Blood Glucose Control With A Software-Algorithm In Intensive Care Unit (ICU) Patients
- Conditions
- Critical Illness
- Interventions
- Other: enhanced model predictive control algorithm (eMPC)
- Registration Number
- NCT00735163
- Lead Sponsor
- B. Braun Melsungen AG
- Brief Summary
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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 20
- Age: > 18 years of age
- Stay in the ICU expected to be > 120 h
- Blood glucose > 110 mg/dl or patient on insulin treatment
- 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
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description A enhanced model predictive control algorithm (eMPC) improved model predictive control algorithm (eMPC) for glycaemic control in ICU patients
- Primary Outcome Measures
Name Time Method percentage of time within the predefined glucose target range of 80-110 mg/dL from start of treatment to the last glucose measurement under treatment
- Secondary Outcome Measures
Name Time Method hypoglycemias (lab) and possible attendant clinical symptoms (e.g. convulsions) from start of treatment to the last glucose measurement under treatment Usability parameters like convenience of alarming function; workload; blood sampling frequency from start of treatment to the last glucose measurement under treatment Concomitant medication including insulin infusion rate, parenteral/enteral nutrition from start of treatment to the last glucose measurement under treatment
Trial Locations
- Locations (1)
Medical University Graz
🇦🇹Graz, Austria