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In Vitro Comparison of Active and Passive Physiological Control Systems for Biventricular Assist Devices

Overview of attention for article published in Annals of Biomedical Engineering, August 2015
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Title
In Vitro Comparison of Active and Passive Physiological Control Systems for Biventricular Assist Devices
Published in
Annals of Biomedical Engineering, August 2015
DOI 10.1007/s10439-015-1425-1
Pubmed ID
Authors

Jo P. Pauls, Michael C. Stevens, Emma Schummy, Geoff Tansley, John F. Fraser, Daniel Timms, Shaun D. Gregory

Abstract

The low preload and high afterload sensitivities of rotary ventricular assist devices (VADs) may cause ventricular suction events or venous congestion. This is particularly problematic with rotary biventricular support (BiVAD), where the Starling response is diminished in both ventricles. Therefore, VADs may benefit from physiological control systems to prevent adverse events. This study compares active, passive and combined physiological controllers for rotary BiVAD support with constant speed mode. Systemic (SVR) and pulmonary (PVR) vascular resistance changes and exercise were simulated in a mock circulation loop to evaluate the capacity of each controller to prevent suction and congestion and increase exercise capacity. All controllers prevented suction and congestion at high levels of PVR (900 dynes s cm(-5)) and SVR (3000 dynes s cm(-5)), however these events occurred in constant speed mode. The controllers increased preload sensitivity (0.198-0.34 L min(-1) mmHg(-1)) and reduced afterload sensitivity (0.0001-0.008 L min(-1) mmHg(-1)) of the VADs when compared to constant speed mode (0.091 and 0.072 L min(-1) mmHg(-1) respectively). The active controller increased pump speeds (400-800 rpm) and pump flow by 2.8 L min(-1) during exercise, thus increasing exercise capacity. By reducing suction and congestion and by increasing exercise capacity, the control systems presented in this study may help increase quality of life of VAD patients.

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Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 6 20%
Student > Ph. D. Student 6 20%
Student > Bachelor 4 13%
Student > Postgraduate 2 7%
Researcher 2 7%
Other 1 3%
Unknown 9 30%
Readers by discipline Count As %
Engineering 10 33%
Medicine and Dentistry 5 17%
Agricultural and Biological Sciences 1 3%
Biochemistry, Genetics and Molecular Biology 1 3%
Nursing and Health Professions 1 3%
Other 1 3%
Unknown 11 37%