ABSTRACT
For the treatment of terminal heart failure, the therapy with left-ventricular assist devices has already been established. In the systems used today, pump speed does not adjust during physical activity so that cardiac output and exercise capacity remain markedly limited. It is the aim of this study to develop an automatic pump speed control based on filling pressure values in order to improve exercise capacity and quality of life in these patients. Different approaches are planned, to be tested in an in vitro patient simulator. The algorithms aim to match the pump speed with the increased venous return. In addition, preservation of aortic valve function should be taken into account.
Subject(s)
Algorithms , Exercise , Heart-Assist Devices , Heart Failure , Humans , Quality of LifeABSTRACT
Long-term survival after left ventricular assist device (LVAD) implantation in heart failure patients is mainly determined by a sophisticated after-care. Ambulatory visits only take place every 12 weeks. In case of life-threatening complications (pump thrombosis, driveline infection) this might lead to delayed diagnosis and delayed intervention. It is the intention of the international project Medolution (Medical care evolution) to develop new approaches in order to create best structures for telemonitoring of LVAD patients. In the very early period of the project a questionnaire was sent to 180 LVAD patients to evaluate the need and acceptance of telemonitoring. Thereafter, a graphical user interface (GUI) mockup was developed as one of the first steps to improve the continuous contact between the LVAD patient and the physician. As a final goal the Medolution project aims to bundle all relevant informations from different data sources into one platform in order to provide the physician a comprehensive overview of a patient's situation. In the systems background a big data analysis should run permanently and should try to detect abnormalities and correlations as well. At crucial events, a notification system should inform the physician and should provide the causing data via a decision support system. With this new system we are expecting early detection and prevention of common and partially life-threatening complications, less readmissions to the hospital, an increase in quality of life for the patients and less costs for the health care system as well.
