Saarinen Harri Juhani, Joutsen Atte, Korpi Kirsi, Halkola Tuomas, Nurmi Marko, Hernesniemi Jussi, Vehkaoja Antti
Heart Hospital, Tampere University Hospital, Tampere, Finland.
Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Front Cardiovasc Med. 2023 Feb 9;10:1100127. doi: 10.3389/fcvm.2023.1100127. eCollection 2023.
The aim was to validate the performance of a monitoring system consisting of a wrist-worn device and a data management cloud service intended to be used by medical professionals in detecting atrial fibrillation (AF).
Thirty adult patients diagnosed with AF alone or AF with concomitant flutter were recruited. Continuous photoplethysmogram (PPG) and intermittent 30 s Lead I electrocardiogram (ECG) recordings were collected over 48 h. The ECG was measured four times a day at prescheduled times, when notified due to irregular rhythm detected by PPG, and when self-initiated based on symptoms. Three-channel Holter ECG was used as the reference.
The subjects recorded a total of 1,415 h of continuous PPG data and 3.8 h of intermittent ECG data over the study period. The PPG data were analyzed by the system's algorithm in 5-min segments. The segments containing adequate amounts, at least ~30 s, of adequate quality PPG data for rhythm assessment algorithm, were included. After rejecting 46% of the 5-min segments, the remaining data were compared with annotated Holter ECG yielding AF detection sensitivity and specificity of 95.6 and 99.2%, respectively. The ECG analysis algorithm labeled 10% of the 30-s ECG records as inadequate quality and these were excluded from the analysis. The ECG AF detection sensitivity and specificity were 97.7 and 89.8%, respectively. The usability of the system was found to be good by both the study subjects and the participating cardiologists.
The system comprising of a wrist device and a data management service was validated to be suitable for use in patient monitoring and in the detection of AF in an ambulatory setting.: ClinicalTrials.gov/, NCT05008601.
本研究旨在验证一种监测系统的性能，该系统由腕部佩戴设备和数据管理云服务组成，供医学专业人员用于检测心房颤动（AF）。
招募了30名仅诊断为AF或合并AF伴扑动的成年患者。在48小时内收集连续的光电容积脉搏波描记图（PPG）和间歇性30秒的I导联心电图（ECG）记录。ECG每天在预定时间测量4次，PPG检测到心律不规则时进行通知测量，以及患者根据症状自行发起测量时进行测量。使用三通道动态心电图作为参考。
在研究期间，受试者共记录了1415小时的连续PPG数据和3.8小时的间歇性ECG数据。系统算法对PPG数据按5分钟片段进行分析。纳入了包含足够数量（至少约30秒）、质量足够用于心律评估算法的PPG数据的片段。在剔除46%的5分钟片段后，将剩余数据与注释的动态心电图进行比较，AF检测的敏感性和特异性分别为95.6%和99.2%。ECG分析算法将三十分之一的30秒ECG记录标记为质量不足，并将这些记录排除在分析之外。ECG AF检测的敏感性和特异性分别为97.7%和89.8 %。研究对象和参与研究的心脏病专家均认为该系统的可用性良好。
由腕部设备和数据管理服务组成的系统经验证适用于患者监测及门诊环境下心房颤动的检测。：ClinicalTrials.gov/，NCT05008601。
