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定量体表等面积映射在预测室性快速性心律失常中的应用。

The utility of quantitative body surface isoarea mapping for predicting ventricular tachyarrhythmias.

作者信息

Goldner B G, Horwitz L, Kohn N, Lesser M, Ehrlich J, Cohen T J, Jadonath R

机构信息

Department of Medicine, North Shore University Hospital-New York University School of Medicine, Manhasset, NY 11030, USA.

出版信息

Pacing Clin Electrophysiol. 1999 Mar;22(3):453-61. doi: 10.1111/j.1540-8159.1999.tb00473.x.

Abstract

Noninvasive techniques, such as the signal averaged ECG, have been used to assess risk of ventricular tachyarrhythmias (VT). However, these methods produce false positive and negative results. The purpose of this study was to develop body surface map algorithms which would enhance prediction of susceptibility to VT. Fifty-three patients referred for programmed electrical stimulation were enrolled in this study. All patients underwent signal averaged ECG, body surface map, programmed electrical stimulation. Group I patients had no sustained inducible VT and group II patients had either inducible sustained VT at electrophysiology study or previously documented spontaneous, sustained VT. For body surface map analysis, the difference between extrema on isoarea maps was calculated and defined as the gradient range. An abnormal body surface map was defined as a QRST gradient range < or = 109 mv.ms. The mean QRST gradient range in group II was significantly < that in group I (P < 0.05). By logistic regression analysis, the presence of coronary artery disease, a QRST gradient range < or = 109 mv.ms, an EF < 40% and a signal averaged ECG QRS duration > 114 ms predicted VT. The sensitivity, specificity, positive and negative predictive values for predicting VT susceptibility of an algorithm which combines the signal averaged ECG QRS duration and the QRST gradients were 0.93, 0.76, 0.79, and 0.91, respectively, while those for the signal averaged ECG alone were 0.52, 0.69, 0.63, and 0.59 for VT susceptibility. A combined body surface map-signal averaged ECG algorithm was more sensitive in detecting susceptibility to VT than the signal averaged ECG alone.

摘要

诸如信号平均心电图等非侵入性技术已被用于评估室性快速心律失常(VT)的风险。然而,这些方法会产生假阳性和假阴性结果。本研究的目的是开发体表标测算法,以增强对VT易感性的预测。53例因进行程控电刺激而转诊的患者纳入本研究。所有患者均接受了信号平均心电图、体表标测和程控电刺激。I组患者无持续性可诱发性VT,II组患者在电生理研究中存在可诱发性持续性VT或既往有记录的自发性持续性VT。对于体表标测分析,计算等面积图上极值之间的差异并将其定义为梯度范围。异常体表标测定义为QRST梯度范围≤109 mv.ms。II组的平均QRST梯度范围显著小于I组(P<0.05)。通过逻辑回归分析,冠心病的存在、QRST梯度范围≤109 mv.ms、射血分数<40%以及信号平均心电图QRS时限>114 ms可预测VT。结合信号平均心电图QRS时限和QRST梯度的算法预测VT易感性的敏感性、特异性、阳性预测值和阴性预测值分别为0.93、0.76、0.79和0.91,而单独使用信号平均心电图预测VT易感性的上述指标分别为0.52、0.69、0.63和0.59。体表标测与信号平均心电图相结合的算法在检测VT易感性方面比单独使用信号平均心电图更敏感。

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