Clinical trial NCT00735163: Blood Glucose Control With A Software-Algorithm In Intensive Care Unit (ICU) Patients
Official title: 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
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Critical Illness
Keywords: algorithm
tight glycemic control
glucose control
intensive care
insulin
ICU
Lead sponsor: B. Braun Melsungen AG
Sponsor class: INDUSTRY
First posted: 2008-08-14
Enrollment: 20
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: TREATMENT

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.


Eligibility criteria: 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

Primary outcomes:
measure: percentage of time within the predefined glucose target range of 80-110 mg/dL
timeFrame: from start of treatment to the last glucose measurement under treatment
Secondary outcomes:
measure: hypoglycemias (lab) and possible attendant clinical symptoms (e.g. convulsions)
timeFrame: from start of treatment to the last glucose measurement under treatment
measure: Usability parameters like convenience of alarming function; workload; blood sampling frequency
timeFrame: from start of treatment to the last glucose measurement under treatment
measure: Concomitant medication including insulin infusion rate, parenteral/enteral nutrition
timeFrame: from start of treatment to the last glucose measurement under treatment
Other outcomes:
Locations:
city: Graz
country: Austria
facility: Medical University Graz
Study officials:
affiliation: Medical University of Graz
name: Thomas R Pieber, Prof. Dr.
role: PRINCIPAL_INVESTIGATOR
References:
citation: Plank J, Blaha J, Cordingley J, Wilinska ME, Chassin LJ, Morgan C, Squire S, Haluzik M, Kremen J, Svacina S, Toller W, Plasnik A, Ellmerer M, Hovorka R, Pieber TR. Multicentric, randomized, controlled trial to evaluate blood glucose control by the model predictive control algorithm versus routine glucose management protocols in intensive care unit patients. Diabetes Care. 2006 Feb;29(2):271-6. doi: 10.2337/diacare.29.02.06.dc05-1689.
citation: Pachler C, Plank J, Weinhandl H, Chassin LJ, Wilinska ME, Kulnik R, Kaufmann P, Smolle KH, Pilger E, Pieber TR, Ellmerer M, Hovorka R. Tight glycaemic control by an automated algorithm with time-variant sampling in medical ICU patients. Intensive Care Med. 2008 Jul;34(7):1224-30. doi: 10.1007/s00134-008-1033-8. Epub 2008 Feb 23.