Abstract
Paroxysmal atrial fibrillation (PAF) is the most common cardiac arrhythmia, conveying a stroke risk comparable to persistent AF. It poses a significant diagnostic challenge given its intermittency and potential brevity, and absence of symptoms in most patients. This pilot study introduces a novel biomarker for early PAF detection, based upon analysis of sinus rhythm ECG waveform complexity. Sinus rhythm ECG recordings were made from 52 patients with (n = 28) or without (n = 24) a subsequent diagnosis of PAF. Subjects used a handheld ECG monitor to record 28-second periods, twice-daily for at least 3 weeks. Two independent ECG complexity indices were calculated using a Lempel-Ziv algorithm: R-wave interval variability (beat detection, BD) and complexity of the entire ECG waveform (threshold crossing, TC). TC, but not BD, complexity scores were significantly greater in PAF patients, but TC complexity alone did not identify satisfactorily individual PAF cases. However, a composite complexity score (h-score) based on within-patient BD and TC variability scores was devised. The h-score allowed correct identification of PAF patients with 85% sensitivity and 83% specificity. This powerful but simple approach to identify PAF sufferers from analysis of brief periods of sinus-rhythm ECGs using hand-held monitors should enable easy and low-cost screening for PAF with the potential to reduce stroke occurrence.
Highlights
Atrial fibrillation (AF) is the most frequently encountered sustained cardiac arrhythmia, affecting about 2% of the population
We demonstrate that Paroxysmal atrial fibrillation (PAF) prediction is possible with very high specificity and selectivity from recordings made with a simple hand-help device
This study shows that analysis of ECG entropy, using LZ’76 complexity, has potential for diagnosing PAF from sinus rhythm
Summary
Atrial fibrillation (AF) is the most frequently encountered sustained cardiac arrhythmia, affecting about 2% of the population. AF is associated with an acceleration of cognitive decline and risk of dementia (Singh-Manoux et al, 2017). It is associated with a fivefold increased risk of ischaemic stroke, as Prediction of Paroxysmal Atrial Fibrillation well as increased stroke severity, mortality and disability relative to those arising from other causes (Dulli et al, 2003). Patients suffering a recurrent stroke are almost twice as likely to have identifiable AF as those presenting with a primary stroke (30 vs 17%; Han et al, 2018), reporting rates are likely underestimated (Jorfida et al, 2016). AF is detected by continuous or periodic electrocardiographic monitoring over extended periods (Kirchhof et al, 2016), using invasive or non-invasive methods (Seet et al, 2011), which can be costly and require patient cooperation
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
