The application of nonlinear metrics to assess organization differences in short recordings of paroxysmal and persistent atrial fibrillation.
Atrial fibrillation (AF) is the most common arrhythmia in clinical practice. In the first stages of the disease, AF may terminate spontaneously and it is referred to as paroxysmal AF. The arrhythmia is called persistent AF when external intervention is required to its termination. In the present work, a method to non-invasively assess AF organization has been applied to discern between paroxysmal and persistent AF episodes at any time. Previous works have suggested that the probability of AF termination is inversely related to the number of reentries wandering throughout the atrial tissue. Given that it has also been hypothesized that the number of reentries is directly correlated with AF organization, a fast and robust method able to assess organization differences in AF could be of great interest. In fact, the distinction between paroxysmal and persistent episodes in patients without previously known AF history, making use of short ECG recordings, could contribute to taking earlier decisions on AF management in daily clinical practice, without the need to require 24 h or 48 h Holter recordings. The method was based on a nonlinear regularity index, such as sample entropy (SampEn), and evidenced to be a significant discriminator of the AF type. Its diagnostic accuracy of 91.80% was demonstrated to be superior to previously proposed parameters, such as dominant atrial frequency (DAF) and fibrillatory waves amplitude, and to others analyzed for the first time in this context, such as atrial activity mean power, 3 dB bandwidth around the DAF, first harmonic frequency, harmonic exponential decay, etc. Additionally, according to previous invasive works, paroxysmal AF episodes (0.0716 +/- 0.0143) presented lower SampEn values and, consequently, more organized activity, than persistent episodes (0.1080 +/- 0.0145).
Alcaraz
Raúl
R
Innovation in Bioengineering Research Group, University of Castilla La Mancha, Campus Universitario, 16071 Cuenca, Spain. raul.alcaraz@uclm.es
Rieta
José Joaquín
JJ
D000368:Aged; D000704:Analysis of Variance; D001281:Atrial Fibrillation / Q000175:diagnosis* / Q000503:physiopathology*; D015716:Electrocardiography, Ambulatory / Q000379:methods*; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D017711:Nonlinear Dynamics; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors