Computerized Glucose Control in Critically Ill Patients (CGAO-REA)

This study has been completed.
Sponsor:
Collaborators:
Société Française d'Anesthésie et de Réanimation
Baxter Healthcare Corporation
Information provided by (Responsible Party):
Dr Pierre KALFON, Centre Hospitalier of Chartres
ClinicalTrials.gov Identifier:
NCT01002482
First received: October 26, 2009
Last updated: November 8, 2013
Last verified: November 2013
  Purpose

The aim of the study is to determine whether the use of the CGAOtm software is associated with a decrease in 90-day mortality when compared with the use of standard care methods for glucose control with target blood glucose levels inferior to 180 mg/dl. The CGAOtm software is designed to assist physicians and nurses in achieving tight glucose control (defined by a target for blood glucose levels between 80 and 110 mg/dl) in critically ill patients.


Condition Intervention Phase
Hyperglycemia
Critical Illness
Device: CGAO-based Glucose Control
Device: Standard-Care Glucose Control
Phase 3

Study Type: Interventional
Study Design: Allocation: Randomized
Endpoint Classification: Safety/Efficacy Study
Intervention Model: Parallel Assignment
Masking: Open Label
Primary Purpose: Treatment
Official Title: Impact of the Use of a Computerized Protocol for Glucose Control Named CGAOtm on the Outcome of Critically Ill Patients

Resource links provided by NLM:


Further study details as provided by Centre Hospitalier of Chartres:

Primary Outcome Measures:
  • All-cause 90-day Mortality [ Time Frame: Day 90 ] [ Designated as safety issue: Yes ]

Secondary Outcome Measures:
  • All-cause 28-day Mortality [ Time Frame: Day 28 ] [ Designated as safety issue: Yes ]
  • All-cause Intensive Care Unit Mortality [ Time Frame: Date of discharge from the ICU ] [ Designated as safety issue: No ]
  • All-cause In-hospital Mortality [ Time Frame: Day of discharge from the hospital ] [ Designated as safety issue: No ]
  • Intensive Care Unit Free Days [ Time Frame: 28 days ] [ Designated as safety issue: No ]
    Intensive care unit free days was 28-day-ICU-free-days i.e. was calculated by subtracting the actual ICU duration in days from 28 with patients who died at day 28 or before being assigned 0 free-days and those who had a stay in ICU of 28 days or more being also assigned 0 free-days

  • Time Spent in Blood Glucose Target [ Time Frame: Day of discharge from the ICU ] [ Designated as safety issue: No ]
  • Severe Hypoglycemia [ Time Frame: Date of discharge from the ICU ] [ Designated as safety issue: Yes ]
    Number of patients with severe biological hypoglycemia (defined as blood glucose of 40 mg per deciliter or less)regardless of clinical signs

  • Hospital Length of Stay [ Time Frame: Date of discharge from the hospital ] [ Designated as safety issue: No ]
  • Intensive Care Unit Length of Stay [ Time Frame: Date of discharge from the ICU ] [ Designated as safety issue: No ]
  • Incidence of Nosocomial Bacteriemia [ Time Frame: Date of discharge from the ICU ] [ Designated as safety issue: Yes ]

Enrollment: 2684
Study Start Date: October 2009
Study Completion Date: April 2013
Primary Completion Date: December 2012 (Final data collection date for primary outcome measure)
Arms Assigned Interventions
Experimental: CGAO-based Glucose Control
Use of a Computerized Protocol fot Tight Glycemic Control named CGAO software in order to maintain Blood Glucose Levels between 4.4 and 6.1 mmol/l.
Device: CGAO-based Glucose Control

Use of a clinical computerized decision-support system named CGAOtm designed to achieve tight glucose control in various ICU settings, and fine-tuned to reduce glucose variability without increasing the incidence of severe hypoglycemia or nurse workload.

CGAOtm is based on explicit replicable recommendations following each blood glucose measurement for insulin rates and time to next measurement, and reminders, alerts, graphic tools, trends, and individual on-line data aimed at increasing confidence of the nursing staff in the computer protocol and giving care staff a method for controlling the process during the whole ICU stay, according to a "human-in-the-loop" approach.

