Fabritz Larissa, Connolly D, Czarnecki E, Dudek D, Zlahoda-Huzior A, Guasch E, Haase D, Huebner T, Jolly K, Kirchhof P, Schotten Ulrich, Zapf Antonia, Schnabel Renate B
University Center of Cardiovascular Science, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Front Cardiovasc Med. 2022 Mar 21;9:839202. doi: 10.3389/fcvm.2022.839202. eCollection 2022.
Screening for atrial fibrillation and timely initiation of oral anticoagulation, rhythm management, and treatment of concomitant cardiovascular conditions can improve outcomes in high-risk populations. Whether wearables can facilitate screening in older adults is not known.
The multicenter, international, investigator-initiated, single-arm case-finding Smartphone and wearable detected atrial arrhythmia in older adults case finding study (Smart in OAC - AFNET 9) evaluates the diagnostic yield of a validated, cloud-based analysis algorithm detecting atrial arrhythmias via a signal acquired by a smartphone-coupled wristband monitoring system in older adults. Unselected participants aged ≥65 years without known atrial fibrillation and not receiving oral anticoagulation are enrolled in three European countries. Participants undergo continuous pulse monitoring using a wristband with a photo plethysmography (PPG) sensor and a telecare analytic service. Participants with PPG-detected atrial arrhythmias will be offered ECG loop monitoring. The study has a virtual design with digital consent and teleconsultations, whilst including hybrid solutions. Primary outcome is the proportion of older adults with newly detected atrial arrhythmias (NCT04579159).
Smart in OAC - AFNET 9 will provide information on wearable-based screening for PPG-detected atrial arrhythmias in Europe and provide an estimate of the prevalence of atrial arrhythmias in an unselected population of older adults.
筛查房颤并及时启动口服抗凝治疗、节律管理以及治疗合并的心血管疾病,可改善高危人群的预后。可穿戴设备能否促进老年人的筛查尚不清楚。
多中心、国际性、研究者发起的单臂病例发现研究“智能手机和可穿戴设备检测老年人房性心律失常”(Smart in OAC - AFNET 9),评估一种经过验证的基于云的分析算法通过智能手机连接的腕带监测系统采集的信号检测老年人房性心律失常的诊断率。在三个欧洲国家招募年龄≥65岁、无已知房颤且未接受口服抗凝治疗的未选择参与者。参与者使用带有光电容积脉搏波描记法(PPG)传感器的腕带和远程医疗分析服务进行连续脉搏监测。PPG检测到房性心律失常的参与者将接受动态心电图监测。该研究采用虚拟设计,包括数字同意和远程会诊,同时包括混合解决方案。主要结局是新检测到房性心律失常的老年人比例(NCT04579159)。
Smart in OAC - AFNET 9将提供关于欧洲基于可穿戴设备筛查PPG检测到的房性心律失常的信息,并估计未选择的老年人群中房性心律失常的患病率。