Abstract
Aims: To assess heart rate complexity changes prior to the onset of atrial fibrillation (AF) using sample entropy. It has been proposed that the autonomic nervous system might have a role in the initiation of AF. Methods and results: The study included 25 patients with lone AF. Each record set contained two 30 min records from 25 subjects. Each patient had 30 min records containing the ECG immediately preceding an episode of AF (pre-AF) and 30 min of ECG during a period distant from any episode of AF (AFd). Sample entropy was used for complexity analysis. The sample entropy of R-R intervals was significantly reduced in the pre-AF period compared with the AFd period (0.45±0.25 vs. 0.78±0.46, P = 0.003). The pre-AF periods were divided into three successive 10 min segments. There was a significant decreasing trend in entropy towards the onset of AF with linear mixed models (P = 0.002). Conclusions: The heart rate complexity is reduced with a significant decreasing trend as assessed by R-R interval entropy prior to the onset of AF. There is a need for well-defined studies with larger patient groups in order to assess the entropy changes further and to look for possible changes, which might predict impending AF episodes.
Original language | English |
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Pages (from-to) | 398-402 |
Number of pages | 5 |
Journal | Europace |
Volume | 8 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2006 |
Keywords
- Atrial fibrillation
- Complexity
- Entropy
- Fractal analysis