Abstract
Left ventricular assist devices (LVADs) assure longer survival to patients, but exercise capacity is limited compared to normal values. Overall, LVAD patients show high wedge pressure and low cardiac output during maximal exercise, a phenomenon hinting at the need for increased LVAD support. Clinical studies investigating the hemodynamic benefits of an LVAD speed increase during exercise, ended in inhomogeneous and sometimes contradictory results. The native ventricle-LVAD interaction changes between rest and exercise, and this evolution is complex, multifactorial and patient-specific. The aim of this paper is to provide a comprehensive overview on the patient-LVAD interaction during exercise and to delineate possible therapeutic strategies for the future. A computational cardiorespiratory model was used to simulate the hemodynamics of peak bicycle exercise in LVAD patients. The simulator included the main cardiovascular and respiratory impairments commonly observed in LVAD patients, so as to represent an average hemodynamic response to exercise. In addition, other exercise responses were simulated, by tuning the chronotropic, inotropic and vascular functions, and implementing aortic regurgitation and stenosis in the simulator. These profiles were tested under different LVAD speeds and LVAD pressure-flow characteristics. Simulations output showed consistency with clinical data from the literature. The simulator allowed the working condition of the assisted ventricle at exercise to be investigated, clarifying the reasons behind the high wedge pressure and poor cardiac output observed in the clinics. Patients with poorer inotropic, chronotropic and vascular functions, are likely to benefit more from an LVAD speed increase during exercise. Similarly, for these patients, a flatter LVAD pressure-flow characteristic can assure better hemodynamic support under physical exertion. Overall, the study evidenced the need for a patient-specific approach on supporting exercise hemodynamics. In this frame, a complex simulator can constitute a valuable tool to define and test personalized speed control algorithms and strategies.