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前瞻性盲法评估基于智能手机的心电图用于鉴别室上性心动过速与不适当窦性心动过速。

Prospective blinded evaluation of smartphone-based ECG for differentiation of supraventricular tachycardia from inappropriate sinus tachycardia.

机构信息

Department of Cardiology II-Electrophysiology, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.

Department of Cardiology and Vascular Medicine, West German Heart and Vascular Center Essen, University Duisburg-Essen, Essen, Germany.

出版信息

Clin Res Cardiol. 2021 Jun;110(6):905-912. doi: 10.1007/s00392-021-01856-5. Epub 2021 May 7.

DOI:10.1007/s00392-021-01856-5
PMID:33961097
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8103426/
Abstract

INTRODUCTION

Supraventricular tachycardias (SVT) are often difficult to document due to their intermittent, short-lasting nature. Smartphone-based one-lead ECG monitors (sECG) were initially developed for the diagnosis of atrial fibrillation. No data have been published regarding their potential role in differentiating inappropiate sinus tachycardia (IST) from regular SVT. If cardiologists could distinguish IST from SVT in sECG, economic health care burden might be significantly reduced.

METHODS

We prospectively recruited 75 consecutive patients with known SVT undergoing an EP study. In all patients, four ECG were recorded: a sECG during SVT and during sinus tachycardia and respective 12-lead ECG. Two experienced electrophysiologists were blinded to the diagnoses and separately evaluated all ECG.

RESULTS

Three hundred individual ECG were recorded in 75 patients (47 female, age 50 ± 18 years, BMI 26 ± 5 kg/m, 60 AVNRT, 15 AVRT). The electrophysiologists' blinded interpretation of sECG recordings showed a sensitivity of 89% and a specificity of 91% for the detection of SVT (interobserver agreement κ = 0.76). In high-quality sECG recordings (68%), sensitivity rose to 95% with a specificity of 92% (interobserver agreement of κ = 0.91). Specificity increased to 96% when both electrophysiologists agreed on the diagnosis. Respective 12-lead ECG had a sensitivity of 100% and specificity of 98% for the detection of SVT.

CONCLUSION

A smartphone-based one-lead ECG monitor allows for differentiation of SVT from IST in about 90% of cases. These results should encourage cardiologists to integrate wearables into clinical practice, possibly reducing time to definitive diagnosis of an arrhythmia and unnecessary EP procedures. A smartphone-based one lead ECG device (panel A) can be used reliably to differentiate supraventricular tachycardia (panel B) from inappropriate sinus tachycardia when compared to a simultaneously conducted gold-standard electrophysiology study (panels C, D).

摘要

简介

由于室上性心动过速 (SVT) 具有间歇性和短暂性,因此通常难以记录。基于智能手机的单导联心电图监测器 (sECG) 最初是为心房颤动的诊断而开发的。尚未发表关于其在区分不适当窦性心动过速 (IST) 与规则 SVT 方面的潜在作用的相关数据。如果心脏病专家能够在 sECG 中区分 IST 与 SVT,则可能会显著降低医疗保健的经济负担。

方法

我们前瞻性地招募了 75 例已知患有 SVT 并接受电生理研究的连续患者。在所有患者中,记录了 4 个心电图:SVT 期间和窦性心动过速期间的 sECG 以及相应的 12 导联心电图。两名经验丰富的电生理学家对诊断结果不了解,并分别评估了所有心电图。

结果

在 75 例患者中记录了 300 个个体心电图(47 例女性,年龄 50 ± 18 岁,BMI 26 ± 5 kg/m,60 例房室结折返性心动过速,15 例房室折返性心动过速)。电生理学家对 sECG 记录的盲法解读显示,SVT 的检测敏感性为 89%,特异性为 91%(观察者间一致性 κ = 0.76)。在高质量的 sECG 记录(68%)中,敏感性提高至 95%,特异性为 92%(观察者间一致性 κ = 0.91)。当两位电生理学家对诊断意见一致时,特异性增加至 96%。相应的 12 导联心电图对 SVT 的检测敏感性为 100%,特异性为 98%。

结论

基于智能手机的单导联心电图监测器可在大约 90%的情况下区分 SVT 与 IST。这些结果应鼓励心脏病专家将可穿戴设备纳入临床实践,可能会减少心律失常明确诊断和不必要的电生理程序的时间。与同时进行的黄金标准电生理研究(面板 C、D)相比,基于智能手机的单导联心电图设备(面板 A)可可靠地区分室上性心动过速(面板 B)和不适当窦性心动过速。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5f/8166806/76d616d3865e/392_2021_1856_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5f/8166806/c2ed6c675eaf/392_2021_1856_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5f/8166806/ed36bab2f7ff/392_2021_1856_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5f/8166806/76d616d3865e/392_2021_1856_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5f/8166806/c2ed6c675eaf/392_2021_1856_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5f/8166806/ed36bab2f7ff/392_2021_1856_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5f/8166806/76d616d3865e/392_2021_1856_Fig3_HTML.jpg

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