The algorithm used in the CGAOtm software for the calculation of the recommended insulin rates derived from a PID (Proportional-integral-derivative) controller, a generic control loop feedback mechanism widely used in industrial control.

Other Name: CGAO, LC_CGAO version1
Active Comparator: Standard-Care Glucose Gontrol
Use of Standard-Care Methods for Glucose Control targeting Blood Glucose Levels inferior to 10 mmol/l.
Device: Standard-Care Glucose Control
Patients in the control group will receive conventional insulin therapy using the "usual care" protocol of each participating centre (already used in the centre before the beginning of the trial and targeting blood glucose levels inferior to 180 mg/dl).
Other Name: Usual care

  Hide Detailed Description

Detailed Description:

Hyperglycemia in response to critical illness has long been associated with adverse outcomes.

In 2001, the first "Leuven study", a randomized controlled trial conducted in surgical intensive care patients comparing a strategy based on a nurse-driven protocol for insulin therapy in order to maintain normal blood glucose levels [80 - 110 mg/dl] with standard care defined at the time as intravenous insulin started only when blood glucose level exceeded 215 mg/dl and then adjusted to keep blood glucose level between 180 and 200 mg/dl, showed a reduction in hospital mortality by one third.

The results of this trial have been enthusiastically received and rapidly incorporated into guidelines, such as the Surviving Sepsis Campaign in 2004, and now endorsed internationally by numerous professional societies.

However, subsequent randomized controlled trials have failed to confirm a mortality benefit with intensive insulin therapy among critically ill patients, in whom stress hypoglycemia is common. Moreover the Normoglycemia in Intensive Care Evaluation - Survival Using Glucose Algorithm Regulation (NICE-SUGAR) study, an international multicentre trial involving 6104 patients, the largest trial of insulin therapy to date, showed a lower 90-day mortality in the control group targeted blood glucose levels inferior to 180 mg/dl when compared to the intervention group with tight glucose control [80 - 110 mg/dl].

In addition, many studies and meta-analyses have reported high rates of hypoglycemia with tight glucose control. Consequently, considerable controversy has emerged as to whether tight glucose control is warranted in all critically ill patients especially as tight glucose control (without appropriate computer protocol) causes a significant increase in nurse workload.

The conflicting results between the first Leuven study and the NICE-SUGAR study could be explained by numerous differences between the two trials : the specific method (algorithms, compliance of nurses and physicians with recommendations, etc) used to achieve tight glucose control in each randomized control trial could be a major issue.

Several experimental and observational studies have highlighted the possible negative impact of glucose variability (large fluctuations in blood glucose possibly with undetected hypoglycemia and hypokalemia alternating with hyperglycemia) when implementing tight glucose control, be it due to the intrinsic properties of the algorithms used, technical factors (errors in measurements of the blood glucose level or lack of control over intravenous insulin therapy) or human factors (delay in performing glucose measurements or non respect of recommendations not based on clinical expertise but as a consequence of insufficient training inducing a lack of confidence in the algorithms by inexperienced nurses).

Therefore, remaining concerns about the best way to achieve glucose control in the ICU reduce the impact of conclusions of all of the recent randomized controlled trials on tight glucose control : are the negative results due to the concept, tight glucose control with intensive insulin therapy in critically ill patients in order to reduce the toxicity of high blood glucose levels, or are the negative results mainly due to specific methods used for achieving tight glucose control ? In most cases the methods used in clinical trials were never tested in numerical patients according to existing and validated models (in SILICO expertise) before implementing them in clinical practice on real patients.

Particularly, whether the use of a clinical computerized decision-support system (CDSS) designed for achieving tight glucose control in various ICU settings, and fine-tuned to reduce glucose variability, without increasing the incidence of severe hypoglycemia nor the nurse workload, has an impact on the outcome of patients staying at least three days in an ICU remains to be tested.

