Crystal Seuradge, Deryk Chen, Seetharaman Hariharan
Anaesthesia and Intensive Care Unit
The University of the West Indies, St Augustine Campus
Eric Williams Medical Sciences Complex, Trinidad
Tel: 1 868 662 4030
Glycaemic control with intensive insulin therapy and its impact on patient outcomes have always been contentious in an intensive care setting. This study aims to assess the patterns of glycaemic control in critically ill patients at a tertiary care institution in Trinidad and its relationship to outcomes.
All adult patients admitted to a multidisciplinary intensive care unit (ICU) for a period of two years were enrolled for a retrospective chart review. Data collected included demographics, admission blood glucose, mean morning blood glucose (MBG), the trend of glucose control, number of hypoglycaemic episodes, admission Simplified Acute Physiology Score (SAPS) II, ICU and hospital length of stay, duration of mechanical ventilation, anaemia, renal replacement therapy and hospital outcome.
A total of 104 patients were studied. Four different patterns of insulin therapy were practised at the ICU. The median age of patients was 55.5 years, the mean SAPS II was 49.3, the mean predicted mortality was 45.5% and the overall observed mortality was 38.5%. The majority of admissions had cardiovascular illnesses (25%), followed by sepsis (20.2%). Patients with multiple hypoglycaemic episodes had an increased mortality (p<0.01). Patients had a better outcome with a higher MBG (>100 mg/dL) (p<0.05). There was a significant difference in mortality among the four patterns of glycaemic control (p<0.001). Admission blood glucose, length of time of mechanical ventilation, ICU length of stay and renal replacement therapy were not found to be associated with adverse outcomes.
Intensive insulin therapy (IIT) may not benefit ICU patients but can be probably associated with higher mortality. Avoidance of hypoglycaemia as well as persistent hyperglycaemia may lead to a better outcome in critically ill patients.
Glycaemic control in critically ill patients has always been a subject of dispute due to the publication of many good-quality studies with conflicting views. The ideal range for glycaemic control remains unclear. It is also unclear whether one particular type of glucose control is applicable to all categories of patients, whether surgical or medical if they are undergoing anaesthesia or admitted in the intensive care unit or on the general wards.
Hyperglycaemia is very common in critically ill patients and may occur secondary to diabetes or a pre-diabetic state, or can be stress-induced . In a previous study, 96% of patients became hyperglycaemic during their ICU stay . Detrimental effects of hyperglycaemia are well known, which include increased inflammation, susceptibility to infection and organ dysfunction .
Insulin therapy seems to offer many other benefits to the patient than control of stress-induced hyperglycaemia and its attendant effects. There are many direct effects of insulin and its glucose-lowering effect that may contribute to superior outcome in patients receiving insulin treatment in the intensive care unit . Hence, the traditional recommendation has been for an Intensive Insulin Therapy (IIT) in the ICU setting in order to tightly control the blood glucose levels.
A study by van den Berghe et al (Leuven I study) suggested that IIT was beneficial in reducing morbidity and mortality in patients of a surgical ICU . Target blood glucose concentrations of 80-110 mg/dL were recommended. There was a decrease in mortality from 8% to 4.6% when the conventional treatment group was compared to the IIT group, albeit the fact that patients with sepsis possibly benefited the most. Another randomised controlled trial by the same authors (Leuven II study) compared IIT with conventional therapy (target blood glucose 180-200 mg/dL) in medical ICU patients. Patients who had IIT had lesser incidence of new kidney injury, reduced length of time on mechanical ventilation and hospital length of stay .
However, hypoglycaemia did occur in 18.7% of patients in the IIT group, while it occurred in only 3.1% of patients in the conventional therapy group. The incidence of hypoglycaemia further increased to 25.1% in patients who stayed in the ICU for longer than five days, and more importantly, hypoglycaemia was independently associated with mortality.
Hypoglycaemia is quite undesirable in an ICU patient, because it is associated with neuronal necrosis as well as seizures, coma, and death [7, 8]. The use of IIT in a critically ill patient with sepsis has an increased risk of serious adverse effects associated with hypoglycaemia . This resulted in the change of the Surviving Sepsis Campaign recommendations in 2009, which advised initializing insulin therapy only when blood glucose levels exceeded 180 mg/dL and keeping blood glucose levels at around 150 mg/dL .
