SUBJECTS AND METHODS: This study included 34 subjects (30 males, 59±9 years): 17 PAF patients and 17 gender and age-matched controls, who underwent 24-hour Holter ECG. The dynamics of one hour of normal sinus rhythm before the onset of AF were assessed using 4 different symbolization algorithms, and quantified by Shannon entropy (SE) and Renyi entropy (RE).

RESULTS: The SE, RE and Error-corrected SE (ECSE) were larger in the PAF than the control patients when the raw R-R data was assessed (Algorithm I). However, when reconstructed time series, expressed as the time difference between 2 successive R-R interval, were analyzed (Algorithm II, III and IV), the entropy of the PAF patients were consistently smaller than those of the controls. Of the 4 different symbolization algorithms, algorithms II and III showed a significant difference in the SE, ECSE and RE between the PAF and the control patients (p<0.05). The difference in the RE at q=4 was most significant (p<0.001). Of the various word patterns seen during analysis using algorithms II and III, a marker of heart rate variation, the frequency of (1,1,1) pattern, was two-fold higher than in the control patients. The frequency of this pattern was 1.5-fold higher in the PAF patients when algorithm IV was used. These results suggest that a few specific word patterns are repetitive in a pathologic condition, such as PAF, and the heart rate dynamics were decreased in PAF.

CONCLUSION: HRV analysis by symbolic dynamics may be a useful adjunctive tool for the detection of abnormal heart rate dynamics as a pathophysiological mechanism of PAF.