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用于心房颤动导管消融长期预后预测的心电图频谱特征

Electrocardiographic Spectral Features for Long-Term Outcome Prognosis of Atrial Fibrillation Catheter Ablation.

作者信息

Alcaraz Raúl, Hornero Fernando, Rieta José J

机构信息

Research Group in Electronic, Biomedical and Telecommunications Engineering, University of Castilla-La Mancha, Cuenca, Spain.

Escuela Politécnica, Campus Universitario, 16071, Cuenca, Spain.

出版信息

Ann Biomed Eng. 2016 Nov;44(11):3307-3318. doi: 10.1007/s10439-016-1641-3. Epub 2016 May 24.

Abstract

Atrial fibrillation (AF) is the most common arrhythmia in routine clinical practice. Despite many years of research, its mechanisms still are not well understood, thus reducing the effectiveness of AF treatments. Nowadays, pulmonary vein isolation by catheter ablation is the treatment of choice for AF resistant either to pharmacological or electrical cardioversion. However, given that long-term recurrences are common, an appropriate patient selection before the procedure is of paramount relevance in the improvement of AF catheter ablation outcome. The present work studies how several spectral features of the atrial activity (AA) from a single lead of the surface electrocardiogram (ECG) can become potential pre-ablation predictors of long-term (>2 months) sinus rhythm maintenance. Among all the analyzed spectral features, results indicated that the most significant single predictor of paroxysmal AF ablation treatment outcome was related to the amplitude of the first harmonic of the dominant frequency, providing sensitivity (Se), specificity (Sp) and accuracy (Ac) values of 90%, 42.86 and 77.78%, respectively. On the other hand, the AA harmonic structure was the most significant single predictor for persistent AF, with Se, Sp and Ac values of 100%, 54.55 and 77.27%, respectively. A logistic regression analysis, mainly based on spectral amplitudes as well as on the harmonic structure of the AA, provided a higher predictive ability both for paroxysmal AF (Se = 100%, Sp = 57.14% and Ac = 88.89%) and persistent AF (Se = 90.91%, Sp = 72.73 and Ac = 81.82%). In conclusion, the study of key AA spectral features from the surface ECG can provide a significant preoperative prognosis of AF catheter ablation outcome at long-term follow-up.

摘要

心房颤动(AF)是常规临床实践中最常见的心律失常。尽管经过多年研究,其机制仍未完全清楚,这降低了房颤治疗的效果。如今,通过导管消融进行肺静脉隔离是对药物或电复律无效的房颤的首选治疗方法。然而,鉴于长期复发很常见,在手术前进行适当的患者选择对于改善房颤导管消融结果至关重要。本研究探讨了来自体表心电图(ECG)单导联的心房活动(AA)的几个频谱特征如何成为长期(>2个月)窦性心律维持的潜在消融前预测指标。在所有分析的频谱特征中,结果表明,阵发性房颤消融治疗结果最显著的单一预测指标与主导频率的一次谐波幅度有关,其敏感性(Se)、特异性(Sp)和准确性(Ac)值分别为90%、42.86%和77.78%。另一方面,AA谐波结构是持续性房颤最显著的单一预测指标,Se、Sp和Ac值分别为100%、54.55%和77.27%。主要基于频谱幅度以及AA谐波结构的逻辑回归分析,对阵发性房颤(Se = 100%,Sp = 57.14%,Ac = 88.89%)和持续性房颤(Se = 90.91%,Sp = 72.73%,Ac = 81.82%)均具有更高的预测能力。总之,对体表心电图关键AA频谱特征的研究可以为房颤导管消融长期随访结果提供重要的术前预后评估。

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