Later, a large randomized trial, the ‘Normoglycaemia in Intensive Care Evaluation-Survival Using Glucose Algorithm Regulation’ (NICE-SUGAR) trial found an increased mortality among patients on IIT, compared to those with conventional targets (target blood glucose of 180 mg/dL or less) . Also, a meta-analysis which included data from the NICE-SUGAR trial showed that while patients in a surgical ICU may benefit from IIT, those in a medical or mixed ICU did not show any mortality benefit from IIT .
Notwithstanding these findings, there has been reported cost-benefits from IIT. The TRIUMPH project (Targeted Insulin Therapy to Improve Hospital Outcomes) assessed the economic benefits of IIT in critically ill patients . The authors reported a total savings of US$ 5.5 million over a one-year period for patients treated with IIT in the ICU. There was a reduction in ICU length of stay (average of 1.2 days), which was one factor saving costs. Another study in a mixed medical-surgical ICU also found reduced costs in patients treated with IIT, amounting to US$ 1,580 per patient or $1,339,500 per year during the treatment period. This was also attributed to the decreased ICU length of stay, decreased length of time on the ventilator and decreased use of laboratory, pharmacy and radiology resources .
Thus, there have been raging debates on the benefit and harm of intensive insulin therapy in critically ill patients in the existing medical literature. To our knowledge, there have been no published studies from the ICUs in the English-Speaking Caribbean, regarding the glycaemic control patterns and whether or not these patterns of treatment influence the outcome of patients.
Therefore, this study aimed to determine the patterns of glycaemic control in adult ICU patients in a tertiary care hospital in Trinidad, in an attempt to enable formulation of appropriate local guidelines.
After obtaining approval from the Ethics Committee of the University of the West Indies, St. Augustine, this study was conducted in a major 323-bedded tertiary teaching health facility in Trinidad with a mixed 10-bed surgical-medical ICU. A retrospective chart review was undertaken of all adult patients consecutively admitted for a period of two years. The inclusion criteria were adult patients (≥18 years of age) at the time of admission to the ICU who were mechanically ventilated for at least 24 hours. The exclusion criteria included those patients who were not mechanically ventilated at the time of admission, and patients who died within 24 hours after admission to the ICU.
Relevant patients were identified from the ICU admission book and then the patients’ notes were sourced from medical records. Data collected included demographics such as the patients’ age and gender, and clinical data including the baseline blood glucose on admission, admitting diagnosis, the trend of glucose control and insulin use, previous history of diabetes and occurrence of hypoglycaemic episodes. The presence of pre-existing diabetes mellitus was based on the clinical record within the notes and not HbA1c levels or a formal record of testing for diabetes. The primary outcome was mortality, whether it had occurred within the ICU or on the general wards. For this study purpose, patients were categorized based on the level of blood glucose into
1. Tight control group (80-110 mg/dL)
2. Conventional control group (80-150 mg/dL)
3. Poor control group (150-200 mg/dL) and
4. Persistent hyperglycaemia group (>200 mg/dL).
Analyses were also done based on mean morning blood glucose level (MBG), (≤ 100mg/dL or > 100 mg/dL). Data were recorded if the patients experienced single, multiple or no hypoglycaemic episodes and if they belonged to medical, emergency surgical and elective surgical groups. The secondary outcomes recorded included duration of mechanical ventilation, ICU length of stay, hospital length of stay, use of renal replacement therapy (RRT). Other variables collected were the presence or absence of anaemia (Hb<10mg/dL).
The Simplified Acute Physiology Score SAPS II was used as the scoring system in this study to quantify the severity of illness. It is usually measured 24 hours after admission to the ICU and ranges from zero to 163. It provides a predicted mortality from 0% to 100% and does not require a primary diagnosis. The SAPS II score requires 12 physiological variables, type of admission (whether scheduled, unscheduled, surgical or medical), three underlying disease variables (acquired immunodeficiency syndrome, metastatic cancer and haematologic malignancy) and age .
