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Abstract

A continuous-time Markov model is used to analyze electrocardiogram data obtained from a preclinical study in rabbits of five antiarrhythmic compounds. The preclinical protocol and data are introduced briefly. Some theoretical background for finite-state continuous-time Markov chain models is presented. The electrocardiogram data are then modeled as a continuous-time Markov process with the states being five categories of arrhythmias. The Markov model used assumes that the dwell times in the states are independent and exponentially distributed according to a parameter which depends on the antiarrhythmic compound and the arrhythmia state. For the five antiarrhythmic compounds the transition probabilities from state-to-state and the limiting distributions of the process are calculated and compared.

Keywords

Markov chain Transition probability Limiting behavior Arrhythmia

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Application of a Continuous-Time Markov Chain to a Preclinical Study

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