Performance of automated single-lead ECG atrial fibrillation screening is associated with patient characteristics

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. Table 1 Excellent signal quality Incorrect measurement Univariate analysis Multivariate analysis Univariate analysis Multivariate analysis Parameter OR 95% CI P OR 95% CI P OR 95% CI P OR 95% CI P Sex [Female] 2.33 1.97-2.75 <0.001 1.92 1.53-2.41 <0.001 0.64 0.49-0.84 0.001 0.57 0.43-0.76 <0.001 Age [years] 0.97 0.96-0.98 <0.001 0.97 0.96-0.98 <0.001 1.07 1.04-1.09 <0.001 1.06 1.04-1.09 <0.001 Height [cm] 0.96 0.95-0.97 <0.001 0.98 0.97-0.99 0.003 1.01 0.99-1.03 0.068 Weight [kg] 0.99 0.99-1.00 0.418 0.99 0.98-0.99 0.003 BMI [kg/cm2] 1.04 1.03-1.06 <0.001 1.04 1.03-1.06 <0.001 0.91 0.88-0.95 <0.001 0.91 0.87-0.94 <0.001 CHADSVASC 1 0.95-1.06 0.912 1.06 0.97-1.17 0.205 Heart failure 0.62 0.41-0.93 0.022 1.86 1.13-3.05 0.015 Hypertension 0.96 0.83-1.11 0.58 1.06 0.80-1.39 0.689 Diabetes mellitus 0.85 0.68-1.07 0.159 0.82 0.54-1.25 0.359 Stroke / TIA 0.82 0.66-1.01 0.066 1.19 0.83-1.69 0.341 Vascular disease 0.89 0.75-1.07 0.213 1.31 0.98-1.77 0.70 OR – odd’s ratio, CI – confidence interval