About this Journal Submit a Manuscript Table of Contents
BioMed Research International
Volume 2013 (2013), Article ID 186439, 8 pages
http://dx.doi.org/10.1155/2013/186439
Research Article

The Use of Continuous Glucose Monitoring Combined with Computer-Based eMPC Algorithm for Tight Glucose Control in Cardiosurgical ICU

1Department of Anaesthesia, Resuscitation and Intensive Medicine, 1st Faculty of Medicine and General University Hospital, Charles University in Prague, U Nemocnice 2, 128 08 Prague 2, Czech Republic
2Third Department of Medicine, 1st Faculty of Medicine and General University Hospital, Charles University in Prague, U Nemocnice 1, 128 08 Prague 2, Czech Republic
3Department of Cardiac Surgery, 1st Faculty of Medicine and General University Hospital, Charles University in Prague, U Nemocnice 2, 128 08 Prague 2, Czech Republic
4Institute of Metabolic Science, University of Cambridge, Addenbrooke's Hospital, Box 289, Cambridge CB2 0QQ, UK

Received 7 September 2012; Revised 19 December 2012; Accepted 20 December 2012

Academic Editor: Sharad Rastogi

Copyright © 2013 Petr Kopecký et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Aim. In postcardiac surgery patients, we assessed the performance of a system for intensive intravenous insulin therapy using continuous glucose monitoring (CGM) and enhanced model predictive control (eMPC) algorithm. Methods. Glucose control in eMPC-CGM group ( ) was compared with a control (C) group ( ) treated by intravenous insulin infusion adjusted according to eMPC protocol with a variable sampling interval alone. In the eMPC-CGM group glucose measured with a REAL-Time CGM system (Guardian RT) served as input for the eMPC adjusting insulin infusion every 15 minutes. The accuracy of CGM was evaluated hourly using reference arterial glucose and Clarke error-grid analysis (C-EGA). Target glucose range was 4.4–6.1 mmol/L. Results. Of the 277 paired CGM-reference glycemic values, 270 (97.5%) were in clinically acceptable zones of C-EGA and only 7 (2.5%) were in unacceptable D zone. Glucose control in eMPC-CGM group was comparable to C group in all measured values (average glycemia, percentage of time above, within, and below target range,). No episode of hypoglycemia (<2.9 mmol) occurred in eMPC-CGM group compared to 2 in C group. Conclusion. Our data show that the combination of eMPC algorithm with CGM is reliable and accurate enough to test this approach in a larger study population.