SummaryThe

Responses of four rotary blood pumps (Incor, Heartmate II, Heartware, and Duraheart) at a single speed setting to changes in preload and afterload were assessed using the human left ventricle as a benchmark for comparison. Data for the rotary pumps were derived from pressure flow relations reported in the literature while the natural heart was characterized by the Frank-Starling curve adjusted to fit outputs at different afterloads reported in the literature. Preload sensitivity (mean ± SD) for all pumps at all afterloads tested was 0.105 ± 0.092 L/min/mm Hg, while afterload sensitivity was 0.09 ± 0.034 L/min/mm Hg-values that were not significantly different (t-test, P = 0.56). By contrast, preload sensitivity of the natural heart was over twice as high (0.213 ± 0.03 L/min/mm Hg) and afterload sensitivity about one-third (0.03 ± 0.01 L/min/mm Hg) the values recorded for rotary pumps (t-test, P < 0.001). Maximum preload sensitivity and minimum afterload sensitivity allow the right and left ventricles to synchronize outputs without neural or humoral intervention. This theoretical study reinforces the need to provide preload sensitive control mechanisms of sufficient power to enable the pump and left ventricle in combination to adapt to changes in right ventricular output automatically.

These results are different from the published results on which the NICE guidelines were based; however, the evidence base in children is small. There is currently insufficient evidence to support the use of ultrasound guidance for central venous catheterization in children.

A clinically intuitive physiologic controller is desired to improve the interaction between implantable rotary blood pumps and the cardiovascular system. This controller should restore the Starling mechanism of the heart, thus preventing overpumping and underpumping scenarios plaguing their implementation. A linear Starling-like controller for pump flow which emulated the response of the natural left ventricle (LV) to changes in preload was then derived using pump flow pulsatility as the feedback variable. The controller could also adapt the control line gradient to accommodate longer-term changes in cardiovascular parameters, most importantly LV contractility which caused flow pulsatility to move outside predefined limits. To justify the choice of flow pulsatility, four different pulsatility measures (pump flow, speed, current, and pump head pressure) were investigated as possible surrogates for LV stroke work. Simulations using a validated numerical model were used to examine the relationships between LV stroke work and these measures. All were approximately linear (r(2) (mean ± SD) = 0.989 ± 0.013, n = 30) between the limits of ventricular suction and opening of the aortic valve. After aortic valve opening, the four measures differed greatly in sensitivity to further increases in LV stroke work. Pump flow pulsatility showed more correspondence with changes in LV stroke work before and after opening of the aortic valve and was least affected by changes in the LV and right ventricular (RV) contractility, blood volume, peripheral vascular resistance, and heart rate. The system (flow pulsatility) response to primary changes in pump flow was then demonstrated to be appropriate for stable control of the circulation. As medical practitioners have an instinctive understanding of the Starling curve, which is central to the synchronization of LV and RV outputs, the intuitiveness of the proposed Starling-like controller will promote acceptance and enable rational integration into patterns of hemodynamic management.

A lumped parameter model of human cardiovascular-implantable rotary blood pump (iRBP) interaction has been developed based on experimental data recorded in two healthy pigs with the iRBP in situ. The model includes descriptions of the left and right heart, direct ventricular interaction through the septum and pericardium, the systemic and pulmonary circulations, as well as the iRBP. A subset of parameters was optimized in a least squares sense to faithfully reproduce the experimental measurements (pressures, flows and pump variables). Our fitted model compares favorably with our experimental measurements at a range of pump operating points. Furthermore, we have also suggested the importance of various model features, such as the curvilinearity of the end systolic pressure-volume relationship, the Starling resistance, the suction resistance, the effect of respiration, as well as the influence of the pump inflow and outflow cannulae. Alterations of model parameters were done to investigate the circulatory response to rotary blood pump assistance under heart failure conditions. The present model provides a valuable tool for experiment designs, as well as a platform to aid in the development and evaluation of robust physiological pump control algorithms.