Critically ill patients often suffer from 'stress hyperglycemia', a condition in which insulin resistance due to increased catecholamine levels causes high blood glucose values [
1]. The association between stress hyperglycemia and adverse outcome has been observed in numerous patient categories, ranging from patients admitted to the general ward [
2] to myocardial infarction [
3] and stroke patients [
4]. For decades, stress hyperglycemia was thought to be merely a marker of disease, and was tolerated as long as glucose levels were not excessively high (e.g., over 11.0 mmol/L). The publication of the Leuven intensive insulin therapy study in September 2001 caused a paradigm shift in critical care medicine [
5]. This study showed that rapid lowering of blood glucose levels below 6.1 mmol/L and subsequent maintaining of normoglycemia reduce mortality and morbidity markedly. These results were confirmed by a before-after study performed by Krinsley, in which also a decrease in mortality was achieved with tight glucose control [
6]. Especially for septic patients, guidelines now recommend using insulin to reduce high glucose levels [
7]. However, infusing insulin in order to lower glucose levels bears the risk of inducing life-threatening hypoglycemia, especially in sedated patients admitted to an intensive care unit (ICU). In order to cut back this risk, glucose levels must be frequently measured. Each measurement calls for a decision on what action to take to keep glucose levels in the normal range. With recommended sampling frequencies ranging from every 1 – 2 hours to every 6 hours, implementation of tighter glucose control poses an important logistic challenge. Many investigators have proposed nurse-driven protocols for glucose control. After each glucose measurement, simple if-then rules or lookup tables yield an advice on how much insulin needs to be administered [
8‐
10]. Even though glucose sampling frequency is high, reduction of hyperglycemia is often not satisfactory, and, more important, hypoglycemia is relatively common [
9]. Glucose metabolism is also an important topic in acute coronary care. Several studies have evaluated glucose-related therapies as strategies to improve outcome in acute coronary syndromes, such as high dose glucose-insulin-potassium (GIK) infusion [
11,
12], or combined glucose-insulin infusion to reduce glucose levels [
13,
14]. Although clinical results have been mixed, with most recent results being negative, the efficacy of glucose-lowering interventions in acute coronary care is still unknown since none of the published trials achieved tight glycemic control [
11,
14]. Because coronary care units (CCU) are a less controlled environment with a lower personnel-to-patient ratio than ICUs, intensive insulin therapy is hard to achieve with paper protocols [
14]. An optimized decision making algorithm might be able to make tighter control possible.
We hypothesized that a computer program can employ the necessary complex logic to achieve the desired level of both safety and efficiency of glucose control without excessive glucose sampling frequencies. In the beginning of 2003 we initiated development of a computer controlled decision support system.