Pressure, Flow Rate and Operating Speed Characteristics of a Continuous Flow Left Ventricular Assist Device During Varying Speed Support

Bozkurt, Selim

doi:10.1109/access.2020.3009264

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…As displayed in Figure 9, during AVC, the left ventricle and CF‐LVAD can work in series model (Figure 9B); a significant change in the aortic valve hemodynamics was observed secondary to the pulsatile flow generated from natural ventricular contraction and aortic root pressure 3,13 . It has been established that AVC is associated with arterial pulsatility weakening, vascular wall remodeling, increased inflammatory reaction, gastrointestinal bleeding, and aortic insufficiency (AI) 14–17 . Dobarro et al reported that AVC could cause a decrease in the overall survival rate in patients supported with CF‐LVAD, inducing damage to the left ventricle 18 .…”

Section: Discussionmentioning

confidence: 99%

Factors influencing the functional status of aortic valve in ovine models supported by continuous‐flow left ventricular assist device

Shi

Zang

et al. 2022

Artificial Organs

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Objectives An acute animal experiment was performed to observe factors influencing the functional status of the aortic valve functional status after continuous‐flow left ventricular assist device (CF‐LVAD) implantation in an ovine model, and a physiologic predictive model was established. Methods A CF‐LVAD model was established in Small Tail Han sheep. The initial heart rate (HR) was set to 60 beats/min, and grouping was performed at an interval of 20 beats/min. In all groups, the pump speed was started from 2000 rpm and was gradually increased by 50–100 rpm. A multi‐channel physiological recorder recorded the HR, aortic pressure, central venous pressure, and left ventricular systolic pressure (LVSP). A double‐channel ultrasonic flowmeter was used to obtain real‐time artificial vascular blood flow (ABF). A color Doppler ultrasound device was applied to assess the aortic valve functional status. Multivariate dichotomous logistic regression was used to screen significant variables for predicting the functional status of the aortic valve. Results Observational studies showed that ABF and the risk of aortic valve closure (AVC) were positively correlated with pump speed at the same HR. Meanwhile, the mean arterial pressure (MAP) was unaltered or slightly increased with increased pump speed. When the pump speed was constant, an increase in HR was associated with a decrease in the size of the aortic valve opening. This phenomenon was accompanied by an initial transient increase in the ABF and MAP, which subsequently decreased. Statistical analysis showed that the AVC was associated with increased pump speed (OR = 1.02, 95% CI = 1.01–1.04, p = 0.001), decreased LVSP (OR = 0.95, 95% CI = 0.91–0.98, p = 0.003), and decreased pulse pressure (OR = 0.82, 95% CI = 0.68–0.96, p = 0.026). ABF or MAP was negatively associated with the risk of AVC (OR < 1). The prediction model of AVC after CF‐LVAD implantation exhibited good differentiation (AUC = 0.973, 95% CI = 0.978–0.995) and calibration performance (Hosmer–Lemeshow χ2 = 9.834, p = 0.277 > 0.05). Conclusions The pump speed, LVSP, ABF, MAP, and pulse pressure are significant predictors of the risk of AVC. Predictive models built from these predictors yielded good performance in differentiating aortic valve opening and closure after CF‐LVAD implantation.

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Section: Discussionmentioning

confidence: 99%

Factors influencing the functional status of aortic valve in ovine models supported by continuous‐flow left ventricular assist device

Shi

Zang

et al. 2022

Artificial Organs

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“…A numerical model describing the pressure (H CF‐LVAD ) and flow rate (Q CF‐LVAD ) relation across HeartMate 3 device 35 was incorporated into the cardiovascular system model to simulate heart pump support. CF‐LVAD support was simulated as shown below 36

H_{CF - LVAD} = k n_{CF - LVAD}^{2} - R_{CF - LVAD} Q_{CF - LVAD} - L_{CF - LVAD} \frac{{dQ}_{italicCF - italicLVAD}}{italicdt} + H_{italicrec},

R_{CF - LVAD} = R_{1} n_{CF - LVAD} + R_{2} Q_{CF - LVAD},

\frac{{dr}_{lv}}{italicdt} = \frac{3 (Q_{italicmv} - Q_{italicav} - Q_{CF - LVAD})}{4 {italicπK}_{italiclv} l_{italiclv}} {((), \frac{3 V_{italiclv}}{2 {italicπK}_{italiclv} l_{italiclv}})}^{- 1 / 2},

\frac{{dp}_{ao}}{italicdt} = \frac{Q_{italicav} + Q_{CF - LVAD} - Q_{italicao}}{C_{ao}} .