By institutional convention, the insulin dosing regime is based on a paper-based protocol and adjustments to the rate of the insulin infusion are made by the nurses based on the previous point-of-care glucose level. No clear trigger level of blood glucose was used at the time of the study to commence insulin therapy. Subcutaneous insulin is not used. Point-of-care measurements are usually done every four hours. Hypoglycaemia is defined as blood glucose < 60 mg/dL. The insulin infusion regimes (as algorithms) practised in the ICU during the study period are shown in Table 1.
Table 1: Insulin algorithm protocol in the study ICU
|Blood glucose (mg/dL)||Algorithm I (rate mL/h)||Algorithm II
Numerical variables were compared using the t-test and the analysis of variance (ANOVA) test as appropriate. Categorical variables were compared using Pearson’s Chi-squared test, Fisher’s exact test and Mantel-Haenszel common odds ratio estimates as appropriate. Kaplan-Meier survival curves were generated to assess the survival between two levels of mean blood glucose levels. ROC curve analysis was undertaken for SAPS II. A p value <0.05 was considered statistically significant. Statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) v.16.0 (IBM Corporation, Route 100 Somers, NY).
A total of 104 patients were included in this study. The age of patients ranged from 19 to 83 years and median age 55.5 years (IQR 42-66.8 years). Males accounted for 56.7% of patients. The median SAPS II score was 47.5 (IQR 35.3-62.8) and the median predicted mortality was 40.4% (IQR 17.2-73.2%).
Figure 1 depicts the distribution of patients according to the diagnoses on admission. The majority of admissions were medical (62.5%), 26.9% were post-operative emergency surgery while 10.6% were admitted after elective surgery.
Figure 1. Percentage distribution of admission diagnoses
Overall, 41.3% of patients were known to have diabetes mellitus prior to admission to the ICU and less than half (43.3%) of patients were anaemic on admission. About 10% of patients received RRT during their ICU stay.
The median admission blood glucose was 137.5 mg/dL (IQR 103.3-171.8 mg/dL) and the median morning blood glucose (MBG) was 139.5 mg/dL (IQR 113.2-178.8 mg/dL). The majority of patients were started on insulin algorithm I (44.2%). A large proportion of patients (46.2%) were not started on any insulin infusion while in the ICU. Algorithm II was started at 7.7%, 1.0% of patients was started on Algorithm III and 1.0% started on Algorithm IV. Patients who were admitted after elective surgery were most likely to be started on insulin therapy (63.6%) and medical admissions were least likely with 49.2% of patients receiving no insulin therapy. 42.9% of patients admitted after emergency surgery received no insulin therapy. Figure 2 shows the proportions of the different categories of patients in accordance with the glucose control achieved.
Figure 2. Percentage distribution of glycaemic control achieved
Overall, 40 patients died with an observed mortality of 38.5%. Medical patients had the highest mortality rate of 41.5%; patients admitted after emergency surgery had a 35.7% mortality rate and there was a 27.3% mortality rate in patients admitted after elective surgery.
Figure 3 shows the mortality in the categories of patients in accordance with the glycaemic control. Patients who were persistently hyperglycaemic and those who had tight control had mortality rates of 72.4% and 43.8% respectively. The conventional control group had a mortality rate of 15.4% and those with poor glycaemic control had a mortality rate of 30%.
Figure 3. Mortality among the different glycaemic control groups
Among the various insulin algorithms, 62.5% of patients on algorithm II died, algorithm I had 34.8% mortality, while algorithm III and IV had no deaths. Patients who were placed on no insulin therapy had 39.6% mortality. Figure 4 depicts the achieved blood glucose in patients grouped according to whether they were medical, emergency surgical or elective surgical.
Figure 4. Glycaemic control achieved according to the type of admission
The overall incidence of hypoglycaemia was 21.2%, when patients experienced at least one hypoglycaemic episode during their ICU stay. Half of these patients had multiple hypoglycaemic episodes. Patients experiencing multiple hypoglycaemic episodes had an 81.8% mortality rate, which was higher than the mortality rate for patients with one hypoglycaemic episode (45.5%) and patients who had no hypoglycaemic episodes (31.7%). Patients who were persistently hyperglycaemic and those who had tight control had the highest incidence of hypoglycaemia, with 31.0% and 37.5% of patients experiencing hypoglycaemic episodes during their ICU stay respectively. In comparison, 15.4% of those with conventional control and 5% of those who had poor control had hypoglycaemia.
