Atrial fibrillation (AF) incidence is high in end-stage renal disease (ESRD) patients, and haemodialysis (HD) session may induce paroxysmal AF episodes. Structural atrium remodelling is common in ESRD patients, moreover, HD session induces rapid plasma electrolytes and blood volume changes, possibly favouring arrhythmia onset. Therefore, HD session represents a unique model to study in vivo the mechanisms potentially inducing paroxysmal AF episodes. Here, we present the case report of a patient in which HD regularly induced paroxysmal AF. In four consecutive sessions, heart rate variability analysis showed a progressive reduction of low/high frequency ratio before the AF onset, suggesting a relative increase in vagal activity. Moreover, all AF episodes were preceded by a great increase of supraventricular ectopic beats. We applied computational modelling of cardiac cellular electrophysiology to these clinical findings, using plasma electrolyte concentrations and heart rate to simulate patient conditions at the beginning of HD session (pre-HD) and right before the AF onset (pre-AF), in a human atrial action potential model. Simulation results provided evidence of a slower depolarization and a shortened refractory period in pre-AF vs. pre-HD, and these effects were enhanced when adding acetylcholine effect. Paroxysmal AF episodes are induced by the presence of a trigger that acts upon a favourable substrate on the background of autonomic nervous system changes and in the described case report all these three elements were present. Starting from these findings, here we review the possible mechanisms leading to intradialytic AF onset.

Vincenti, A., Passini, E., Fabbrini, P., Luise, M., Severi, S., Genovesi, S. (2014). Recurrent intradialytic paroxysmal atrial fibrillation: hypotheses on onset mechanisms based on clinical data and computational analysis. EUROPACE, 16(3), 396-404 [10.1093/europace/eut346].

Recurrent intradialytic paroxysmal atrial fibrillation: hypotheses on onset mechanisms based on clinical data and computational analysis

GENOVESI, SIMONETTA CARLA
2014

Abstract

Atrial fibrillation (AF) incidence is high in end-stage renal disease (ESRD) patients, and haemodialysis (HD) session may induce paroxysmal AF episodes. Structural atrium remodelling is common in ESRD patients, moreover, HD session induces rapid plasma electrolytes and blood volume changes, possibly favouring arrhythmia onset. Therefore, HD session represents a unique model to study in vivo the mechanisms potentially inducing paroxysmal AF episodes. Here, we present the case report of a patient in which HD regularly induced paroxysmal AF. In four consecutive sessions, heart rate variability analysis showed a progressive reduction of low/high frequency ratio before the AF onset, suggesting a relative increase in vagal activity. Moreover, all AF episodes were preceded by a great increase of supraventricular ectopic beats. We applied computational modelling of cardiac cellular electrophysiology to these clinical findings, using plasma electrolyte concentrations and heart rate to simulate patient conditions at the beginning of HD session (pre-HD) and right before the AF onset (pre-AF), in a human atrial action potential model. Simulation results provided evidence of a slower depolarization and a shortened refractory period in pre-AF vs. pre-HD, and these effects were enhanced when adding acetylcholine effect. Paroxysmal AF episodes are induced by the presence of a trigger that acts upon a favourable substrate on the background of autonomic nervous system changes and in the described case report all these three elements were present. Starting from these findings, here we review the possible mechanisms leading to intradialytic AF onset.
Articolo in rivista - Articolo scientifico
Electrolytes; P-wave; Haemodialysis; Computational modelling; Atrial fibrillation
English
2014
16
3
396
404
none
Vincenti, A., Passini, E., Fabbrini, P., Luise, M., Severi, S., Genovesi, S. (2014). Recurrent intradialytic paroxysmal atrial fibrillation: hypotheses on onset mechanisms based on clinical data and computational analysis. EUROPACE, 16(3), 396-404 [10.1093/europace/eut346].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/50488
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