Atrial fibrillation in continuous flow-left ventricular assist device (CF-LVAD) patients: impact on pathophysiology

TL;DR

This review explores how atrial fibrillation affects the physiology and outcomes of patients with continuous flow-left ventricular assist devices.

Contribution

The paper highlights the need for AI-driven technologies to identify novel risk factors for atrial fibrillation in LVAD patients.

Findings

Atrial fibrillation is common in CF-LVAD patients and can lead to complications like pump thrombosis and stroke.

Atrial fibrillation contributes to the progression of right ventricular failure and valvular regurgitation.

AI technologies may help identify risk factors for atrial fibrillation, especially in diverse populations.

Abstract

Continuous Flow -Left Ventricular Assist Devices (CF-LVADs) remain the mainstay in end stage HFrEF patients with refractory Stage D HF. AF is common in patients supported on CF-LVADs, with a significantly increasing number developing new-onset AF post LVAD implantation. This review will summarize the effects of atrial fibrillation on LVAD physiology and its impact on outcomes. Literature search for this qualitative review was done using Google Scholar and PubMed. Only studies in adult human LVAD patients were included. The keywords used were atrial fibrillation in LVADs, effect of atrial fibrillation on functional mitral regurgitation /tricuspid regurgitation, effect on right ventricular failure, pump thrombosis and stroke and gender differences in outcomes.The main aspects addressed are effect on LVAD hemodynamics, the complexinteractions between low pulse pressure and atrial fibrillation leading to pump thrombosis and stroke , the role of atrial fibrillation in the initiation and progression ofright ventricular failure, impact on valvular regurgitation (Functional Mitral /TricuspidRegurgitation), utility of Cardiac Resynchronization Therapy post LVAD implant anduse of AI-driven technologies in risk factor identification to help identify novel risk factors important in predicting prognosis to improve outcomes. Use of AI technologies to identify novel risk factors for atrial fibrillation post LVADsurgery is warranted in the context of race, ethnicity and gender. Further studies areneeded to address optimal pacing strategies in LVAD patients with cardiac resynchronization therapy to institute guidelines for use of this therapy post LVAD implantation especially in the context of co-existing atrial fibrillation.

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