments were then analyzed to determine which polynomial coefficients were most significant for rhythm discrimination.
RESULTS
When analyzing the QR segment during arrhythmia, there were statistically significant (P<0.05) correlations in 4 of 4 (100%) of the QR coefficients when comparing normal sinus rhythm (NSR) to SVT and 2 of 4 (50%) when comparing NSR to VT or SVT to VT. When analyzing the RQ segment during arrhythmia, there were statistically significant (P<0.05) correlations in 4 of 7 (57%) of the RQ coefficients when comparing NSR to SVT, 5 of 7 (71%) when comparing NSR to VT, and 3 of 7 (43%) when comparing SVT to VT. Using a cutoff value of 50% change from NSR, the ratio of first-order to zero-order QR coefficient was able to completely separate VT from SVT (P=0.03) in this series of patients.
CONCLUSION
Our data demonstrate the feasibility of simple polynomial equations that reproduce the depolarization and repolarization phases of human ventricular shock EGM. The ratio of first-order to zero-order QR coefficient was able to reliably discriminate between SVT and VT while reducing the polynomial model to a first-order system. The results of this pilot trial may serve as the basis for a larger prospective trial implementing a discrimination algorithm for use in low computational power implantable devices.
背景
对于植入式心脏除颤器（ICD）患者而言，不适当的电击仍是一个问题。我们评估了多项式模型化心室电图（EGM）在鉴别室上性心动过速（SVT）和室性心动过速（VT）方面的性能。
方法
纳入了7组来自在单次ICD问询期间记录到同时患有SVT和VT的患者的EGM。心动周期离线分析为两个部分，即QR段和RQ段，分别使用三阶和六阶多项式方程进行建模。然后对这些段进行分析，以确定哪些多项式系数对心律鉴别最为重要。
结果
在分析心律失常期间的QR段时，将正常窦性心律（NSR）与SVT进行比较时，4个QR系数中有4个（100%）存在统计学显著相关性（P<0.05）；将NSR与VT或SVT与VT进行比较时，4个QR系数中有2个（50%）存在统计学显著相关性。在分析心律失常期间的RQ段时，将NSR与SVT进行比较时，7个RQ系数中有4个（57%）存在统计学显著相关性（P<0.05）；将NSR与VT进行比较时，7个RQ系数中有5个（71%）存在统计学显著相关性；将SVT与VT进行比较时，7个RQ系数中有3个（43%）存在统计学显著相关性。在本系列患者中，使用与NSR相比变化50%的截止值，一阶与零阶QR系数之比能够将VT与SVT完全区分开（P=0.03）。
结论
我们的数据证明了简单多项式方程的可行性，该方程可再现人类心室电击EGM的去极化和复极化阶段。一阶与零阶QR系数之比能够可靠地鉴别SVT和VT，同时将多项式模型简化为一阶系统。该初步试验的结果可为开展更大规模前瞻性试验奠定基础，该前瞻性试验将实施一种用于低计算能力植入设备的鉴别算法。
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