Among the different CDSS, the CGAOtm software has been developed to standardize different aspects of glucose control in an ICU setting based on 1) explicit replicable recommendations following each blood glucose level measurement concerning insulin rates and time to next measurement, 2) reminders and alerts and 3) various graphic tools, trends, and individual on-line data aiming to increase the confidence of the nursing staff in the computer protocol and therefore their adherence, to reduce necessary training time, and to give physicians and nurses a way to control the tight glucose control process during the whole ICU stay. Moreover, the CGAOtm software is designed to take into account irregular sampling, saturations, and some precision and stability issues.

The aim of the study is to evaluate the capability of the CGAOtm software to reduce 90-day mortality in a mixed ICU population of patients requiring intensive care for at least three days.

Sample size and power calculations. The expected all cause 90-day mortality in the control group is 25 % (identical to the observed all cause 90-day mortality in the control group of the NICE-SUGAR trial). Considering that all cause 90-day mortality in the experimental group (computer protocol group) is expected to be 22 % (absolute reduction of 3 %), considering an alpha risk and a beta risk respectively of 0.05 and 0.20 and three intermediate analyses performed according to the O'Brien-Fleming design, 3,211 patients per treatment arms are needed and will be recruited from the participating 60 centres, all located in France.

  Eligibility

Ages Eligible for Study:   18 Years and older
Genders Eligible for Study:   Both
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  • At time of the patient's admission to the ICU, the treating ICU specialist expects the patient will require treatment in the ICU that extends beyond the calendar day following the day of admission.

Exclusion Criteria:

  • Age < 18 years or patient under guardianship.
  • Pregnancy.
  • Moribund patient or imminent death in the ICU (e.g. patient expected to die in the ICU within 24 hours).
  • At time of the patient's admission, the treating physicians are not committed tu full supportive care.
  • Patient admitted to the ICU for treatment of diabetic ketoacidosis or hyperosmolar state.
  • Patient admitted to the ICU for hypoglycemia.
  • Patient thought to be at abnormally high risk of suffering hypoglycemia (e.g. known insulin secreting tumor or history of unexplained or recurrent hypoglycemia or fulminant hepatic failure).
  • Patient who have suffered hypoglycemia without documented full neurological recovery
  • Patient is expected to be eating before the end of the day following admission.
  • Patient previously enrolled in the CGAO-REA study.
  Contacts and Locations
Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the Contacts provided below. For general information, see Learn About Clinical Studies.

