INTRODUCTION: Atrial fibrillation (AF) is characterized by an irregularly irregular ("random") heart beat. However, controversy exists whether the ventricular rhythm in AF is truly random. We investigated randomness by constructing three-dimensional RR interval plots (3D plots), allowing identification of "clustering" of RR intervals. It was hypothesized that electrical cardioversion (ECV) would be more effective in AF patients with clustering, because clustering might reflect a higher degree of organization of atrial fibrillatory activity. METHODS AND RESULTS: The study group consisted of 66 patients (44 men and 22 women; mean age 68 +/- 11 years), who were referred for ECV because of persistent AF. Twenty-four-hour Holter recordings were used to construct 3D plots by plotting each RR interval (x axis) against the previous RR interval (y axis) and the number of occurrences of each of these x,y combinations (z axis). A clustering index was calculated as the percentage of beats within the peaks in the 3D plot. Based on the 3D plots, clustering of RR intervals was present in 31 (47%) of the 66 patients. ECV was effective in restoring sinus rhythm in 29 (94%) of these 31 patients, whereas sinus rhythm was restored in only 25 (71%) of the remaining 35 patients without clustering (P = 0.020). The clustering index ranged from <2% in the 12 patients with failed ECV to >8% in the 32 patients with sinus rhythm at the end of the study (4 weeks after the ECV); the clustering index in the 22 patients with a relapse of AF after effective ECV was intermediate (P = 0.034 and P = 0.042, respectively). CONCLUSION: This study indicates that ECV is more effective in restoring sinus rhythm in AF patients with clustering compared to patients in whom no clustering is apparent on 3D plots. In addition, the degree of clustering appears to be predictive of the overall outcome of ECV; the higher the degree of clustering, the higher the likelihood of sinus rhythm at follow-up.
INTRODUCTION:Atrial fibrillation (AF) is characterized by an irregularly irregular ("random") heart beat. However, controversy exists whether the ventricular rhythm in AF is truly random. We investigated randomness by constructing three-dimensional RR interval plots (3D plots), allowing identification of "clustering" of RR intervals. It was hypothesized that electrical cardioversion (ECV) would be more effective in AFpatients with clustering, because clustering might reflect a higher degree of organization of atrial fibrillatory activity. METHODS AND RESULTS: The study group consisted of 66 patients (44 men and 22 women; mean age 68 +/- 11 years), who were referred for ECV because of persistent AF. Twenty-four-hour Holter recordings were used to construct 3D plots by plotting each RR interval (x axis) against the previous RR interval (y axis) and the number of occurrences of each of these x,y combinations (z axis). A clustering index was calculated as the percentage of beats within the peaks in the 3D plot. Based on the 3D plots, clustering of RR intervals was present in 31 (47%) of the 66 patients. ECV was effective in restoring sinus rhythm in 29 (94%) of these 31 patients, whereas sinus rhythm was restored in only 25 (71%) of the remaining 35 patients without clustering (P = 0.020). The clustering index ranged from <2% in the 12 patients with failed ECV to >8% in the 32 patients with sinus rhythm at the end of the study (4 weeks after the ECV); the clustering index in the 22 patients with a relapse of AF after effective ECV was intermediate (P = 0.034 and P = 0.042, respectively). CONCLUSION: This study indicates that ECV is more effective in restoring sinus rhythm in AFpatients with clustering compared to patients in whom no clustering is apparent on 3D plots. In addition, the degree of clustering appears to be predictive of the overall outcome of ECV; the higher the degree of clustering, the higher the likelihood of sinus rhythm at follow-up.
Authors: Eva María Cirugeda Roldan; Sofía Calero; Víctor Manuel Hidalgo; José Enero; José Joaquín Rieta; Raúl Alcaraz Journal: Entropy (Basel) Date: 2020-07-07 Impact factor: 2.524