Those admitted after emergency surgery were least likely to have hypoglycaemic episodes (10.7%), while those admitted after elective surgery were most likely to have hypoglycaemic episodes (36.4%). Even in patients who received no insulin therapy, the incidence of at least one hypoglycaemic episode occurring was 27.1% while patients who were on algorithm III and IV had no hypoglycaemic episodes. 25% of patients on algorithm II had at least one hypoglycaemic episode while 15.2% of patients on algorithm I had at least one episode; the details are shown in Table 2. Table 3 shows the morning blood glucose levels in different categories of patients.
Table 2. Number of hypoglycaemic episodes versus insulin therapy used
Table 3. Mean morning blood glucose (MBG) in different groups of patients
|Variable||Mean||95% Confidence Intervals|
The mortality in non-diabetics was 39.3% while it was 37.2% in known diabetics. Patients in the persistently hyperglycaemic group were the highest proportion to receive RRT (17.2%), followed by those under tight control (12.5%), poor control (10%) and the conventional control group (5.1%). 36.4% of patients who received RRT died.
The median duration on mechanical ventilation was four days (IQR 2-8 days) and the median length of stay in the ICU was also four days (IQR 3-9 days). The median hospital length of stay was 12 days (IQR 6-19 days). Table 4 shows the distribution of ICU and hospital length of stay in accordance with the glycaemic control.
Table 4. ICU and hospital length of stay in patients with different glycaemic control
Mean (95% CI)
Mean (95% CI)
|Tight control||4.4 (2.5 – 6.4)||10.6 (7.0-14.3)|
|Conventional control||7.0 (4.9-9.0)||13.9 (9.0-18.7)|
|Poor control||8.4 (4.4-12.3)||17.5 (13.2 -21.9)|
|Persistent hyperglycaemia||7.7 (4.6-10.7)||19.3 (10.2 – 28.4)|
Factors such as age, admission blood glucose, days of mechanical ventilation, and ICU length of stay were not significantly different between survivors and non-survivors.
Figure 5 shows the Kaplan-Meier survival curves. Patients with a mean morning blood glucose >100mg/dL had a significantly higher 30-day survival than patients with a mean morning blood glucose ≤ 100mg/dL (p=0.03).
Figure 5. Kaplan-Meier survival analyses for the relationship between mean morning blood glucose (MBG) and length of hospital stay
Figure 6 shows the Receiver Operating Characteristic (ROC) curve for the SAPS II scoring system, which was a reasonably good discriminator between survivors and non-survivors in the study ICU (ROC area under the curve = 0.83, p< 0.001).
Figure 6. ROC curve for the SAPS II score
The important finding of the study is that Intensive Insulin Therapy (IIT) may not be always needed to have a tighter glycaemic control in critically ill adult patients, since this may be associated with a higher incidence of hypoglycaemic episodes and adverse outcomes. In fact, the value of IIT has been questioned by a number of other studies, which have shown no benefit of IIT over conventional glycaemic control in the ICU [6, 16, 17].
The overall incidence of hypoglycaemia in this study was 21.2 % in the present study. In the study ICU, hypoglycaemia is defined as a blood glucose value of ≤ 60 mg/dL. When the patient’s blood glucose is found to be at the hypoglycaemic level, the insulin is stopped, treatment is started using a bolus of 25-50 mL of 50% dextrose solution and the blood glucose level is rechecked in 30 minutes. A previous retrospective study in an 18-bed mixed ICU, used the definition of hypoglycaemia as blood glucose value ≤ 45 mg/dL and found that only 4.8% of patients had at least one episode of hypoglycaemia . Thus, the present study found a higher incidence of hypoglycaemia even with the cut-off value of 60 mg/dL.
