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体表心电图峡部顺钟向折返性房扑的算法:ACTION 研究。

Algorithm for cavo-tricuspid isthmus flutter on surface ECGs: the ACTIONS study.

机构信息

Cardiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.

Internal Medicine, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania, USA.

出版信息

Open Heart. 2021 Jan;8(1). doi: 10.1136/openhrt-2020-001431.

Abstract

OBJECTIVE

Cavo-tricuspid isthmus atrial flutter (CTI-AFL) is an important arrhythmia to recognise because there is a highly effective and relatively low-risk ablation strategy. However, clinical experience has demonstrated that providers often have difficulty distinguishing AFL from atrial fibrillation.

METHODS

We developed a novel ECG-based three-step algorithm to identify CTI-AFL based on established CTI flutter characteristics and verified on consecutive ablation cases of typical flutter, atypical flutter and atrial fibrillation. The algorithm assesses V1/inferior lead F-wave concordance, consistency of P-wave morphology and the presence of isoelectric intervals in the inferior leads. In this observation study, the algorithm was validated on a cohort of 50 second-year medical students. Students were paired in a control and experimental group, and each pair received 10 randomly selected ECGs (from a pool of 50 intracardiac electrogram-proven CTI-AFL and 50 AF or atypical AFL cases). The experimental group received a cover sheet with the CTI algorithm, and the control group received no additional guidance.

RESULTS

There was a statistically significant difference in the mean number of correctly identified ECGs among the students in the experimental and control groups (8.12 vs 5.68, p<0.001). Students who used the algorithm correctly identified 2.44 more ECGs as being CTI-AFL or not CTI-AFL. Using the electrophysiology study as the gold standard, the algorithm had an accuracy of 81%, sensitivity of 81%, specificity of 82%, positive predictive value of 78% and negative predictive value of 84% in identifying CTI-AFL.

CONCLUSION

We developed a three-step ECG algorithm that provides a simple, sensitive, specific and accurate tool to identify CTI-AFL.

摘要

目的

三尖瓣峡部房扑(CTI-AFL)是一种重要的心律失常,需要识别,因为存在一种非常有效且风险相对较低的消融策略。然而,临床经验表明,提供者通常难以将 AFL 与心房颤动区分开来。

方法

我们开发了一种新的基于心电图的三步算法,根据已建立的 CTI 扑动特征来识别 CTI-AFL,并在连续的典型扑动、非典型扑动和心房颤动消融病例中进行验证。该算法评估 V1/下导联 F 波的一致性、P 波形态的一致性以及下导联中的等电间隔的存在。在这项观察性研究中,该算法在 50 名二年级医学生的队列中进行了验证。学生分为对照组和实验组,每组接受 10 份随机选择的心电图(来自 50 份经心内电图证实的 CTI-AFL 以及 50 份 AF 或非典型 AFL 病例的心电图)。实验组收到了一份带有 CTI 算法的覆盖表,对照组则没有收到额外的指导。

结果

实验组学生正确识别的心电图数量明显多于对照组(8.12 比 5.68,p<0.001)。使用该算法的学生正确识别了 2.44 个心电图为 CTI-AFL 或非 CTI-AFL。使用电生理研究作为金标准,该算法在识别 CTI-AFL 方面的准确性为 81%,灵敏度为 81%,特异性为 82%,阳性预测值为 78%,阴性预测值为 84%。

结论

我们开发了一种三步心电图算法,为识别 CTI-AFL 提供了一种简单、敏感、特异和准确的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e719/7843312/bcb155f1d1c4/openhrt-2020-001431f01.jpg

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