…”

Section: Methodsmentioning

confidence: 99%

Computational evaluation of heart failure and continuous flow left ventricular assist device support in anaemia

Bozkurt

2023

Numer Methods Biomed Eng

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Anaemia is common in end‐stage heart failure patients supported with continuous flow left ventricular assist device (CF‐LVAD) and is associated with adverse outcomes such as heart failure readmission. This study evaluates the haemodynamic effects of anaemia on cardiac function and cerebral blood flow in heart failure patients supported with CF‐LVAD using computational simulations. A dynamic model simulating cardiac function, systemic, pulmonary and cerebral circulations, cerebral flow autoregulatory mechanisms and gas contents in blood was used to evaluate the effects of anaemia and iron deficiency in heart failure and during CF‐LVAD support. CF‐LVAD therapy was simulated by a model describing HeartMate 3. Anaemia and iron deficiency were simulated by reducing the haemoglobin level from 15 to 9 g/dL and modifying scaling coefficients in the models simulating heart chamber volumes. Reduced haemoglobin levels decreased the arterial O2 content, which increased cerebral blood flow rate by more than 50% in heart failure and during CF‐LVAD assistance. Reduced haemoglobin levels simulating anaemia had minimal effect on the arterial and atrial blood pressures and ventricular volumes. In contrast, iron deficiency increased end‐diastolic left and right ventricular diameters in heart failure from 6.6 cm to 7 cm and 2.9 cm to 3.1 cm and during CF‐LVAD support from 6.1 to 6.4 cm and 3.1 to 3.3 cm. The developed numerical model simulates the effects of anaemia in failing heart and during CF‐LVAD therapy. It is in good agreement with clinical data and can be utilised to assess CF‐LVAD therapy.

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Interaction of a Ventricular Assist Device With Patient-Specific Cardiovascular Systems: In-Silico Study With Bidirectional Coupling

Hahne,

Crone,

Thomas

et al. 2024

ASAIO Journal

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Ventricular assist devices (VADs) are used to assist the heart function of patients with advanced heart failure. Computational fluid dynamics in VADs are widely applied in the development and optimization, for example, to evaluate blood damage. For these simulations, the pulsating operating conditions, in which the VAD operates, should be included accurately. Therefore, this study aims to evaluate the flow in a VAD by interacting with patient-specific cardiovascular systems of heart failure patients. A numeric method will be presented, which includes a patient-specific cardiovascular system model that is bidirectionally coupled with a three-dimensional (3D) flow simulation of the HeartMate 3. The cardiovascular system is represented by a lumped parameter model. Three heart failure patients are considered, based on clinical data from end-stage heart failure patients. Various parameters of the cardiovascular system and the VAD are analyzed, for example, flow rates, pressures, VAD heads, and efficiencies. A further important parameter is the blood damage potential of the VAD, which varies significantly among different patients. Moreover, the predicted blood damage fluctuates within a single heartbeat. The increase in blood damage is evaluated based on the operating conditions. Both, overload and especially partial load conditions during the pulsating operation result in elevated blood damage.

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Pressure, Flow Rate and Operating Speed Characteristics of a Continuous Flow Left Ventricular Assist Device During Varying Speed Support

Cited by 4 publications

References 30 publications

Factors influencing the functional status of aortic valve in ovine models supported by continuous‐flow left ventricular assist device

Factors influencing the functional status of aortic valve in ovine models supported by continuous‐flow left ventricular assist device

Computational evaluation of heart failure and continuous flow left ventricular assist device support in anaemia

Interaction of a Ventricular Assist Device With Patient-Specific Cardiovascular Systems: In-Silico Study With Bidirectional Coupling

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