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Methods Inf Med 2014; 53(02): 121-136
DOI: 10.3414/ME13-01-0047
Original Articles
Schattauer GmbH

A Decision Support System for the Treatment of Patients with Ventricular Assist Device Support

E. C. Karvounis
1   Biomedical Research Institute-FORTH, Ioannina, Greece
2   Unit of Medical Technology and Intelligent Information Systems, Dept. of Material Science and Engineering, University of Ioannina, Ioannina, Greece
,
M. G. Tsipouras
1   Biomedical Research Institute-FORTH, Ioannina, Greece
2   Unit of Medical Technology and Intelligent Information Systems, Dept. of Material Science and Engineering, University of Ioannina, Ioannina, Greece
,
A. T. Tzallas
1   Biomedical Research Institute-FORTH, Ioannina, Greece
2   Unit of Medical Technology and Intelligent Information Systems, Dept. of Material Science and Engineering, University of Ioannina, Ioannina, Greece
,
N. S. Katertsidis
1   Biomedical Research Institute-FORTH, Ioannina, Greece
2   Unit of Medical Technology and Intelligent Information Systems, Dept. of Material Science and Engineering, University of Ioannina, Ioannina, Greece
,
K. Stefanou
1   Biomedical Research Institute-FORTH, Ioannina, Greece
2   Unit of Medical Technology and Intelligent Information Systems, Dept. of Material Science and Engineering, University of Ioannina, Ioannina, Greece
,
Y. Goletsis
1   Biomedical Research Institute-FORTH, Ioannina, Greece
3   Department of Economics, University of Ioannina, Ioannina, Greece
,
M. Frigerio
4   Cardiology 2 – Heart Failure and Transplantation Division, “A. De Gasperis” Cardiothoracic and Vascular Department, Niguarda Ca’ Granda Hospital, Milan, Italy
,
A. Verde
4   Cardiology 2 – Heart Failure and Transplantation Division, “A. De Gasperis” Cardiothoracic and Vascular Department, Niguarda Ca’ Granda Hospital, Milan, Italy
,
R. Caruso
5   CNR Institute of Clinical Physiology, Pisa, Italy
,
B. Meyns
6   Department of Cardiac Surgery, University Hospital Leuven, Leuven, Belgium
,
J. Terrovitis
7   3rd Cardiology Department, University of Athens, School of Medicine, Athens, Greece
,
M. G. Trivella
5   CNR Institute of Clinical Physiology, Pisa, Italy
,
D. I. Fotiadis
1   Biomedical Research Institute-FORTH, Ioannina, Greece
2   Unit of Medical Technology and Intelligent Information Systems, Dept. of Material Science and Engineering, University of Ioannina, Ioannina, Greece
› Institutsangaben
Weitere Informationen

Publikationsverlauf

received: 29. April 2013

accepted: 01. Januar 2014

Publikationsdatum:
20. Januar 2018 (online)

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Summary

Background: Heart failure (HF) is affecting millions of people every year and it is characterized by impaired ventricular performance, exercise intolerance and shortened life expectancy. Despite significant advancements in drug therapy, mortality of the disease remains excessively high, as heart transplant remains the gold standard treatment for end-stage HF when no contraindications subsist. Traditionally, implanted Ventricular Assist Devices (VADs) have been employed in order to provide circulatory support to patients who cannot survive the waiting time to transplantation, reducing the workload imposed on the heart. In many cases that process could recover its contractility performance.

Objectives: The SensorART platform focuses on the management and remote treatment of patients suffering from HF. It provides an inter-operable, extendable and VAD-independent solution, which incorporates various hardware and software components in a holistic approach, in order to improve the quality of the patients’ treatment and the workflow of the specialists. This paper focuses on the description and analysis of Specialist’s Decision Support System (SDSS), an innovative component of the SensorART platform.

Methods: The SDSS is a Web-based tool that assists specialists on designing the therapy plan for their patients before and after VAD implantation, analyzing patients’ data, extracting new knowledge, and making informative decisions.

Results: SDSS offers support to medical and VAD experts through the different phases of VAD therapy, incorporating several tools covering all related fields; Statistics, Association Rules, Monitoring, Treatment, Weaning, Speed and Suction Detection.

Conclusions: SDSS and its modules have been tested in a number of patients and the results are encouraging.

Keywords

Heart failure - ventricular assist devices - decision support system
 

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