Daniëls Fenna, Ramdjan Tanwier T T K, Mánfai Balázs, Adiyaman Ahmet, Smit Jaap Jan J, Delnoy Peter Paul H M, Elvan Arif
Department of Cardiology, Isala Heart Centre, Zwolle, The Netherlands.
Neth Heart J. 2024 Apr;32(4):160-166. doi: 10.1007/s12471-023-01828-6. Epub 2023 Nov 28.
Untreated atrial fibrillation (AF) often results in increased morbidity and mortality. Opportunistic AF screening in persons aged ≥ 65 years is recommended to identify patients with AF in order to prevent AF-related complications.
The aim of this study was to assess the feasibility of screening persons for AF with the Kardia mobile electrocardiogram device (MED) and to determine the percentage of newly detected AF cases by selective population screening in the Netherlands.
Persons aged ≥ 65 years, without a medical history of AF, in nursing homes, at public events or visiting the general practitioner (GP) were approached to participate. A Kardia MED smartphone ECG (sECG) was recorded and the CHADS-VASc score was calculated. An automated AF algorithm classified the sECGs as 'sinus rhythm', 'AF' or 'unclassified'. In the case of AF, participants were referred to their GP. All sECGs were assessed by blinded experts.
A total of 2168 participants were screened for AF. According to the expert's interpretation, 2.5% had newly detected AF, of whom 76.4% never experienced palpitations and 89.1% had a CHADS-VASc score ≥ 2. The algorithm result was unclassified in 12.2% of cases, of which 95.5% were interpretable by experts. With expert opinion as the gold standard and excluding unclassified sECGs, the Kardia MED's negative and positive predictive value for detecting AF was 99.8% and 60.0%, respectively.
Screening for AF using the Kardia MED is feasible and results in 2.5% newly detected AF cases. Expert interpretation of algorithm outcomes AF and unclassified is recommended.
未经治疗的心房颤动（房颤）常导致发病率和死亡率增加。建议对65岁及以上人群进行机会性房颤筛查，以识别房颤患者，预防与房颤相关的并发症。
本研究旨在评估使用Kardia移动心电图设备（MED）对人群进行房颤筛查的可行性，并确定荷兰通过选择性人群筛查新发现的房颤病例百分比。
邀请65岁及以上、无房颤病史的养老院居民、参加公共活动的人员或就诊于全科医生（GP）的人员参与。记录Kardia MED智能手机心电图（sECG）并计算CHADS-VASc评分。自动房颤算法将sECG分类为“窦性心律”、“房颤”或“未分类”。如为房颤，参与者被转诊至其全科医生处。所有sECG均由盲法专家评估。
共对2168名参与者进行了房颤筛查。根据专家解读，2.5%的人新发现房颤，其中76.4%从未有心悸症状，89.1%的CHADS-VASc评分≥2。算法结果在12.2%的病例中未分类，其中95.5%可由专家解读。以专家意见为金标准并排除未分类的sECG，Kardia MED检测房颤的阴性和阳性预测值分别为99.8%和60.0%。
使用Kardia MED进行房颤筛查是可行的，新发现房颤病例占2.5%。建议对算法结果房颤和未分类进行专家解读。