In fact, the cut-off value for defining hypoglycaemia varies between published studies. One study looked at different cut-off values for hypoglycaemia and the risk of ICU mortality . Interestingly, this study suggested that there was an increased risk of ICU mortality up to a blood glucose level of 85 mg/dL. Another study used 81 mg/dL as the cut-off value for hypoglycaemia and found an increased ICU mortality below this value . However, there have been other published studies which found no relationship between hypoglycaemia and mortality [17, 20].
The question remains whether hypoglycaemia is a marker for the severity of illness or an independent risk factor for mortality. Arabi et al attempted to identify the independent predictors of hypoglycaemia in patients receiving insulin treatment and found factors such as IIT, length of ICU stay, female gender, known DM, increasing severity of illness score and patients receiving RRT to be more likely associated with the development of hypoglycaemia . The incidence of hypoglycaemia also increased with an increasing length of ICU stay. Hence, it may be prudent to adjust the rate of hypoglycaemia to represent the treatment days. The median length of stay in the Leuven I trial was three days , and in Arabi et al study was 10 days, and in the latter study, the authors attributed a higher incidence of hypoglycaemia to the increased length of stay . In the present study, the median length of ICU stay was four days, however, the incidence of hypoglycaemia was 21.2%.
The interpretation of this finding must take into consideration a number of confounding factors. Firstly, it must be determined whether hypoglycaemia was spontaneous or insulin-induced. In the present study, almost half of the patients (46.2%) were not started on insulin therapy while in ICU. A previous report has showed that in patients who did not receive insulin, hypoglycaemia lead to higher mortality than in patients who experienced hypoglycaemia while receiving insulin therapy . In our study, hypoglycaemia occurred in 27.1% of patients who did not receive insulin therapy, and more than half of these patients had multiple hypoglycaemic episodes. Patients who did not receive insulin therapy also had the highest frequency of an MBG ≤100mg/dL. One possible explanation is that patients receiving insulin therapy are subject to more frequent sampling which would detect hypoglycaemia at an earlier stage, thereby shortening the duration of the hypoglycaemic episode . Dependence on bedside point-of-care glucose monitors may be another confounding factor . Since laboratory sampling remains the gold standard, patients should have their blood glucose checked in the laboratory at least once daily to ensure correlation with the point-of-care sample. Also, arterial blood sampling is preferred over capillary blood sampling to prevent wide variation. ICU patients frequently have problems such as vasoconstriction, shock or oedema making capillary blood measurements less reliable . In addition, signs of hypoglycaemia are often masked in the critically ill patient . Any patient exhibiting unexplained signs such as seizures, diaphoresis, hypotension, tachycardia or tachypnoea should have their blood glucose checked . Point-of-care blood glucose <80mg/dL should be treated and a sample should be sent to the laboratory for confirmation.
In present study, there was no significant relationship between admission blood glucose and mortality; Cely et al found that stress hyperglycaemia manifests itself early after admission, with the measured blood glucose after admission >150 mg/dL in 38% of patients and > 200 mg/dL in 23 % of patients . The limits of safe and acceptable glycaemic control remain unclear. Hyperglycaemia can be defined in different ways. Cely et al used a definition of ≥110 mg/dL for hyperglycaemia , while the American Diabetes Association (ADA) and the American Association of Clinical Endocrinologists (AACE) use Fasting blood glucose ≥126 mg/dL and Random blood glucose ≥200 mg/dL as the levels to denote hyperglycaemia [25, 26].
A tight glycaemic control regime seems to place the patient at a higher risk for hypoglycaemia, especially in a setting in which frequent blood glucose sampling is not feasible . The AACE, the ADA as well as the Society of Hospital Medicine have published guidelines for glycaemic control goals in critically ill patients [25-27]. The NICE-SUGAR trial, in which the conventional group (BG 144-180 mg/dL) had lower mortality and lower incidence of hypoglycaemia than the IIT group, also showed that lower glucose targets were difficult to attain . The IIT group achieved a mean blood glucose in the range of 81-108 mg/dL while the control group achieved a mean of 144 mg/dL.
