Markov Chain Models for Cardiac Rhythm Dynamics in Patients Undergoing Catheter Ablation of Atrial Fibrillation

Tae Jin Lee; Adam E. Berman; Arni S.R.Srinivasa Rao

doi:10.1007/s11538-023-01125-8

Markov Chain Models for Cardiac Rhythm Dynamics in Patients Undergoing Catheter Ablation of Atrial Fibrillation

Tae Jin Lee, Adam E. Berman, Arni S.R.Srinivasa Rao

Research output: Contribution to journal › Article › peer-review

Abstract

We have developed a novel Markov Chain modeling system that considers vectors of patients with atrial fibrillation (AF) by their AF status over a period of time. Our model examines the impact of catheter ablation of AF upon the dynamics of a patient’s AF status and their potential return to sinus rhythm. We prove several theorems to determine the probabilities of patients achieving sinus rhythm or progressing to permanent AF. Additionally, we observed aggregation of patients within the paroxysmal AF state in simulation. The aggregating property of Markov chains illustrated the potential benefits of catheter ablation on healthcare resource allocation.

Original language	English (US)
Article number	34
Journal	Bulletin of Mathematical Biology
Volume	85
Issue number	5
DOIs	https://doi.org/10.1007/s11538-023-01125-8
State	Published - May 2023

Keywords

AF Models
Absorbing and recovery probabilities
Data structures
State spaces
Vector

ASJC Scopus subject areas

General Neuroscience
Immunology
General Mathematics
General Biochemistry, Genetics and Molecular Biology
General Environmental Science
Pharmacology
General Agricultural and Biological Sciences
Computational Theory and Mathematics

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abstract = "We have developed a novel Markov Chain modeling system that considers vectors of patients with atrial fibrillation (AF) by their AF status over a period of time. Our model examines the impact of catheter ablation of AF upon the dynamics of a patient{\textquoteright}s AF status and their potential return to sinus rhythm. We prove several theorems to determine the probabilities of patients achieving sinus rhythm or progressing to permanent AF. Additionally, we observed aggregation of patients within the paroxysmal AF state in simulation. The aggregating property of Markov chains illustrated the potential benefits of catheter ablation on healthcare resource allocation.",

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AB - We have developed a novel Markov Chain modeling system that considers vectors of patients with atrial fibrillation (AF) by their AF status over a period of time. Our model examines the impact of catheter ablation of AF upon the dynamics of a patient’s AF status and their potential return to sinus rhythm. We prove several theorems to determine the probabilities of patients achieving sinus rhythm or progressing to permanent AF. Additionally, we observed aggregation of patients within the paroxysmal AF state in simulation. The aggregating property of Markov chains illustrated the potential benefits of catheter ablation on healthcare resource allocation.

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KW - Data structures

KW - State spaces

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Markov Chain Models for Cardiac Rhythm Dynamics in Patients Undergoing Catheter Ablation of Atrial Fibrillation

Abstract

Keywords

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