Atrial Fibrillation Episode Patterns and Their Influence on Detection Performance

Author(s):  
Monika Butkuviene ◽  
Andrius Petrenas ◽  
Andrius Solosenko ◽  
Alba Martin-Yebra ◽  
Vaidotas Marozas ◽  
...  
2004 ◽  
Vol 43 (01) ◽  
pp. 94-98 ◽  
Author(s):  
S. Mota ◽  
F. J. Toro ◽  
A. F. Díaz ◽  
F. J. Fernández ◽  
E. Ros

Summary Objectives: The objective of the paper is to describe an automatic algorithm for Paroxysmal Atrial Fibrillation (PAF) Detection, based on parameters extracted from ECG traces with no atrial fibrillation episode. The modular automatic classification algorithm for PAF diagnosis is developed and evaluated with different parameter configurations. Methods: The database used in this study was provided by Physiobank for The Computers in Cardiology Challenge 2001. Each ECG file in this database was translated into a 48 parameter vector. The modular classification algorithm used for PAF diagnosis was based on the nearest K-neighbours. Several configuration options were evaluated to optimize the classification performance. Results: Different configurations of the proposed modular classification algorithm were tested. The uni-parametric approach achieved a top classification rate value of 76%. A multi-parametric approach was configured using the 5 parameters with highest discrimination power, and a top classification rate of 80% was achieved; different functions to typify the parameters were tested. Finally, two automatic parametric scanning strategies, Forward and Backward methods, were adopted. The results obtained with these approaches achieved a top classification rate of 92%. Conclusions: A modular classification algorithm based on the nearest K-neighbours was designed. The classification performance of the algorithm was evaluated using different parameter configurations, typification functions and number of K-neighbors. The automatic parametric scanning techniques achieved much better results than previously tested configurations.


2020 ◽  
Vol 3 (7) ◽  
pp. e208748 ◽  
Author(s):  
Jason G. Andrade ◽  
Marc W. Deyell ◽  
Atul Verma ◽  
Laurent Macle ◽  
Jean Champagne ◽  
...  

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Kremer ◽  
D.S Stierle ◽  
H Naegele

Abstract Aims The primary goal of this study was the evaluation of the arrhythmia detection performance of an implantable loop recorder (ILR) in patients with syncope of unknown etiology and patients with embolic stroke of undetermined source (ESUS). Secondary goals were the evaluation of diagnostic yield, time to diagnosis and established therapeutical consequences. Methods The Reveal LINQ ILR was implanted in n=143 patients (n=84 after ESUS, n=59 after syncope). Automatically detected episodes (n=3213) were transmitted via internet and validated by two experienced cardiologists and either classified as correct or incorrect. Positive-predictive value (ppv = true-positive episodes/true-positive episodes + false-positive episodes) was calculated for each available arrhythmia type. Incorrect episodes were classified as undersensing, oversensing, artifacts or supraventricular/ventricular ectopic beats. The diagnostic yield was defined by asystole ≥3 seconds or the detection of atrial fibrillation. Time to diagnosis was calculated as the time from implantation to detection of an asystole or atrial fibrillation. Results Every second asystole episode in syncope-patients was false-positive (ppv 52%), mostly due to undersensing. The atrial fibrillation detection performance in ESUS-patients was 70% (ppv-average). The majority of false-positive episodes was due to premature atrial and ventricular complexes (80%), followed by artifacts (14%) and oversensing (4%). Undersensing accounted for 2%. 36% of syncope-patients were diagnosed with an asystole after a mean time to event of 114 days. In 47% of syncope-patients diagnosed with asystole, a pacemaker was implanted. In 31% of ESUS-patients a diagnosis of atrial fibrillation was established, after a mean time to event of 92 days. 85% of ESUS-patients diagnosed with atrial fibrillation were ultimately treated with an oral anticoagulant. Conclusion and discussion The Reveal Linq ILR - advertised as an automatic diagnostic tool for syncope- and ESUS-patients - has its caveats. A high number of false-positive detections due to undersensing limited the asystole detection performance. The atrial fibrillation detection performance presented more reliable, despite a substantial number of false-positive detections. A time-consuming manual episode review still represents an indispensable step in the diagnostic process, and enough human resources have to be factored before starting an ILR program. Funding Acknowledgement Type of funding source: None


2017 ◽  
Vol 26 (1) ◽  
pp. 109-113 ◽  
Author(s):  
Michał Peller ◽  
Piotr Lodziński ◽  
Krzysztof Ozierański ◽  
Agata Tymińska ◽  
Paweł Balsam ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document