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移动医疗应用程序在心房颤动检测中的应用:系统评价。

Mobile health applications for the detection of atrial fibrillation: a systematic review.

机构信息

Department of Cardiology, Hopital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium.

Servicio de Cardiología, Hospital Universitario Miguel Servet, Isabel La Catolica 1-3, Zaragoza 50009, Spain.

出版信息

Europace. 2021 Jan 27;23(1):11-28. doi: 10.1093/europace/euaa139.

DOI:10.1093/europace/euaa139
PMID:33043358
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7842109/
Abstract

AIMS

Atrial fibrillation (AF) is the most common sustained arrhythmia and an important risk factor for stroke and heart failure. We aimed to conduct a systematic review of the literature and summarize the performance of mobile health (mHealth) devices in diagnosing and screening for AF.

METHODS AND RESULTS

We conducted a systematic search of MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. Forty-three studies met the inclusion criteria and were divided into two groups: 28 studies aimed at validating smart devices for AF diagnosis, and 15 studies used smart devices to screen for AF. Evaluated technologies included smartphones, with photoplethysmographic (PPG) pulse waveform measurement or accelerometer sensors, smartbands, external electrodes that can provide a smartphone single-lead electrocardiogram (iECG), such as AliveCor, Zenicor and MyDiagnostick, and earlobe monitor. The accuracy of these devices depended on the technology and the population, AliveCor and smartphone PPG sensors being the most frequent systems analysed. The iECG provided by AliveCor demonstrated a sensitivity and specificity between 66.7% and 98.5% and 99.4% and 99.0%, respectively. The PPG sensors detected AF with a sensitivity of 85.0-100% and a specificity of 93.5-99.0%. The incidence of newly diagnosed arrhythmia ranged from 0.12% in a healthy population to 8% among hospitalized patients.

CONCLUSION

Although the evidence for clinical effectiveness is limited, these devices may be useful in detecting AF. While mHealth is growing in popularity, its clinical, economic, and policy implications merit further investigation. More head-to-head comparisons between mHealth and medical devices are needed to establish their comparative effectiveness.

摘要

目的

心房颤动(AF)是最常见的持续性心律失常,也是中风和心力衰竭的重要危险因素。本研究旨在对文献进行系统回顾,总结移动医疗(mHealth)设备在诊断和筛查 AF 中的性能。

方法和结果

我们对 MEDLINE、Embase 和 Cochrane 对照试验中心注册库进行了系统检索。符合纳入标准的研究有 43 项,分为两组:28 项研究旨在验证用于 AF 诊断的智能设备,15 项研究使用智能设备筛查 AF。评估的技术包括智能手机,具有光体积描记(PPG)脉搏波测量或加速度计传感器、智能手环、可提供智能手机单导联心电图(iECG)的外部电极,如 AliveCor、Zenicor 和 MyDiagnostick,以及耳垂监测器。这些设备的准确性取决于技术和人群,AliveCor 和智能手机 PPG 传感器是最常分析的系统。AliveCor 提供的 iECG 分别显示出 66.7%至 98.5%和 99.4%至 99.0%的敏感性和特异性。PPG 传感器检测 AF 的敏感性为 85.0%至 100%,特异性为 93.5%至 99.0%。新诊断心律失常的发生率范围为 0.12%(健康人群)至 8%(住院患者)。

结论

尽管临床有效性的证据有限,但这些设备可能有助于检测 AF。随着移动医疗的普及,其临床、经济和政策影响值得进一步研究。需要对 mHealth 和医疗设备进行更多的头对头比较,以确定它们的相对有效性。