一种新的诊断工具,可以通过信号指纹识别来识别心房内分心异步
Lu Zhang1, Mathijs S van Schie1, Paul Knops1
1Department of Cardiology, Erasmus Medical Center, Rotterdam, the Netherlands.
概括
在心房的患者中,可以使用电图 (EGM) 的特征识别电动内皮心异步 (EEA). 一个新的异步指纹评分 (AFS) 准确地估计了EEA度,可能表明与AF相关的基板.
科学领域:
- 电子生理学 电子生理学
- 心脏节律失常症 心脏节律失常症
- 医疗器械技术 医疗器械技术
背景情况:
- 持续性心房 (AF) 与在鼻节律 (SR) 期间增加的电内皮心异步 (EEA) 有关.
- 之前的研究表明,内心和/或上心表面的单极电图 (EGM) 形态是EEA的指标.
研究的目的:
- 开发一种用于估计EEA程度的新方法.
- 为了利用内心和/或上心记录的单极EGM特征进行EEA评估.
主要方法:
- 在SR期间,同时对86名患者进行内分外皮心映射.
- 对单极电压,低电压区域 (LVAs),潜在类型 (SP,SDP,LDP,FP) 和分离持续时间 (FD) 的分析.
- 使用量化EGM特征构建异步指纹分数 (AFS).
主要成果:
- 欧洲经济区的单极电压较低,LDP/FP较多,DP/FP持续时间较长.
- 患有AF的患者在欧洲经济区表现出较低的电位电压和改变的电位类型.
- 综合EE-AFS显示了EEA度的最高预测值 (AUC:0.913),单独表现优于endo和epi-AFS.
结论:
- EGM特征有效地识别了EEA区域.
- AFS作为一种新型诊断工具,用于准确估计EEA度.
- 这些发现表明EGM特征可能表明AF相关的节律失常基质.
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