Key result
Human atrial fibrillation dynamics exhibited a significantly higher number of missing ordinal patterns compared to surrogate data (2.7 vs 0.39, p<0.001), indicating it is not a linear stochastic process.
Observational (n=10)
No
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This study proposes a methodological framework using symbolic representation of intracardiac recordings to determine whether human atrial fibrillation is driven by deterministic or stochastic processes.
Atrial fibrillation (AF) is the most common cardiac arrhythmia in human beings, and is associated with significant morbidity and mortality. The current standard of care includes interventional catheter ablation in selected patients, but the success rate is limited. The major limitation of the current approach to AF is the lack of fundamental understanding of its underlying mechanism. Specifically, it remains unclear whether human AF dynamics are a deterministic or a stochastic process. Here we assess for determinism in human AF by evaluating the properties of the symbolic representation of intracardiac electrical recordings obtained from patients. Specifically, we evaluate (a) the number of the missing ordinal patterns, (b) the rate of missing ordinal pattern decay for increased length of the time series, and (c) the causal-entropy complexity plane of the Bandt-Pompe symbolic representation. When used together, these are powerful tools to detect determinism, even in the presence of experimental noise and brief time series.
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Aronis et al. (2018) conducted an observational in Atrial Fibrillation (n=10). Human atrial fibrillation dynamics (AA interval time series) vs. Iterative amplitude-adjusted, Fourier-transform (IAAFT) surrogate data was evaluated on Number of missing ordinal patterns (MOPs) (p=<0.001). Human atrial fibrillation dynamics exhibited a significantly higher number of missing ordinal patterns compared to surrogate data (2.7 vs 0.39, p<0.001), indicating it is not a linear stochastic process.
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