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基于光电容积脉搏波技术的智能设备对心房颤动检测的诊断性能:初步研究(Pre-mAFA II 注册研究)

Diagnostic Performance of a Smart Device With Photoplethysmography Technology for Atrial Fibrillation Detection: Pilot Study (Pre-mAFA II Registry).

机构信息

College of Medicine, Nankai University, Tianjin, China.

Department of Cardiology, Chinese People's Liberation Army General Hospital, Beijing, China.

出版信息

JMIR Mhealth Uhealth. 2019 Mar 5;7(3):e11437. doi: 10.2196/11437.

Abstract

BACKGROUND

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. The asymptomatic nature and paroxysmal frequency of AF lead to suboptimal early detection. A novel technology, photoplethysmography (PPG), has been developed for AF screening. However, there has been limited validation of mobile phone and smart band apps with PPG compared to 12-lead electrocardiograms (ECG).

OBJECTIVE

We investigated the feasibility and accuracy of a mobile phone and smart band for AF detection using pulse data measured by PPG.

METHODS

A total of 112 consecutive inpatients were recruited from the Chinese PLA General Hospital from March 15 to April 1, 2018. Participants were simultaneously tested with mobile phones (HUAWEI Mate 9, HUAWEI Honor 7X), smart bands (HUAWEI Band 2), and 12-lead ECG for 3 minutes.

RESULTS

In all, 108 patients (56 with normal sinus rhythm, 52 with persistent AF) were enrolled in the final analysis after excluding four patients with unclear cardiac rhythms. The corresponding sensitivity and specificity of the smart band PPG were 95.36% (95% CI 92.00%-97.40%) and 99.70% (95% CI 98.08%-99.98%), respectively. The positive predictive value of the smart band PPG was 99.63% (95% CI 97.61%-99.98%), the negative predictive value was 96.24% (95% CI 93.50%-97.90%), and the accuracy was 97.72% (95% CI 96.11%-98.70%). Moreover, the diagnostic sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of mobile phones with PPG for AF detection were over 94%. There was no significant difference after further statistical analysis of the results from the different smart devices compared with the gold-standard ECG (P>.99).

CONCLUSIONS

The algorithm based on mobile phones and smart bands with PPG demonstrated good performance in detecting AF and may represent a convenient tool for AF detection in at-risk individuals, allowing widespread screening of AF in the population.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR-OOC-17014138; http://www.chictr.org.cn/showproj.aspx?proj=24191 (Archived by WebCite at http://www.webcitation/76WXknvE6).

摘要

背景

心房颤动(AF)是最常见的持续性心律失常。AF 的无症状性质和阵发性频率导致早期检测效果不佳。一种新的技术,光体积描记法(PPG),已经被开发用于 AF 筛查。然而,与 12 导联心电图(ECG)相比,用于手机和智能手环的 PPG 的移动应用程序的验证有限。

目的

我们研究了使用 PPG 测量的脉搏数据的手机和智能手环检测 AF 的可行性和准确性。

方法

2018 年 3 月 15 日至 4 月 1 日,从中国人民解放军总医院连续招募了 112 名住院患者。参与者同时使用手机(华为 Mate 9、华为 Honor 7X)、智能手环(华为 Band 2)和 12 导联心电图进行 3 分钟测试。

结果

在排除 4 例心律不齐患者后,共有 108 例患者(窦性心律正常 56 例,持续性 AF 52 例)纳入最终分析。智能手环 PPG 的相应灵敏度和特异性分别为 95.36%(95%CI 92.00%-97.40%)和 99.70%(95%CI 98.08%-99.98%)。智能手环 PPG 的阳性预测值为 99.63%(95%CI 97.61%-99.98%),阴性预测值为 96.24%(95%CI 93.50%-97.90%),准确性为 97.72%(95%CI 96.11%-98.70%)。此外,手机 PPG 检测 AF 的诊断灵敏度、特异性、阳性预测值、阴性预测值和准确率均超过 94%。进一步对不同智能设备与金标准 ECG 之间的结果进行统计分析后,结果差异无统计学意义(P>.99)。

结论

基于智能手机和智能手环的 PPG 算法在检测 AF 方面表现出良好的性能,可能成为 AF 检测的便捷工具,有助于在高危人群中进行 AF 检测,从而在人群中广泛筛查 AF。

试验注册

中国临床试验注册中心 ChiCTR-OOC-17014138;http://www.chictr.org.cn/showproj.aspx?proj=24191(由 WebCite 存档;http://www.webcitation/76WXknvE6)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49d4/6423467/488329e1a3d7/mhealth_v7i3e11437_fig1.jpg

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