Blood Glucose Control With A Software-Algorithm In Intensive Care Unit (ICU) Patients

Mono-Centric, Open, Non-Controlled Study To Investigate The Feasibility Of Blood Glucose Control With The Software-Algorithm eMPC (Enhanced Model Predictive Control) In ICU Patients

Hyperglycemia is common in critically ill patients and associated with an adverse outcome. Recently, large randomized controlled trials have demonstrated that tight glycaemic control (TGC) reduces morbidity and mortality in this population. Based on this emerging evidence intensive insulin therapy is currently finding its way into the critical care practice.

In the meantime numerous insulin infusion protocols, which are based on frequent bedside glucose monitoring, have been implemented. Recent reviews comparing different types of protocols describe widely ranging practice and difficulties in achieving TGC despite extensive efforts of the intensive care unit (ICU) staff. A fully automated algorithm may help to overcome some of these limitations by excluding intuitive interventions and integrating relevant clinical data in the decision-making process. The primary objective of the current study is to investigate the performance (efficacy) of a control algorithm for glycaemic control in ICU patients for the whole length of ICU stay.

Inclusion Criteria:

• Age: > 18 years of age
• Stay in the ICU expected to be > 120 h
• Blood glucose > 110 mg/dl or patient on insulin treatment

Exclusion Criteria:

• Patients with hyperglycaemic crisis/ketoacidosis due to insulin deficiency.
• Known or suspected allergy to insulin
• Any disease or condition which the investigator or treating physician feels would interfere with the trial or the safety of the patient (i.e., liver failure, other fatal organ failures)
• Moribund patients likely to die within 24 hours