@Article{info:doi/10.2196/mhealth.8290,
author="Chen, Ying-Hsien
and Hung, Chi-Sheng
and Huang, Ching-Chang
and Hung, Yu-Chien
and Hwang, Juey-Jen
and Ho, Yi-Lwun",
title="Atrial Fibrillation Screening in Nonmetropolitan Areas Using a Telehealth Surveillance System With an Embedded Cloud-Computing Algorithm: Prospective Pilot Study",
journal="JMIR Mhealth Uhealth",
year="2017",
month="Sep",
day="26",
volume="5",
number="9",
pages="e135",
keywords="atrial fibrillation; screen; cloud-computing algorithm; electrocardiography",
abstract="Background: Atrial fibrillation (AF) is a common form of arrhythmia that is associated with increased risk of stroke and mortality. Detecting AF before the first complication occurs is a recognized priority. No previous studies have examined the feasibility of undertaking AF screening using a telehealth surveillance system with an embedded cloud-computing algorithm; we address this issue in this study. Objective: The objective of this study was to evaluate the feasibility of AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm. Methods: We conducted a prospective AF screening study in a nonmetropolitan area using a single-lead electrocardiogram (ECG) recorder. All ECG measurements were reviewed on the telehealth surveillance system and interpreted by the cloud-computing algorithm and a cardiologist. The process of AF screening was evaluated with a satisfaction questionnaire. Results: Between March 11, 2016 and August 31, 2016, 967 ECGs were recorded from 922 residents in nonmetropolitan areas. A total of 22 (2.4{\%}, 22/922) residents with AF were identified by the physician's ECG interpretation, and only 0.2{\%} (2/967) of ECGs contained significant artifacts. The novel cloud-computing algorithm for AF detection had a sensitivity of 95.5{\%} (95{\%} CI 77.2{\%}-99.9{\%}) and specificity of 97.7{\%} (95{\%} CI 96.5{\%}-98.5{\%}). The overall satisfaction score for the process of AF screening was 92.1{\%}. Conclusions: AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm is feasible. ",
issn="2291-5222",
doi="10.2196/mhealth.8290",
url="https://mhealth.jmir.org/2017/9/e135/",
url="https://doi.org/10.2196/mhealth.8290",
url="http://www.ncbi.nlm.nih.gov/pubmed/28951384"
}