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Observable Atrial and Ventricular Fibrillation Episode Durations Are Conformant With a Power Law Based on System Size
Dhani Dharmaprani1,2, Kathryn Tiver1,3, Sobhan Salari Shahrbabaki1
1College of Medicine and Public Health, Flinders University (D.D., K.T., S.S.S., E.V.J., D.C., C.S., J.X.Q., I.T., A.N.G.).
Circulation. Arrhythmia and Electrophysiology
|June 28, 2024
Summary
Fibrillation episode durations, including atrial fibrillation (AF) and ventricular fibrillation (VF), follow a power law related to system size and correlation length. This finding provides a quantitative framework for understanding fibrillation episode duration.
Area of Science:
- Computational Biology
- Cardiac Electrophysiology
- Nonlinear Dynamics
Background:
- Atrial fibrillation (AF) and ventricular fibrillation (VF) episodes vary in duration, with a lack of quantitative frameworks to explain these differences.
- Understanding the factors influencing fibrillation episode duration is crucial for predicting and managing cardiac arrhythmias.
Purpose of the Study:
- To test the hypothesis that observable self-terminating atrial fibrillation (AF) and ventricular fibrillation (VF) episode lengths conform to a power law.
- To establish a quantitative relationship between episode duration and the ratio of system size to correlation length ([Formula: see text]).
Main Methods:
- Utilized computer simulations (2D and 3D) and clinical recordings from human VF (n=12) and AF (n=51) patients.
- Assessed power law conformance using Akaike information criterion, Bayesian information criterion, R², and maximum likelihood estimation.
- Calculated [Formula: see text] as the ratio of system size (chamber/simulation size) to correlation length (xi).
Main Results:
- All computer models and clinical AF/VF recordings demonstrated conformance with a power law relationship between episode durations and [Formula: see text] (R² values ranging from 0.61 to 0.92, P<0.001).
- The [Formula: see text] ratio effectively differentiated between self-terminating and sustained AF/VF episodes (P<0.001) and between paroxysmal and persistent AF (P<0.001).
- Other electrogram metrics, including dominant frequency and Shannon Entropy, showed no significant differences.
Conclusions:
- Observable fibrillation episode durations in both simulations and clinical data are quantitatively described by a power law based on system size and correlation length.
- This power law framework offers a novel approach to understanding and potentially predicting the duration of cardiac fibrillation episodes.
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