Hence, the AACE/ADA in their consensus statement suggested that a blood glucose target of <140 mg/dL was not necessary, as a lower target may expose the patient to hypoglycaemia . In the present study, patients with an MBG >100mg/dL had a significantly higher 30-day survival than patients with an MBG ≤100mg/dL. The glycaemic control groups with the highest mortality rates either belonged to the ‘persistently hyperglycaemic’ group (MBG: 197.1 mg/dL) or the ‘tight control’ group (MBG: 92.4 mg/dL). It, therefore, seems a rational conclusion that the low target blood glucose is not necessary and at the same time severe hyperglycaemia (BG >180mg/dL) should be treated and avoided in critically ill patients.
Interestingly, the group of patients who were persistently hyperglycaemic had the highest rates of hypoglycaemia, as well as, the highest rate of mortality among the four groups of glucose control. This may point to large glycaemic variability among patients. Likely causes for large swings in blood glucose levels in these patients include over-treatment of hypoglycaemic episodes with glucose-containing solutions and over-treatment of hyperglycaemic events with insulin. Several authors have found that glycaemic variability to be an independent risk factor for mortality in the ICU [28,29]. Avoiding glycaemic variability lies in improved monitoring including increased frequency of blood glucose measurement and improved insulin protocols to prevent or reduce over-shoot of corrections of hypoglycaemia and hyperglycaemia.
The introduction of computerized protocols can potentially make insulin therapy more individual, rather than the current setting in which one insulin protocol is applied to all patients [30, 31]. The SPRINT protocol, which is a model-derived tight glycaemic control computerized protocol, showed reduced organ failure and reduced mortality compared to the pre-SPRINT group, which was treated with sliding scale insulin . However, this may not be always true since although the NICE-SUGAR study utilized computerized treatment algorithms, the tight glycaemic control group had a significantly greater incidence of severe hypoglycaemia and a higher mortality rate than the conventional treatment group. Future improvements should also occur with the development of closed-loop systems/ continuous glucose monitoring systems or the “artificial pancreas” which would reduce nursing workload and human error but will come with an initial high cost to the ICU .
In our study, 41.3% of patients were known diabetics prior to admission. In the Leuven II trial, only 16.9% of patients were known diabetics , while NICE-SUGAR reported 20% . A trial by Arabi et al approached our figure with 39% of patients being known diabetics . Falciglia et al found an association between hyperglycaemia and increased mortality in both diabetics and non-diabetics but the effect was greater among non-diabetics ; other studies have reported increased mortality among non-diabetes but not diabetic patients . Caution must be exercised when interpreting the results of trials as one must take into consideration the proportion of known diabetics within the trial.
Another study found that hyperglycaemia (BG> 200mg/dL) was an independent risk factor in the cardiac, cardiothoracic and neurosurgical intensive care units but only in patients who were not known diabetics . However, in the present study, there was no significant difference in mortality between diabetics and non-diabetics. It is possible that there is a large proportion of unrecognised or previously undiagnosed diabetes in this population, especially as HbA1c levels are not routinely measured on admission to the ICU. HbA1c levels should be assessed if the patient did not have his/her levels checked within the last two to three months as this would assess the baseline blood glucose control . Values > 6.5 % suggest that the patient may be a previously undiagnosed diabetic . HbA1c may also be an appropriate tool for risk stratification .
It is also questionable if there is any relationship between the insulin algorithm used and the mean blood glucose achieved, although in the present study there was a significant difference, with a higher MBG in patients on algorithm II rather than algorithm I (p<0.05). Finney et al have shown that the level of glucose control achieved was more important in conferring a mortality benefit than the levels of exogenous insulin .
Despite a large amount of research in the area of glycaemic control in the critically ill, there remain several areas in which clear guidelines/ associations are not yet available . These include:
- The association between hypoglycaemia and an increased risk of mortality
- The avoidance of dextrose containing solutions leading to a reduction in hyperglycaemia
- Adjustment of carbohydrate intake to achieve better glycaemic control, whether parenteral or enteral
- Insulin infusion algorithms and which are superior
- Computer-assisted glucose control protocols and their role in the critical care setting
- Staffing/training of nurses in the ICU for new glucose control protocol implementation
- Further assessment of a new glucose protocol once it is implemented
There were some limitations to the present study which include retrospective nature of the study leading to the loss of data, previously diagnosed diabetes was obtained from the medical history but discrimination between undiagnosed diabetes and stress hyperglycaemia could not be made (by HbA1C measurement) and an assessment of the subtype of diabetes was also not possible.
