Optimal Management of the Patient with an Episode of Atrial Fibrillation In and Out of the Hospital

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75668/1/j.1540-8167.1999.tb00696.x.pd

Atrial arrhythmogenesis in wild-type and Scn5a+/Δ murine hearts modelling LQT3 syndrome

Long QT(3) (LQT3) syndrome is associated with abnormal repolarisation kinetics, prolonged action potential durations (APD) and QT intervals and may lead to life-threatening ventricular arrhythmias. However, there have been few physiological studies of its effects on atrial electrophysiology. Programmed electrical stimulation and burst pacing induced atrial arrhythmic episodes in 16 out of 16 (16/16) wild-type (WT) and 7/16 genetically modified Scn5a+/Δ (KPQ) Langendorff-perfused murine hearts modelling LQT3 (P < 0.001 for both), and in 14/16 WT and 1/16 KPQ hearts (P < 0.001 for both; Fisher’s exact test), respectively. The arrhythmogenic WT hearts had significantly larger positive critical intervals (CI), given by the difference between atrial effective refractory periods (AERPs) and action potential durations at 90% recovery (APD90), compared to KPQ hearts (8.1 and 3.2 ms, respectively, P < 0.001). Flecainide prevented atrial arrhythmias in all arrhythmogenic WT (P < 0.001) and KPQ hearts (P < 0.05). It prolonged the AERP to a larger extent than it did the APD90 in both WT and KPQ groups, giving negative CIs. Quinidine similarly exerted anti-arrhythmic effects, prolonged AERP over corresponding APD90 in both WT and KPQ groups. These findings, thus, demonstrate, for the first time, inhibitory effects of the KPQ mutation on atrial arrhythmogenesis and its modification by flecainide and quinidine. They attribute these findings to differences in the CI between WT and mutant hearts, in the presence or absence of these drugs. Thus, prolongation of APD90 over AERP gave positive CI values and increased atrial arrhythmogenicity whereas lengthening of AERP over APD90 reduced such CI values and produced the opposite effect

A three-dimensional human atrial model with fiber orientation. Electrograms and arrhythmic activation patterns relationship

The most common sustained cardiac arrhythmias in humans are atrial tachyarrhythmias, mainly atrial fibrillation. Areas of complex fractionated atrial electrograms and high dominant frequency have been proposed as critical regions for maintaining atrial fibrillation; however, there is a paucity of data on the relationship between the characteristics of electrograms and the propagation pattern underlying them. In this study, a realistic 3D computer model of the human atria has been developed to investigate this relationship. The model includes a realistic geometry with fiber orientation, anisotropic conductivity and electrophysiological heterogeneity. We simulated different tachyarrhythmic episodes applying both transient and continuous ectopic activity. Electrograms and their dominant frequency and organization index values were calculated over the entire atrial surface. Our simulations show electrograms with simple potentials, with little or no cycle length variations, narrow frequency peaks and high organization index values during stable and regular activity as the observed in atrial flutter, atrial tachycardia (except in areas of conduction block) and in areas closer to ectopic activity during focal atrial fibrillation. By contrast, cycle length variations and polymorphic electrograms with single, double and fragmented potentials were observed in areas of irregular and unstable activity during atrial fibrillation episodes. Our results also show: 1) electrograms with potentials without negative deflection related to spiral or curved wavefronts that pass over the recording point and move away, 2) potentials with a much greater proportion of positive deflection than negative in areas of wave collisions, 3) double potentials related with wave fragmentations or blocking lines and 4) fragmented electrograms associated with pivot points. Our model is the first human atrial model with realistic fiber orientation used to investigate the relationship between different atrial arrhythmic propagation patterns and the electrograms observed at more than 43000 points on the atrial surface.This work was partially supported by the Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica, Ministerio de Ciencia e Innovacion of Spain (TEC2008-02090), by the Plan Avanza (Accion Estrategica de Telecomunicaciones y Sociedad de la Informacion), Ministerio de Industria Turismo y Comercio of Spain (TSI-020100-2010-469), by the Programa Prometeo 2012 of the Generalitat Valenciana and by the Programa de Apoyo a la Investigacion y Desarrollo de la Universitat Politecnica de Valencia (PAID-06-11-2002). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Tobón Zuluaga, C.; Ruiz Villa, CA.; Heidenreich, E.; Romero Pérez, L.; Hornero, F.; Saiz Rodríguez, FJ. (2013). A three-dimensional human atrial model with fiber orientation. Electrograms and arrhythmic activation patterns relationship. PLoS ONE. 8(2):1-13. https://doi.org/10.1371/journal.pone.0050883S11382Ho SY, Sanchez-Quintana D, Anderson RH (1998) Can anatomy define electric pathways? In: International Workshop on Computer Simulation and Experimental Assessment of Electrical Cardiac Function, Lausanne, Switzerland. 77–86.Tobón C (2009) Evaluación de factores que provocan fibrilación auricular y de su tratamiento mediante técnicas quirúrgicas. Estudio de simulación. Master Thesis Universitat Politècnica de València.Ruiz C (2010) Estudio de la vulnerabilidad a reentradas a través de modelos matemáticos y simulación de la aurícula humana. Doctoral Thesis Universitat Politècnica de València.Tobón C (2010) Modelización y evaluación de factores que favorecen las arritmias auriculares y su tratamiento mediante técnicas quirúrgicas. Estudio de simulación. Doctoral Thesis Universitat Politècnica de València.Henriquez, C. S., & Papazoglou, A. A. (1996). Using computer models to understand the roles of tissue structure and membrane dynamics in arrhythmogenesis. Proceedings of the IEEE, 84(3), 334-354. doi:10.1109/5.486738Grimm, R. A., Chandra, S., Klein, A. L., Stewart, W. J., Black, I. W., Kidwell, G. A., & Thomas, J. D. (1996). Characterization of left atrial appendage Doppler flow in atrial fibrillation and flutter by Fourier analysis. American Heart Journal, 132(2), 286-296. doi:10.1016/s0002-8703(96)90424-xMaleckar, M. M., Greenstein, J. L., Giles, W. R., & Trayanova, N. A. (2009). K+ current changes account for the rate dependence of the action potential in the human atrial myocyte. American Journal of Physiology-Heart and Circulatory Physiology, 297(4), H1398-H1410. doi:10.1152/ajpheart.00411.200