Please refer to this study by its ClinicalTrials.gov identifier: NCT01002482

Locations
France
C.H.U. Hôpital Nord
Amiens, France, 80054
C.H. d'Avignon
Avignon, France, 84902
G.H.U. Nord Hôpital Jean Verdier
Bondy, France, 93143
Polyclinique Jean Vilar
Bruges, France, 33520
Hôpital Sainte-Camille
Bry sur Marne, France, 94366
C.H. de Chartres
Chartres, France, 28018
C.H. Châteauroux
Chateauroux, France, 36019
Hôpital Sud-Francilien - Site Corbeil
Corbeil-Essonnes, France, 91006
Clinique des Cèdres
Cornebarrieu, France, 31700
C.H. Victor Jousselin
Dreux, France, 28012
Raymond Poincaré
Garches, France, 92380
Centre Hospitalier Départemental Les Oudairies
La Roche Sur Yon, France, 85925
G.H.U. Sud Bicêtre
Le Kremlin Bicêtre, France, 94275
Hôpital de Mantes-La-Jolie
Mantes-La-Jolie, France, 78200
C.H.U. La Timone
Marseille, France, 13005
Hôpital Paul Desbief
Marseille, France, 13002
Hôpital Ambroise Paré
Marseille, France, 13291
C.H.U. Lapeyronie
Montpellier, France, 34925
C.H.U. de -Hôpital Saint-Eloi
Montpellier, France, 34295
C.H.U. Nantes - Hôpital Laennec
Nantes, France, 44093
C.H.U. de Nice - Hôpital Saint-Roch
Nice, France, 06006
G.H.U. Pitié-Salpétriêre
Paris, France, 75651
Hôpital Européen Georges Pompidou
Paris, France, 75015
Institut Mutualiste Montsouris
Paris, France, 75674
G.H.U. Nord Claude Bernard
Paris, France, 75877
C.H. de Pau
Pau, France, 64046
CHU de Bordeaux - Groupe Hospitalier Sud, Hôpital Haut Lévêque
Pessac, France, 33604
C.H. René Dubos
Pontoise, France, 95301
C.H. Bourran
Rodez, France, 12000
C.H.U. Hôpitaux de Rouen
Rouen, France, 76031
Hôpital Foch
Suresnes, France, 92151
C.H. Intercommunal - Hôpital Font-Pré
Toulon, France, 83100
C.H.U. Rangueil
Toulouse, France, 31059
C.H.U. Purpan
Toulouse, France, 31059
C.H.R.U. de Tours
Tours, France, 37044
Sponsors and Collaborators
Centre Hospitalier of Chartres
Société Française d'Anesthésie et de Réanimation
Baxter Healthcare Corporation
Investigators
Principal Investigator: Pierre Kalfon, MD Centre Hospitalier de Chartres
Study Director: Bruno Riou, MD PhD G.H.U. Est, C.H.U. Pitié-Salpétriêre
Study Chair: Djillali Annane, MD PhD G.H.U. Ouest, Hôpital Raymond Poincaré
Study Chair: Jean Chastre, MD PhD G.H.U. Est, Pitié-Salpétriêre
Study Chair: Pierre-François Dequin, MD PhD CHRU Tours
Study Chair: Hervé Dupont, MD PhD CHRU Amiens
Study Chair: Carole Ichai, MD PhD CHRU de Nice
Study Chair: Yannick Malledant, MD PhD CHRU Rennes
Study Chair: Philippe Montravers, MD PhD G.H.U. Nord Bichat-Claude Bernard
  More Information

Publications:
Guerrini A; Roudillon G; Gontier O; Rebaï L; Isorni MA; Mutinelli-Szymanski P; Sorine M; Kalfon P. High glycemic variability induced by inappropriate algorithms for intensive insulinotherapy: the example of the NICE-SUGAR study. Abstract award winners: The best pre-selected abstracts of the 22th Annual Congress of the European Society of Intensive Care Medicine, 11-14 October 2009, Vienna, Austria. Intensive Care Med. 2009 Sep;35 Suppl 1:S111.
Gontier O; Hamrouni M; Lherm T; Monchamps G; Ouchenir A; Kalfon P. The CGAO software improves glycaemic control in intensive care patients without increasing the incidence of severe hypoglycaemia nor the nurse workload. Abstracts of the 21th Annual Congress of the European Society of Intensive Care Medicine, 21-24 September 2007, Lisbon, Portugal. Intensive Care Med. 2008 Sep;34 Suppl 2:S220.
Kalfon P; Marie C; Gontier O; Riou B. Improvement of glycaemic control in critically ill patients with the software CGAO. Abstract of the 20th Annual Congress of the European Society of Intensive Care Medicine, 7-10 October 2007, Berlin, Germany. Intensive Care Med. 2007 Sep;33 Suppl 2:S54.

Additional publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):
Responsible Party: Dr Pierre KALFON, principal investigator, Centre Hospitalier of Chartres
ClinicalTrials.gov Identifier: NCT01002482     History of Changes
Other Study ID Numbers: CGAO-REA-01
Study First Received: October 26, 2009
Results First Received: April 24, 2013
Last Updated: November 8, 2013
Health Authority: France: Afssaps - Agence française de sécurité sanitaire des produits de santé (Saint-Denis)

Keywords provided by Centre Hospitalier of Chartres:
Hyperglycemia
Hypoglycemia
Intensive Care Unit
Glucose Control
Insulin
Computer Protocol
Metabolic Disorders

Additional relevant MeSH terms:
Critical Illness
Hyperglycemia
Disease Attributes
Pathologic Processes
Glucose Metabolism Disorders
Metabolic Diseases

ClinicalTrials.gov processed this record on July 29, 2014