Critical Illness Clinical Trial
Official title:
Impact of the Use of a Computerized Protocol for Glucose Control Named CGAOtm on the Outcome of Critically Ill Patients
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.
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.
;
Allocation: Randomized, Endpoint Classification: Safety/Efficacy Study, Intervention Model: Parallel Assignment, Masking: Open Label, Primary Purpose: Treatment
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