Nevertheless, this study could clearly establish that optimizing glucose management in the ICU setting is essential to improve outcomes in patients. Intensive Insulin Therapy may be associated with hypoglycaemic episodes and adverse outcomes and hence should be avoided. Although the ideal range for glycaemic control could not be established, the study found that both persistent hyperglycaemia (>180 mg/dL) and targeting a tight control of blood glucose (80-110 mg/dL) increases mortality.
A multidisciplinary approach is essential to address this, with the close involvement of the nursing staff at the ICU. Training and increased awareness of all medical staff are also important. Establishment of new glucose control protocols must also be followed by further reassessments and adjustments based on continuing research.
- McCowen KC, Malhotra A, Bistrain BR: Stress-induced Hyperglycemia. Crit Care Clini 2001; 17:107-24.
- Fahy BG, Sheehy AM, Coursin DB: Glucose control in the intensive care unit. Crit Care Med 2009; 37:1769-1776.
- Turina M, Fry DE, Polk HC Jr et al: Acute hyperglycaemia and the innate immune system: Clinical, cellular and molecular aspects. Crit Care Med 2005;33: 1624-33
- Vanhorebeek I, Langouche L, Van de Berghe G: Glycaemic and nonglycemic effects of insulin: how do they contribute to a better outcome of critical illness. Curr Opin Crit Care 2005 Aug; 11(4): 304-11
- Van den Berghe G, Wouters P, Weekers F et al: Intensive insulin therapy in the critically ill. N Engl J Med 2001 Nov8; 345(19): 1359-67
- Van den Berghe G, Wilmer A, Hermans G et al: Intensive insulin therapy in the medical ICU. N Engl J Med 2006 Feb 2;354(5):449-61
- Auer RN: Hypoglycaemic brain damage. Metab Brain Dis 2004; 19:169-75.
- Cryer PE, Davis SN, Shamoon H: Hypoglycaemia in diabetes. Diabetes Care 2003; 26:1902-12.
- Brunkhorst FM, Engel C, Bloos F et al: Intensive insulin therapy and Pentastarch resuscitation in severe sepsis N Engl J Med 2008; 358(2);125-139.
- The Surviving Sepsis Campaign. www.survivingsepsis.org/About_the_Campaign/Documents/SSCStatement on Glucose Control in Severe Sepsis.pdf.
- The NICE-SUGAR study investigators: Intensive versus conventional glucose control in critically ill patients. N Engl J Med 2009; 360:1283-97.
- Greisdale D, de Souza RJ, van Dam RM et al: Intensive insulin therapy and mortality among critically ill patients: a meta-analysis including NICE-SUGAR study data. CMAJ 2009; 180(8):821-7.
- Krinsley JS, Jones RL. Cost analysis of intensive glycaemic control in critically ill adult patients. Chest 2006; 129:644-650.
- Blot SI, Depuydt P, Annemans L, Benoit D, Hoste E, De Waele JJ, Decruyenaere J, Vogelaers D, Colardyn F, Vendewoude KH: Clinical and economic outcomes in critically ill patients with nosocomial catheter related blood stream infections. Clin Infectious Dis 2005; 41:1591-8.
- Jean-Roger Le Gall, MD; Stanley Lemeshow, PhD; Fabienne Saulnier, MD: A new simplified acute physiology score (SAPS II) based on European/ North American multicenter study. JAMA. 1993; 270(24):2957-2963.
- Gisela Del Carmen De La Rosa, Donado JH, Restrepo AH et al. Strict glycaemic control in patients hospitalised in a mixed medical and surgical intensive care unit: a randomized clinical trial. Critical Care 2008;12: R120
- Arabi YM, Tamim HM, Rishu AH: Hypoglycemia with intensive insulin therapy in critically ill patients: predisposing factors and association with mortality. Crit Care Med 2009, 37: 2536-2544.
