BACKGROUND: Atrial fibrillation is usually thought of as a "random" pattern of circulating wavelets. However, local atrial activation should be influenced by the constant anatomy and receding tail of refractoriness from the previous activation. The general tendency for wave fronts to follow paths of previous excitation has been termed "linking." We examined intra-atrial electrograms recorded during atrial fibrillation for evidence of linking. METHODS AND RESULTS: Two minutes of atrial fibrillation were recorded in 15 patients with an orthogonal catheter. We have previously demonstrated that this catheter can be used to detect changes in the direction of local atrial activation. A mean vector was calculated for each electrogram. The similarity of the direction of the vectors from two consecutive electrograms can be quantified on a scale of 1 to -1 by calculating the cosine (cos) of the smallest angle (theta) between them. Two vectors pointing in the same or opposite directions then have cos(theta) = 1 or -1, respectively. For the entire group of patients, mean cos(theta) was significantly greater than 0 (mean, 0.36; p less than 0.001). In nine of 15 patients, there were groups of six or more consecutive beats (total, 44 groups; range, six to 14 beats per group) in which the direction of activation of each beat was within 30 degrees of the previous beat. The likelihood of one group of six or 14 consecutive similar beats occurring by chance in any one patient in 1 minute is less than 0.05 and less than 0.0000001, respectively. There was a significant correlation (r = 0.90) between the amount of linking during the first and second minutes of atrial fibrillation in each patient. CONCLUSIONS: Transient similarities in the direction of wavelet propagation in the majority of patients with atrial fibrillation is consistent with the presence of transient linking. To our knowledge, this is the first direct evidence that atrial activation during atrial fibrillation in humans is not entirely random.
BACKGROUND:Atrial fibrillation is usually thought of as a "random" pattern of circulating wavelets. However, local atrial activation should be influenced by the constant anatomy and receding tail of refractoriness from the previous activation. The general tendency for wave fronts to follow paths of previous excitation has been termed "linking." We examined intra-atrial electrograms recorded during atrial fibrillation for evidence of linking. METHODS AND RESULTS: Two minutes of atrial fibrillation were recorded in 15 patients with an orthogonal catheter. We have previously demonstrated that this catheter can be used to detect changes in the direction of local atrial activation. A mean vector was calculated for each electrogram. The similarity of the direction of the vectors from two consecutive electrograms can be quantified on a scale of 1 to -1 by calculating the cosine (cos) of the smallest angle (theta) between them. Two vectors pointing in the same or opposite directions then have cos(theta) = 1 or -1, respectively. For the entire group of patients, mean cos(theta) was significantly greater than 0 (mean, 0.36; p less than 0.001). In nine of 15 patients, there were groups of six or more consecutive beats (total, 44 groups; range, six to 14 beats per group) in which the direction of activation of each beat was within 30 degrees of the previous beat. The likelihood of one group of six or 14 consecutive similar beats occurring by chance in any one patient in 1 minute is less than 0.05 and less than 0.0000001, respectively. There was a significant correlation (r = 0.90) between the amount of linking during the first and second minutes of atrial fibrillation in each patient. CONCLUSIONS: Transient similarities in the direction of wavelet propagation in the majority of patients with atrial fibrillation is consistent with the presence of transient linking. To our knowledge, this is the first direct evidence that atrial activation during atrial fibrillation in humans is not entirely random.
Authors: Thomas H Everett; Emily E Wilson; Sander Verheule; Jose M Guerra; Scott Foreman; Jeffrey E Olgin Journal: Am J Physiol Heart Circ Physiol Date: 2006-07-28 Impact factor: 4.733
Authors: Andrew Grace; Stephan Willems; Christian Meyer; Atul Verma; Patrick Heck; Min Zhu; Xinwei Shi; Derrick Chou; Lam Dang; Christoph Scharf; Günter Scharf; Graydon Beatty Journal: JCI Insight Date: 2019-03-21
Authors: Sanjiv M Narayan; Tina Baykaner; Paul Clopton; Amir Schricker; Gautam G Lalani; David E Krummen; Kalyanam Shivkumar; John M Miller Journal: J Am Coll Cardiol Date: 2014-03-13 Impact factor: 24.094