Key result
A synchronization theory-based algorithm classified 10 atrial fibrillation recordings into three types: single driver (n=3), weakly coupled drivers (n=4), and moderately interacting drivers (n=3).
Why the study?
The exact mechanisms of AF have remained elusive, and the complexity, irregular period, and non-local nature of atrial signals make characterising its spatiotemporal organisation very difficult.
Observational (n=10)
Answers are grounded in this paper and cite their sources.
A novel data-processing pipeline based on synchronization theory can classify human atrial fibrillation into distinct spatiotemporal types based on driver interactions, providing mechanistic insights.
I. ABSTRACT Atrial Fibrillation (AF) is a chronic, progressive, and heterogeneous disease, which exhibits irregular and chaotic atrial electrical activity. The exact mechanisms of AF have remained elusive. The complexity of the atrial signals, irregular period, and the non-local nature of AF make it very difficult to characterize its spatiotemporal organization. This paper presents a set of data-processing tools to find and evaluate the intracardiac signals in AF based on synchronization theory. Specifically, a graph-theoretical algorithm is developed to prune spurious detections of atrial complexes (spikes). The processing pipeline was applied to 10 intracardiac recordings obtained during ablation procedures in patients with paroxysmal or persistent AF. The AF cases were classified into three main types. Type I (n=3) is defined as the presence of a single driver that dominates both atria and is consistent with the mother rotor hypothesis. The majority of the cases had more than one driver and were classified as types II (n=4) and III (n=3). The drivers, i.e., the interacting organized areas, in type II have significantly different peak frequencies and are only weakly coupled. The drivers in type III have close frequencies, are moderately interacting, and show evidence of transient intermittent phase-locking (intermittency). In addition, a long-distance correlation between channels from the left and right atria was observed. The theory of synchronization is a useful conceptual framework to process and analyze AF and can provide mechanistic insight into AF and the effect of various interventions.
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Shahriar Iravanian (2021) conducted an observational in Atrial Fibrillation (n=10). Data-processing tools based on synchronization theory was evaluated on Classification of AF driver types. A synchronization theory-based algorithm classified 10 atrial fibrillation recordings into three types: single driver (n=3), weakly coupled drivers (n=4), and moderately interacting drivers (n=3).
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