- Hermanides J, Bosman RJ, Vriesendorp TM et al: Hypoglycaemia is associated with intensive care unit mortality. Crit Care Med 2010;38: 1430-1434.
- Bagshaw SM, Bellomo R, Jacka MJ et al: The impact of early hypoglycaemia and blood glucose variability on outcome in critical illness. Critical Care 2009, 13: R91
- Krinsley JS, Grover A: Severe hypoglycemia in critically ill patients: Risk factors and outcomes. Crit Care Med 2007; 35: 2262-2267.
- Van den Berghe G, Wilmer A, Milants I et al: Intensive insulin therapy in mixed medical/surgical intensive care units: benefit vs harm. Diabetes 2006; 55:3151-3159.
- Lacara T, Domagtoy C, Lickliter D et al: Comparison of point-of-care and laboratory glucose analysis in critically ill patients. Am J Crit Care 2007, 16:336-346.
- Ichai C., Presier J et al: International recommendations for glucose control in adult non diabetic critically ill patients. Critical Care 2010, 14: R166.
- Cely CM, Arora P, Quartin AA, Kett DH, Schein RM: Relationship of baseline blood glucose homeostasis to hyperglycaemia during medical critical illness. Chest 2004; 126:879-887.
- Moghissi ES, Korytkowski MT, DiNardo M, et al. American Association of Clinical Endocrinologists and American Diabetes Association consensus statement on inpatient glycemic control. Diabetes Care 2009;32(6):1119-1131.
- American Diabetes Association. Standards of medical care in diabetes— 2010. Diabetes Care 2010;33(suppl 1): S11-61.
- Schnipper JL, Magee M, Larsen K, Inzucchi SE, Maynard G. Society of Hospital Medicine Glycemic Control Task Force summary: practical recommendations for assessing the impact of glycemic control efforts. J Hosp Med. 2008;3(5 suppl):66-75.
- Krinsley JS: Glycemic variability a strong independent predictor of mortality in critically ill patients. Crit Care Med 2008; 12: 116
- Egi M, Bellomo R, Stachowski E et al: Variability of blood glucose concentration and short-term mortality in critically ill patients. Anesthesiology 2006; 105: 244-252.
- Hunt DL, Haynes RB, Hanna SE, Smith K: Effects of computer based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA 1998, 280:1339-1346.
- Meijering S, Corstjens AM, Tulleken JE et al: Towards a feasible algorithm for tight glycaemic control in critically ill patients: a systematic review of the literature. Critical Care 2006, 10: R19.
- Chase JG, Pretty CG, Pfeifer L et al: Organ failure and tight glycaemic control in the SPRINT study. Critical Care 2010, 14: R154.
- Yamashita K, Yatabe T: Intraoperative glycaemic control procedures and the use of an artificial pancreas. World J Gastroenterol 2009;15(33): 4126-4131.
- Arabi YM, Dabbagh OC, Tamim HM, Al-Shimemeri AA, Memish ZA, Haddad SH, Syed SJ, Giridhar HR, Rishu AH, Al-Daker MO, Kahoul SH, Britts RJ, Sakkijha MH. Intensive versus conventional insulin therapy: a randomized controlled trial in medical and surgical critically ill patients. Crit Care Med. 2008;36(12):3190–7.
- Falciglia M, Freyburg R, Almenoff P et al. Hyperglycaemia-related mortality in critically ill patients varies with admission diagnosis. Crit Care Med 2009; 37(12):3001-3009.
- Stegenga ME, Vincent J, Vail GM et al: Diabetes does not alter mortality or hemostatic and inflammatory responses in patients with severe sepsis. Crit Care Med 2010; 38(2): 539-45
- Whitcomb BW, Pradhan EK, Pittas AG, Roghmann MC, Perencevich EN. Impact of admission hyperglycaemia on hospital mortality in various intensive care unit populations. Crit Care Med 2005 Dec;33(12):2772-7.
- Finney SJ, Zekveld C, Elia A et al: Glucose control and mortality in critically ill patients. JAMA 2003 Oct 15;290 (15): 2041-7