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用于鉴别阵发性与非阵发性心房颤动的新型评分系统

Novel Scoring System for Distinction Between Paroxysmal and Non-Paroxysmal Atrial Fibrillation.

作者信息

Oikawa Jun, Niwano Shinichi, Fukaya Hidehira, Nakamura Hironori, Igarashi Tazuru, Fujiishi Tamami, Ishizue Naruya, Yoshizawa Tomoharu, Satoh Akira, Kishihara Jun, Murakami Masami, Ako Junya

机构信息

Department of Cardiovascular Medicine, Kitasato University School of Medicine.

出版信息

Circ J. 2017 May 25;81(6):788-793. doi: 10.1253/circj.CJ-16-1054. Epub 2017 Feb 28.

Abstract

BACKGROUND

Distinction of paroxysmal atrial fibrillation (PAF) from non-PAF is important in clinical practice, but this is often difficult at the time of first documented AF. Given that fibrillation cycle length (FCL) is longer in PAF than in non-PAF, the aim of this study was to compare various clinical parameters including FCL to establish a scoring system to distinguish PAF and non-PAF.

METHODS AND RESULTS

The subjects consisted of 382 consecutive patients with AF on digital ECG at the present institute between 2008 and 2011. They were divided into PAF and non-PAF groups according to the following clinical course. Propensity score matching yielded 88 matched patient pairs with similar mean age and gender between the 2 groups. FCL was evaluated using customized fibrillation wave analyzer with fast Fourier transform analysis. On multivariate analysis, higher HR, longer FCL, and smaller LAD were independent predictors of PAF. For the scoring, cut-offs for each parameter were determined according to highest sensitivity and specificity on the ROC curves, and 1 point assigned for each parameter. Using this scoring system, 2 points detected PAF with 64% sensitivity and 84% specificity.

CONCLUSIONS

We propose a scoring system including FCL to distinguish PAF from non-PAF. Further studies are needed to validate the results.

摘要

背景

在临床实践中,区分阵发性心房颤动(PAF)和非PAF很重要,但在首次记录到房颤时往往很难做到。鉴于PAF的颤动周期长度(FCL)比非PAF长,本研究的目的是比较包括FCL在内的各种临床参数,以建立一个区分PAF和非PAF的评分系统。

方法与结果

研究对象为2008年至2011年间本研究所连续382例数字心电图显示房颤的患者。根据以下临床病程将他们分为PAF组和非PAF组。倾向得分匹配产生了88对匹配的患者,两组之间的平均年龄和性别相似。使用定制的颤动波分析仪和快速傅里叶变换分析来评估FCL。多因素分析显示,较高的心率、较长的FCL和较小的左心房内径是PAF的独立预测因素。在评分时,根据ROC曲线上的最高敏感性和特异性确定每个参数的临界值,每个参数赋予1分。使用该评分系统,2分可检测出PAF,敏感性为64%,特异性为84%。

结论

我们提出了一个包括FCL的评分系统来区分PAF和非PAF。需要进一步研究来验证结果。

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