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首页> 外文期刊>Journal of cardiovascular electrophysiology >Clustering of RR Intervals Predicts Effective Electrical Cardioversion for Atrial Fibrillation.
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Clustering of RR Intervals Predicts Effective Electrical Cardioversion for Atrial Fibrillation.

机译:RR间隔的聚类预测心房颤动的有效电复律。

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Electrical Cardioversion for Atrial Fibrillation. Introduction: Atrial fibrillation (AF) is characterized by an irregularly irregular ("random") heart beat. However, controversy exists whether the ventricular rhythm in AF is truly random. We investigated randomness by constructing three-dimensional RR interval plots (3D plots), allowing identification of clustering cardioversion (ECV) would be more effective in AF patients with clustering, because clustering might reflect a higher degree of organization of atrial fibrillatory activity. Methods and Results: The study group consisted of 66 patients (44 men and 22 women; mean age 68 +/- 11 years,) who were referred for ECV because of persistent AF. Twenty-four-hour Holter recordings were used to construct 3D plots by plotting each RR interval (x axis) against the previous RR interval (y axis) and the number of occurrences of each of these x,y combinations (z axis). A clustering index was calculated as the percentage of beats within the peaks in the 3D plot. Based on the 3D plots, clustering of RR intervals was present in 31 (47%) of the 66 patients. ECV was effective in restoring sinus rhythm in 29 (94%) of these 31 patients, whereas sinus rhythm was restored in only 25 (71%) of the remaining 35 patients without clustering (P = 0.020). The clustering index ranged from <2% in the 12 patients with failed ECV to >8% in the 32 patients with sinus rhythm at the end of the study (4 weeks after the ECV); the clustering index in the 22 patients with a relapse of AF after effective ECV was intermediate (P = 0.034 and P = 0.042, respectively). Conclusion: This study indicates that ECV is more effective in restoring sinus rhythm in AF patients with clustering compared to patients in whom no clustering is apparent on 3D plots. In addition, the degree of clustering appears to be predictive of the overall outcome of ECV; the higher the degree of clustering, the higher the likelihood of sinus rhythm at follow-up. (J Cardiovasc Electrophysiol, Vol. 15, pp. 1-7, September 2004)
机译:心房颤动的电复律。简介:心房颤动(AF)的特征是心律不规则(“随机”)。但是,AF的心律是否真的随机存在争议。我们通过构建三维RR间隔图(3D图)来研究随机性,从而使聚类心脏复律(ECV)的识别在具有聚类的AF患者中更为有效,因为聚类可能反映出较高的心房纤颤活动组织度。方法和结果:该研究组包括66例患者(44例男性和22例女性;平均年龄68 +/- 11岁),他们因持续性房颤而转诊ECV。通过将每个RR间隔(x轴)相对于先前的RR间隔(y轴)以及每个x,y组合的出现次数(z轴)作图,将二十四小时的Holter记录用于构建3D图。将聚类指数计算为3D图中峰值内的心跳百分比。根据3D图,在66位患者中,有31位(47%)存在RR间期的聚类。 ECV可有效恢复这31例患者中的29例(94%)的窦性心律,而其余35例中没有聚集的窦性心律仅恢复25例(71%)(P = 0.020)。在研究结束时(ECV后4周),聚集指数的范围从12例ECV失败的患者中的<2%到32例窦性心律的患者中的> 8%;有效ECV后AF复发的22例患者的聚集指数处于中等水平(分别为P = 0.034和P = 0.042)。结论:这项研究表明,与在3D图上没有明显聚集的患者相比,具有聚集性的AF患者ECV在恢复窦性心律方面更有效。此外,聚类的程度似乎可以预测ECV的总体结果。聚类程度越高,随访时窦性心律的可能性越高。 (J Cardiovasc Electrophysiol,Vol.15,pp.1-7,2004年9月)

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