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Completed

NCT Number: NCT00735163

Blood Glucose Control With A Software-Algorithm In Intensive Care Unit (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.

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Key information

Conditions

Critical Illness Disease Attributes Glucose Metabolism Disorders Hyperinsulinism Insulin Resistance Metabolic Diseases Nutritional and Metabolic Diseases Pathologic Processes Pathological Conditions, Signs and Symptoms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Medical University Graz

Graz, 8036, Austria

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

enhanced model predictive control algorithm (eMPC)

Other

eMPC (software on a bedside computer) advised insulin titration to establish tight glycaemic control

Primary outcomes

  1. percentage of time within the predefined glucose target range of 80-110 mg/dL

    Time frame: from start of treatment to the last glucose measurement under treatment

Secondary outcomes

  1. hypoglycemias (lab) and possible attendant clinical symptoms (e.g. convulsions)

    Time frame: from start of treatment to the last glucose measurement under treatment

  2. Usability parameters like convenience of alarming function; workload; blood sampling frequency

    Time frame: from start of treatment to the last glucose measurement under treatment

  3. Concomitant medication including insulin infusion rate, parenteral/enteral nutrition

    Time frame: from start of treatment to the last glucose measurement under treatment

Sponsors and collaborators

Lead sponsor

B. Braun Melsungen AG

Industry

Registry information

Official study 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

Acronym: Aldea _01

Important dates

Study start
2008
Primary completion
2009
Study completion
2009
First posted
Aug 14, 2008
Registry last updated
Apr 16, 2009

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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