Jieqiong Guan1, Ailian Wang2, Wenjing Song1, Nathan Obore1, Pan He1, Siyu Fan1, Hong Zhi3, Lina Wang4. 1. Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, 87 Ding Jiaqiao Rd., Nanjing, 210009, China. 2. Qixia District, Yaohua Community Healthcare Center, Nanjing, China. 3. Department of Cardiology, ZhongDa Hospital, Southeast University, Nanjing, China. 4. Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, 87 Ding Jiaqiao Rd., Nanjing, 210009, China. lnwang@seu.edu.cn.
Abstract
BACKGROUND: SnapECG is a new handheld single-lead electrocardiograph (ECG) device used for arrhythmia screening, it is widely used in clinical practice but not in primary care. AIMS: To evaluate the arrhythmia screening value of SnapECG among a community-based population. METHODS: A cross-sectional community-based study of multistage stratified cluster sampling was conducted from March 1st to April 30th 2019. The sensitivities, specificities and the area under the receiver operating characteristic (AUCROC) curves of the SnapECG and reference 12-lead ECG on arrhythmia were calculated in three age-groups [50-64 years, 65-74 years, and over-75 years]. RESULTS: A total of 2263 participants took part in the arrhythmia screening, these included 1479 aged 50-64 years, 602 aged 65-74 years and 182 aged over-75 years. The SnapECG categorized 1828 (80.8%) as sinus rhythm, 161 (7.1%) as premature atrial/ventricular contractions (PAVs/PCVs), 32 (1.4%) as possible atrial fibrillation (AF), 56 (2.5%) as supraventricular tachycardias or sinus bradycardia (SVT/SB) and 186 (8.2%) as unreadable. SnapECG had 89% sensitivity (95% CI 0.52-1.00) and 99% specificity (95% CI 0.97-0.99) of detecting AF in the 65-74 years age-group. The AUCROC to detect AF was 0.94 for the 65-74 years age-group, 0.77 for over-75 years, 0.62 for the 50-64 years. DISCUSSION: This study is the first community screening application of SnapECG. Main limitation is the SnapECG and the 12-lead ECG were not done simultaneously. CONCLUSIONS: In the people aged 65-74 years, AF can be detected accurately by the SnapECG with high sensitivity, specificity and large area under the ROC curve, which might have the highest screening predictive accuracy.
BACKGROUND: SnapECG is a new handheld single-lead electrocardiograph (ECG) device used for arrhythmia screening, it is widely used in clinical practice but not in primary care. AIMS: To evaluate the arrhythmia screening value of SnapECG among a community-based population. METHODS: A cross-sectional community-based study of multistage stratified cluster sampling was conducted from March 1st to April 30th 2019. The sensitivities, specificities and the area under the receiver operating characteristic (AUCROC) curves of the SnapECG and reference 12-lead ECG on arrhythmia were calculated in three age-groups [50-64 years, 65-74 years, and over-75 years]. RESULTS: A total of 2263 participants took part in the arrhythmia screening, these included 1479 aged 50-64 years, 602 aged 65-74 years and 182 aged over-75 years. The SnapECG categorized 1828 (80.8%) as sinus rhythm, 161 (7.1%) as premature atrial/ventricular contractions (PAVs/PCVs), 32 (1.4%) as possible atrial fibrillation (AF), 56 (2.5%) as supraventricular tachycardias or sinus bradycardia (SVT/SB) and 186 (8.2%) as unreadable. SnapECG had 89% sensitivity (95% CI 0.52-1.00) and 99% specificity (95% CI 0.97-0.99) of detecting AF in the 65-74 years age-group. The AUCROC to detect AF was 0.94 for the 65-74 years age-group, 0.77 for over-75 years, 0.62 for the 50-64 years. DISCUSSION: This study is the first community screening application of SnapECG. Main limitation is the SnapECG and the 12-lead ECG were not done simultaneously. CONCLUSIONS: In the people aged 65-74 years, AF can be detected accurately by the SnapECG with high sensitivity, specificity and large area under the ROC curve, which might have the highest screening predictive accuracy.
Authors: Fred M Kusumoto; Mark H Schoenfeld; Coletta Barrett; James R Edgerton; Kenneth A Ellenbogen; Michael R Gold; Nora F Goldschlager; Robert M Hamilton; José A Joglar; Robert J Kim; Richard Lee; Joseph E Marine; Christopher J McLeod; Keith R Oken; Kristen K Patton; Cara N Pellegrini; Kimberly A Selzman; Annemarie Thompson; Paul D Varosy Journal: Circulation Date: 2018-11-06 Impact factor: 29.690