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

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 (n = 12) was compared with a control (C) group (n = 12) 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.