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Related Experiment Video

Updated: Jul 3, 2026

Improving IV Insulin Administration in a Community Hospital

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

Intensive insulin therapy: enhanced Model Predictive Control algorithm versus standard care.

Jeremy J Cordingley¹, Dirk Vlasselaers, Natalie C Dormand

¹Adult Intensive Care Unit, Royal Brompton Hospital, Sydney Street, London, UK. j.cordingley@rbht.nhs.uk

Intensive Care Medicine

|July 29, 2008

Summary

An enhanced Model Predictive Control (eMPC) algorithm effectively managed blood glucose in critically ill patients across two ICUs. This advanced algorithm demonstrated safe and tight glucose control, comparable to standard care, over 72 hours.

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Last Updated: Jul 3, 2026

Improving IV Insulin Administration in a Community Hospital

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

Area of Science:

Critical care medicine
Biomedical engineering
Clinical informatics

Background:

Critically ill patients often experience hyperglycemia, necessitating precise glucose management.
Traditional insulin infusion protocols can lead to glucose variability and suboptimal control.
Advanced control algorithms offer potential for improved glycemic management in intensive care units.

Purpose of the Study:

To evaluate the effectiveness of an enhanced Model Predictive Control (eMPC) algorithm for intravenous insulin infusion.
To assess the eMPC algorithm's ability to achieve tight glucose control in critically ill patients over 72 hours.
To compare the eMPC algorithm's performance against standard care in two distinct intensive care unit (ICU) settings.

Main Methods:

A two-center, open-label, randomized clinical trial comparing eMPC-guided insulin infusion with standard care.
Thirty-four critically ill patients with hyperglycemia were enrolled in two university hospital ICUs.
Patients were randomized to receive insulin infusion guided by the eMPC algorithm or the ICU's standard protocol.

Main Results:

The eMPC algorithm achieved similar time-weighted average glucose concentrations (104 mg/dL) in both ICUs.
Standard care resulted in significantly different glucose concentrations between ICUs (128 vs. 99 mg/dL).
The glucose measurement interval advised by eMPC differed significantly between ICUs (1.1 vs. 1.8 hours).

Conclusions:

The eMPC algorithm demonstrated feasibility for effective and safe tight glucose control in critically ill patients.
The eMPC algorithm provided consistent glycemic control across different ICU management protocols.
Further research is needed to optimize the glucose sampling interval for the eMPC algorithm while minimizing hypoglycemia risk.