The left ventricular assist device as a patient monitoring system

Using pulsatility responses to breath-hold maneuvers to predict readmission rates in continuous-flow left ventricular assist device patients

BACKGROUND

Dynamic respiratory maneuvers induce heterogenous changes to flow-pulsatility in continuous-flow left ventricular assist device patients. We evaluated the association of these pulsatility responses with patient hemodynamics and outcomes.

METHODS

Responses obtained from HVAD (Medtronic) outpatients during successive weekly clinics were categorized into three ordinal groups according to the percentage reduction in flow-waveform pulsatility (peak-trough flow) upon inspiratory-breath-hold, (%∆P): (1) minimal change (%∆P ≤ 50), (2) reduced pulsatility (%∆P > 50 but <100), (3) flatline (%∆P = 100). Same-day echocardiography and right-heart-catheterization were performed. Readmissions were compared between patients with ≥1 flatline response (F-group) and those without (NF-group).

RESULTS

Overall, 712 responses were obtained from 55 patients (82% male, age 56.4 ± 11.5). When compared to minimal change, reduced pulsatility and flatline responses were associated with lower central venous pressure (14.2 vs. 11.4 vs. 9.0 mm Hg, p = 0.08) and pulmonary capillary wedge pressure (19.8 vs. 14.3 vs. 13.0 mm Hg, p = 0.03), lower rates of ≥moderate mitral regurgitation (48% vs. 13% vs. 10%, p = 0.01), lower rates of ≥moderate right ventricular impairment (62% vs. 25% vs. 27%, p = 0.03), and increased rates of aortic valve opening (32% vs. 50% vs. 75%, p = 0.03). The F-group (n = 28) experienced numerically lower all-cause readmissions (1.51 vs. 2.79 events-per-patient-year [EPPY], hazard-ratio [HR] = 0.67, p = 0.12), reduced heart failure readmissions (0.07 vs. 0.57 EPPY, HR = 0.15, p = 0.008), and superior readmission-free survival (HR = 0.47, log-rank p = 0.04). Syncopal readmissions occurred exclusively in the F-group (0.20 vs. 0 EPPY, p = 0.01).

CONCLUSION

Responses to inspiratory-breath-hold predicted hemodynamics and readmission risk. The impact of inspiratory-breath-hold on pulsatility can non-invasively guide hemodynamic management decisions, patient optimization, and readmission risk stratification.

Estimation of Left Ventricular Stroke Work for Rotary Left Ventricular Assist Devices

Continuous monitoring of left ventricular stroke work (LVSW) may improve the medical management of patients with rotary left ventricular assist devices (LVAD). However, implantable pressure-volume sensors are limited by measurement drift and hemocompatibility. Instead, estimator algorithms derived from rotary LVAD signals may be a suitable alternative. An LVSW estimator algorithm was developed and evaluated in a range of in vitro and ex vivo cardiovascular conditions during full assist (closed aortic valve [AoV]) and partial assist (opening AoV) mode. For full assist, the LVSW estimator algorithm was based on LVAD flow, speed, and pump pressure head, whereas for partial assist, the LVSW estimator combined the full assist algorithm with an estimate of AoV flow. During full assist, the LVSW estimator demonstrated a good fit in vitro and ex vivo (R 2 : 0.97 and 0.86, respectively) with errors of ± 0.07 J. However, LVSW estimator performance was reduced during partial assist, with in vitro : R 2 : 0.88 and an error of ± 0.16 J and ex vivo : R 2 : 0.48 with errors of ± 0.11 J. Further investigations are required to improve the LVSW estimate with partial assist; however, this study demonstrated promising results for a continuous estimate of LVSW for rotary LVADs.

An in vitro model to study suction events by a ventricular assist device: validation with clinical data

Introduction: Ventricular assist devices (LVADs) are a valuable therapy for end-stage heart failure patients. However, some adverse events still persist, such as suction that can trigger thrombus formation and cardiac rhythm disorders. The aim of this study is to validate a suction module (SM) as a test bench for LVAD suction detection and speed control algorithms. Methods: The SM consists of a latex tube, mimicking the ventricular apex, connected to a LVAD. The SM was implemented into a hybrid in vitro-in silico cardiovascular simulator. Suction was induced simulating hypovolemia in a profile of a dilated cardiomyopathy and of a restrictive cardiomyopathy for pump speeds ranging between 2,500 and 3,200 rpm. Clinical data collected in 38 LVAD patients were used for the validation. Clinical and simulated LVAD flow waveforms were visually compared. For a more quantitative validation, a binary classifier was used to classify simulated suction and non-suction beats. The obtained classification was then compared to that generated by the simulator to evaluate the specificity and sensitivity of the simulator. Finally, a statistical analysis was run on specific suction features (e.g., minimum impeller speed pulsatility, minimum slope of the estimated flow, and timing of the maximum slope of the estimated flow). Results: The simulator could reproduce most of the pump waveforms observed in vivo. The simulator showed a sensitivity and specificity and of 90.0% and 97.5%, respectively. Simulated suction features were in the interquartile range of clinical ones. Conclusions: The SM can be used to investigate suction in different pathophysiological conditions and to support the development of LVAD physiological controllers.

Initial clinical validation of a hybrid in silico—in vitro cardiorespiratory simulator for comprehensive testing of mechanical circulatory support systems

Simulators are expected to assume a prominent role in the process of design—development and testing of cardiovascular medical devices. For this purpose, simulators should capture the complexity of human cardiorespiratory physiology in a realistic way. High fidelity simulations of pathophysiology do not only allow to test the medical device itself, but also to advance practically relevant monitoring and control features while the device acts under realistic conditions. We propose a physiologically controlled cardiorespiratory simulator developed in a mixed in silico-in vitro simulation environment. As inherent to this approach, most of the physiological model complexity is implemented in silico while the in vitro system acts as an interface to connect a medical device. As case scenarios, severe heart failure was modeled, at rest and at exercise and as medical device a left ventricular assist device (LVAD) was connected to the simulator. As initial validation, the simulator output was compared against clinical data from chronic heart failure patients supported by an LVAD, that underwent different levels of exercise tests with concomitant increase in LVAD speed. Simulations were conducted reproducing the same protocol as applied in patients, in terms of exercise intensity and related LVAD speed titration. Results show that the simulator allows to capture the principal parameters of the main adaptative cardiovascular and respiratory processes within the human body occurring from rest to exercise. The simulated functional interaction with the LVAD is comparable to the one clinically observed concerning ventricular unloading, cardiac output, and pump flow. Overall, the proposed simulation system offers a high fidelity in silico-in vitro representation of the human cardiorespiratory pathophysiology. It can be used as a test bench to comprehensively analyze the performance of physically connected medical devices simulating clinically realistic, critical scenarios, thus aiding in the future the development of physiologically responding, patient-adjustable medical devices. Further validation studies will be conducted to assess the performance of the simulator in other pathophysiological conditions.