Suppr超能文献

心房电图的频率分析确定了在两种犬类模型中房颤期间从左心房到右心房的传导途径。

Frequency analysis of atrial electrograms identifies conduction pathways from the left to the right atrium during atrial fibrillation-studies in two canine models.

作者信息

Ryu Kyungmoo, Sahadevan Jayakumar, Khrestian Celeen M, Stambler Bruce S, Waldo Albert L

机构信息

Department of Biomedical Engineering, Case Western Reserve University, 11100 Euclid Avenue, Cleveland, OH 44106, USA.

出版信息

J Cardiovasc Electrophysiol. 2009 Jun;20(6):667-74. doi: 10.1111/j.1540-8167.2008.01403.x. Epub 2009 Jan 16.

Abstract

UNLABELLED

Studies of atrial fibrillation (AF) have demonstrated that a stable rhythm of very short cycle length in the left atrium (LA) can cause fibrillatory conduction in the rest of the atria. We tested the hypothesis that fast Fourier transform (FFT) analysis of atrial electrograms (AEGs) during this AF will rapidly and reliably identify LA-to-right atrium (RA) conduction pathway(s) generated by the driver.

METHODS AND RESULTS

During induced atrial tachyarrhythmias in the canine sterile pericarditis and rapid ventricular pacing-induced congestive heart failure models, 380-404 AEGs were recorded simultaneously from epicardial electrodes on both atria. FFT analysis of AEGs during AF demonstrated a dominant frequency peak in the LA (driver), and multiple frequency peaks in parts of the LA and the most of the RA. Conduction pathways from the LA driver to the RA varied from study-to-study. They were identified by the presence of multiple frequency peaks with one of the frequency peaks at the same frequency as the driver, and traveled (1) inferior to the inferior vena cava (IVC); (2) between the superior vena cava and the right superior pulmonary vein (RSPV); (3) between the RSPV and the right inferior pulmonary vein (RIPV); (4) between the RIPV and the IVC; and (5) via Bachmann's bundle. Conduction pathways identified by FFT analysis corresponded to the conduction pathways found in classical sequence of activation mapping. Computation time for FFT analysis for each AF episode took less than 5 minutes.

CONCLUSION

FFT analysis allowed rapid and reliable detection of the LA-to-RA conduction pathways in AF generated by a stable and rapid LA driver.

摘要

未标注

心房颤动(AF)的研究表明,左心房(LA)中非常短的周期长度的稳定节律可导致心房其余部分的颤动传导。我们检验了这样一个假设,即在这种房颤期间对心房电图(AEG)进行快速傅里叶变换(FFT)分析将快速且可靠地识别由驱动因素产生的从左心房到右心房(RA)的传导通路。

方法与结果

在犬无菌性心包炎诱导的房性快速心律失常和快速心室起搏诱导的充血性心力衰竭模型中,同时从两个心房的心外膜电极记录380 - 404个AEG。房颤期间对AEG进行FFT分析显示,左心房(驱动因素)有一个主导频率峰值,左心房部分区域和大部分右心房有多个频率峰值。从左心房驱动因素到右心房的传导通路在不同研究中有所不同。它们通过多个频率峰值的存在来识别,其中一个频率峰值与驱动因素的频率相同,并走行于:(1)下腔静脉(IVC)下方;(2)上腔静脉与右上肺静脉(RSPV)之间;(3)RSPV与右下肺静脉(RIPV)之间;(4)RIPV与IVC之间;以及(5)通过Bachmann束。通过FFT分析确定的传导通路与经典激活标测序列中发现的传导通路相对应。每次房颤发作的FFT分析计算时间不到5分钟。

结论

FFT分析能够快速且可靠地检测由稳定且快速的左心房驱动因素产生的房颤中从左心房到右心房的传导通路。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验