Tight Glycemic Control by eMPC Algorithm in Medical ICU Patients.
Primary Purpose
Critically Ill Patients, Mechanical Ventilation, Hyperglycemia
Status
Completed
Phase
Not Applicable
Locations
Austria
Study Type
Interventional
Intervention
insulin titration applying a computer algorithm
Sponsored by
About this trial
This is an interventional treatment trial for Critically Ill Patients focused on measuring algorithm, insulin, hyperglycemia, tight glycemic control, intensive care, adults
Eligibility Criteria
Inclusion Criteria:
- Mechanical ventilation
- Increased blood glucose levels during ICU care (> 110 mg/dL; > 6.1 mM) or patient on current insulin treatment.
- Age of patients in the range from 18 to 90 years.
Exclusion Criteria:
- Known or suspected allergy against insulin.
- Any disease or condition which the Investigator or the treating physician feels would interfere with the trial or the safety of the patient.
- Patients participating in another study.
- Moribund patients likely to die in the next 24 hours.
- Disabled patients
Sites / Locations
- Medical University Graz
Outcomes
Primary Outcome Measures
Hyperglycemic Index
Secondary Outcome Measures
Number of hypoglycaemic episodes (BG < 40 mg/dl (< 2.2mM) [10] )
Mean glucose
Sampling interval
Insulin need
Full Information
NCT ID
NCT00460252
First Posted
April 12, 2007
Last Updated
April 12, 2007
Sponsor
Medical University of Graz
1. Study Identification
Unique Protocol Identification Number
NCT00460252
Brief Title
Tight Glycemic Control by eMPC Algorithm in Medical ICU Patients.
Official Title
An Open, Mono-Centre Randomised Controlled Trial to Investigate the Feasibility of Blood Glucose Control With the Software-Algorithm eMPC (Enhanced Model Predictive Control) Via the Arterial-Intravenous Route in Patients at the Medical Intensive Care Unit.
Study Type
Interventional
2. Study Status
Record Verification Date
April 2007
Overall Recruitment Status
Completed
Study Start Date
May 2006 (undefined)
Primary Completion Date
undefined (undefined)
Study Completion Date
November 2006 (Actual)
3. Sponsor/Collaborators
Name of the Sponsor
Medical University of Graz
4. Oversight
Data Monitoring Committee
No
5. Study Description
Brief Summary
This is an open mono-centre randomised controlled trial performed at the Medical University Graz including a treatment visit (V1). In the treatment visit (V1) after admittance to the ICU arterial blood glucose values will be monitored and either the software-algorithm eMPC will be used to adjust the infusion rate of intravenously administered human soluble insulin to normalise arterial blood glucose or routine treatment will be used to establish tight glycaemic control. The treatment visit will last for 72 hours.
The primary hypothesis of the study is that blood glucose control by the eMPC algorithm is not inferior compared to the implemented routine protocol.
Detailed Description
Hyperglycaemia is commonly found in critically ill patients. The stress of critical illness induces glucose counterregulatory hormones and a number of alterations in carbohydrate metabolism, including increased peripheral glucose demands, enhanced hepatic glucose production, insulin resistance and relative insulin deficiency. Moreover, clinical interventions, such as corticoids, vasopressors, and enteral or parenteral nutrition, further predispose these patients to elevated blood glucose levels. In patients in intensive care as well as in general hospital settings patients with hyperglycemia have higher mortality rates. Recent studies demonstrated that tight blood glucose control in ICU patients results in a significant better outcome for the patients.
Based on this emerging clinical evidence, there are increasing efforts world-wide to maintain strict glycaemic control in critically ill patients. However, achieving this goal requires extensive nursing efforts, including frequent bedside glucose monitoring and the implementation of complex intensive insulin infusion protocols and such increased work demands may not be readily accepted by a busy ICU nursing staff.
The development of a closed loop control system that automatically infuses insulin on the basis of glucose measurements could permit strict glycaemic control and improve clinical outcome without increasing workload of the ICU nursing staff. The EU founded project CLINICIP (Closed Loop Infusion in Critically ill patients) aims to develop a low-risk monitoring and control system which allows maintaining metabolic control in intensive care units. As a first step a local bedside semi-closed system will be developed. Based on arterial spot measurement, an adaptive control algorithm will generate advice and thus represent a decision supporting system for the ICU nursing staff. This control algorithm was adapted for patients in the ICU. The first study using this algorithm was performed at the Medical University Hospital in Graz. In all six patients, who were included in this feasibility trial, blood glucose levels could be normalised and maintained in the narrow target range for up to 24 hours without a single hypoglycaemic episode. Subsequently, the algorithm was tested in a multicentric randomized controlled trial setting and showed superiority by means of a reduced number of hypoglycaemic events and a higher percentage of glucose values within the target range as compared to routine care glucose management protocols. In this study it was a fact that the hourly sampling frequency in the algorithm group has positively influenced the outcome in the algorithm group. Therefore in an enhanced version of the algorithm (eMPC) the sampling interval is expanded up to 240 min.
The purpose of this study is to evaluate the feasibility of this enhanced model predictive control algorithm for glycaemic control in critically ill patients compared to routine treatment.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Critically Ill Patients, Mechanical Ventilation, Hyperglycemia
Keywords
algorithm, insulin, hyperglycemia, tight glycemic control, intensive care, adults
7. Study Design
Primary Purpose
Treatment
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
None (Open Label)
Allocation
Randomized
Enrollment
50 (false)
8. Arms, Groups, and Interventions
Intervention Type
Procedure
Intervention Name(s)
insulin titration applying a computer algorithm
Primary Outcome Measure Information:
Title
Hyperglycemic Index
Secondary Outcome Measure Information:
Title
Number of hypoglycaemic episodes (BG < 40 mg/dl (< 2.2mM) [10] )
Title
Mean glucose
Title
Sampling interval
Title
Insulin need
10. Eligibility
Sex
All
Minimum Age & Unit of Time
18 Years
Maximum Age & Unit of Time
90 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
Mechanical ventilation
Increased blood glucose levels during ICU care (> 110 mg/dL; > 6.1 mM) or patient on current insulin treatment.
Age of patients in the range from 18 to 90 years.
Exclusion Criteria:
Known or suspected allergy against insulin.
Any disease or condition which the Investigator or the treating physician feels would interfere with the trial or the safety of the patient.
Patients participating in another study.
Moribund patients likely to die in the next 24 hours.
Disabled patients
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Thomas R Pieber, MD.
Organizational Affiliation
Medical University of Graz
Official's Role
Principal Investigator
Facility Information:
Facility Name
Medical University Graz
City
Graz
ZIP/Postal Code
8036
Country
Austria
12. IPD Sharing Statement
Citations:
PubMed Identifier
16443872
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.
Results Reference
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Tight Glycemic Control by eMPC Algorithm in Medical ICU Patients.
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