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观察性研究方案:心律失常通知功能。

Observational study protocol for an arrhythmia notification feature.

机构信息

Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA.

WHOOP, Boston, Massachusetts, USA.

出版信息

BMJ Open. 2024 Jun 3;14(6):e075110. doi: 10.1136/bmjopen-2023-075110.

Abstract

INTRODUCTION

Screening for atrial fibrillation (AF) in the general population may help identify individuals at risk, enabling further assessment of risk factors and institution of appropriate treatment. Algorithms deployed on wearable technologies such as smartwatches and fitness bands may be trained to screen for such arrhythmias. However, their performance needs to be assessed for safety and accuracy prior to wide-scale implementation.

METHODS AND ANALYSIS

This study will assess the ability of the WHOOP strap to detect AF using its WHOOP Arrhythmia Notification Feature (WARN) algorithm in an enriched cohort with a 2:1 distribution of previously diagnosed AF (persistent and paroxysmal) and healthy controls. Recruited participants will collect data for 7 days with the WHOOP wrist-strap and BioTel ePatch (electrocardiography gold-standard). Primary outcome will be participant level sensitivity and specificity of the WARN algorithm in detecting AF in analysable windows compared with the ECG gold-standard. Similar analyses will be performed on an available epoch-level basis as well as comparison of these findings in important subgroups.

ETHICS AND DISSEMINATION

The study was approved by the ethics board at the study site. Participants will be enrolled after signing an online informed consent document. Updates will be shared via clinicaltrials.gov. The data obtained from the conclusion of this study will be presented in national and international conferences with publication in clinical research journals.

TRIAL REGISTRATION NUMBER

NCT05809362.

摘要

简介

在普通人群中筛查心房颤动(AF)有助于识别高危人群,从而进一步评估危险因素并进行适当的治疗。可穿戴技术(如智能手表和健身带)上部署的算法可用于筛查此类心律失常。然而,在广泛实施之前,需要评估其安全性和准确性。

方法和分析

本研究将使用 WHOOP 表带的 WHOOP 心律失常通知功能(WARN)算法,在先前诊断为 AF(持续性和阵发性)和健康对照组比例为 2:1 的丰富队列中,评估 WHOOP 表带检测 AF 的能力。招募的参与者将使用 WHOOP 腕带和 BioTel ePatch(心电图金标准)收集 7 天的数据。主要结果是与 ECG 金标准相比,可分析窗口中 WARN 算法检测 AF 的参与者水平敏感性和特异性。还将在可用的 epoch 水平上进行类似的分析,并在重要亚组中比较这些发现。

伦理和传播

该研究已获得研究现场伦理委员会的批准。参与者将在签署在线知情同意书后被纳入。更新将通过 clinicaltrials.gov 共享。从这项研究结束获得的数据将在全国和国际会议上展示,并在临床研究期刊上发表。

试验注册号

NCT05809362。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74a5/11149124/7df2036d327d/bmjopen-2023-075110f01.jpg

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