Performance of automated single-lead ECG atrial fibrillation screening is associated with patient characteristics. (24th May 2021)

• Record Type: Journal Article
• Authors: Zink, MD; Freedman, B; Mischke, K; Keszei, A; Rummey, C; Marx, N
• Is Part Of: Europace. Volume 23:Supplement 3(2021)
• Publication Date: 2021-05-24
• Subjects: Arrhythmia -- Treatment -- Periodicals; Cardiac pacing -- Periodicals; Catheter ablation -- Periodicals; Heart -- Physiology -- Periodicals; Electrophysiology -- Periodicals; 617.4120645
• DOI: 10.1093/europace/euab116.164
• Languages: English
• ISSNs: 1099-5129

Abstract

Abstract: Funding Acknowledgements: Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): The investigators received and unrestricted research grant by Pfizer/BMS. Pfizer/BMS was not involved in the planning, conduction, analysis, or interpretation of the data. Introduction: Screening for atrial fibrillation (AF) with a single-lead electrocardiogram device is on the rise. However, little is known about influence of automated AF screening performance related to patient characteristics. Aim: We tested the accuracy of automated AF detection of a single-lead ECG device and identified factors associated with diagnostic performance. Methods: In 6482 subjects of community-pharmacies a single-time point AF screening was performed. All ECGs were analyzed by blinded human overread and compared to the automated results in context of patient characteristics. Results: Automated screening showed good prediction of AF with an area under the receiver operating curve of 0.89; sensitivity 80%; specificity 98%; positive predictive value 71%; negative predictive value 99%. Good ECG signal quality was highly associated with correct measurement, while low signal quality leads to incorrect measurements. In a multivariate model we determined factors associated with excellent signal quality and as counterexample incorrect automatic AF identification. The Odds' ratio (OR) for excellent signal quality was strongly associated with female sex, lower age, lower height, and higher body weight index (table). Conclusion: The performance of automated AF screening is influenced by sex, age, height and body mass index. Potential target population groups, with high AF prevalence, have a higher chance of incorrect automatic measurement. We recommend an expert over-read, at least for all AF positive ECG recordings.