Abdelhamid Khaled, Reissenberger Pamela, Piper Diana, Koenig Nicole, Hoelz Bianca, Schlaepfer Julia, Gysler Simone, McCullough Helena, Ramin-Wright Sebastian, Gabathuler Anna-Lena, Khandpur Jahnvi, Meier Milene, Eckstein Jens
Department of Internal Medicine, University Hospital Basel, 4031 Basel, Switzerland.
Preventicus GmbH, 07743 Jena, Germany.
Diagnostics (Basel). 2025 May 14;15(10):1233. doi: 10.3390/diagnostics15101233.
: Atrial fibrillation (AF) remains a major risk factor for stroke. It is often asymptomatic and paroxysmal, making it difficult to detect with conventional electrocardiography (ECG). While photoplethysmography (PPG)-based devices like smartwatches have demonstrated efficacy in detecting AF, they are rarely integrated into hospital infrastructure. The study aimed to establish a seamless system for real-time AF screening in hospitalized high-risk patients using a wrist-worn PPG device integrated into a hospital's data infrastructure. : In this investigator-initiated prospective clinical trial conducted at the University Hospital Basel, patients with a CHADS-VASc score ≥ 2 and no history of AF received a wristband equipped with a PPG sensor for continuous monitoring during their hospital stay. The PPG data were automatically transmitted, analyzed, stored, and visualized. Upon detection of an absolute arrhythmia (AA) in the PPG signal, a Holter ECG was administered. : The analysis encompassed 346 patients (mean age 72 ± 10 years, 175 females (50.6%), mean CHADS-VASc score 3.5 ± 1.3)). The mean monitoring duration was 4.3 ± 4.4 days. AA in the PPG signal was detected in twelve patients (3.5%, CI: 1.5-5.4%), with most cases identified within 24 h ( = 0.004). There was a 1.3 times higher AA burden during the nighttime compared to daytime ( = 0.03). Compliance was high (304/346, 87.9%). No instances of AF were confirmed in the nine patients undergoing Holter ECG. : This study successfully pioneered an automated infrastructure for AF screening in hospitalized patients through the use of wrist-worn PPG devices. This implementation allowed for real-time data visualization and intervention in the form of a Holter ECG. The high compliance and early AA detection achieved in this study underscore the potential and relevance of this novel infrastructure in clinical practice.
心房颤动(AF)仍然是中风的主要危险因素。它通常无症状且呈阵发性,使得用传统心电图(ECG)难以检测到。虽然像智能手表这样基于光电容积脉搏波描记法(PPG)的设备已证明在检测AF方面有效,但它们很少集成到医院基础设施中。该研究旨在使用集成到医院数据基础设施中的腕戴式PPG设备,为住院高危患者建立一个用于实时AF筛查的无缝系统。
在巴塞尔大学医院进行的这项由研究者发起的前瞻性临床试验中,CHADS-VASc评分≥2且无AF病史的患者在住院期间佩戴配备PPG传感器的腕带进行连续监测。PPG数据被自动传输、分析、存储和可视化。在PPG信号中检测到绝对心律失常(AA)后,进行动态心电图检查。
分析纳入了346例患者(平均年龄72±10岁,175例女性(50.6%),平均CHADS-VASc评分为3.5±1.3)。平均监测时长为4.3±4.4天。在12例患者(3.5%,置信区间:1.5 - 5.4%)的PPG信号中检测到AA,大多数病例在24小时内被识别(P = 0.004)。夜间的AA负担比白天高1.3倍(P = 0.03)。依从性较高(304/346,87.9%)。在接受动态心电图检查的9例患者中未确认有AF病例。
本研究通过使用腕戴式PPG设备成功开创了一种用于住院患者AF筛查的自动化基础设施。这种实施方式实现了实时数据可视化以及以动态心电图形式进行干预。本研究中实现的高依从性和早期AA检测突出了这种新型基础设施在临床实践中的潜力和相关性。