与标准动态心电图监测相比，通过腕戴式人工智能设备进行动态房颤检测和量化分析。
Ambulatory atrial fibrillation detection and quantification by wristworn AI device compared to standard holter monitoring.
作者信息
van Vliet Mariska, Aalberts Jan J J, Hamelinck Cora, Hauer Arnaud D, Hoftijzer Dieke, Monnink Stefan H J, Schipper Jurjan C, Constandse Jan C, Peters Nicholas S, Lip Gregory Y H, Steinhubl Steven R, Ronner Eelko
机构信息
Department of Cardiology, Reinier the Graaf Hospital, Reinier de Graafweg 5, 2625 AD, Delft, the Netherlands.
National Heart and Lung Institute, Imperial College London, London, UK.
出版信息
NPJ Digit Med. 2025 Mar 25;8(1):177. doi: 10.1038/s41746-025-01555-9.
Timely detection of atrial fibrillation (AF) is crucial for the prevention of serious consequences such as stroke and heart failure, yet it remains challenging due to its often asymptomatic or paroxysmal nature. Wearable devices with artificial intelligence algorithms offer promising solutions. AF detection by the CardioWatch 287-2 (CW2), a wrist-worn photoplethysmography (PPG) and single-lead ECG device, was compared to 24-h Holter. Patient compliance, AF prevalence and AF burden were evaluated for 27 additional days. Data from 150 participants (mean age 64 ± 12 SD; 41% female) were analysed. The CW2's PPG and single-lead ECG algorithms achieved a specificity ≥98% and sensitivity ≥95% for AF detection, and 99% correlation for AF burden, compared to 24-h Holter. AF prevalence increased from 14.7% (24-h Holter) to 26.7% (28-day CW2). Thus, the wrist-worn device showed promising performance in detecting AF and determining AF burden. The trial was registered on ClinicalTrials.gov (NCT05899959) on June 2, 2023.
及时检测心房颤动（AF）对于预防中风和心力衰竭等严重后果至关重要，但由于其通常无症状或阵发性的特点，检测仍具有挑战性。带有人工智能算法的可穿戴设备提供了有前景的解决方案。将腕部佩戴的光电容积脉搏波描记法（PPG）和单导联心电图设备CardioWatch 287-2（CW2）检测AF的结果与24小时动态心电图进行比较。另外对27天的患者依从性、AF患病率和AF负荷进行了评估。分析了150名参与者（平均年龄64±12标准差；41%为女性）的数据。与24小时动态心电图相比，CW2的PPG和单导联心电图算法在AF检测方面特异性≥98%，敏感性≥95%，AF负荷相关性为99%。AF患病率从（24小时动态心电图检测的）14.7%增至（28天CW2检测的）26.7%。因此，这种腕部佩戴设备在检测AF和确定AF负荷方面表现出有前景的性能。该试验于2023年6月2日在ClinicalTrials.gov上注册（NCT05899959）。
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