Intensive Insulin Therapy Protocol Research Articles

Safe and effective glycaemic control in premature infants: observational clinical results from the computerised STAR-GRYPHON protocol

ObjectivePrevious studies examine clinical outcomes of insulin therapy in neonatal intensive care units (NICUs), without first developing safe and effective control protocols. This research quantifies the safety and performance of...

Tight glycemic control in acutely ill patients: low evidence of benefit, high evidence of harm!

In 1878 Claude Bernard described hyperglycemia during hemorrhagic shock [1]. It is now well known that acute illness or injury may result in hyperglycemia, insulin resistance, and glucose intolerance, collectively termed stress hyperglycemia [2]. Stress hyperglycemia is an evolutionarily preserved adaptive response which provides the nervous and immune system with an immediate source of energy at a time of crisis. Insects, worms, and all vertebrates develop stress hyperglycemia when exposed to stress [2]. Stress hyperglycemia is a component of the stereotypic and coordinated response to stress referred to by Hans Selye as the “general adaption syndrome” which until 2001 was believed to be a beneficial host response which enhanced the host’s chances of survival [3]. On 8 November 2001, Van den Berghe and colleagues published a study entitled “Intensive insulin therapy in critically ill patients” in which they randomized 1548 surgical ICU patients (63 % who had undergone cardiac surgery) to an intensive insulin therapy (IIT) protocol targeting a blood glucose of 80–110 mg/dl or a control arm in which patients only received insulin when the blood glucose exceeded 215 mg/dl with a target of 180–200 mg/ dl (Leuven I study) [4]. Hospital mortality was 7.2 % in the IIT group as compared to 10.9 % in the control group (p = 0.01); in addition IIT reduced length of stay and patient morbidities. This study was supported by retrospective cohort studies in acutely ill patients demonstrating an association between increasing hyperglycemia and poor clinical outcomes. The findings of the Leuven study were widely embraced and endorsed by the Institute for Health Care Improvement, the American College of Endocrinology as well as other national and international organizations and soon became considered the standard of care for ICU patients around the world. In 2006, Van den Berghe and colleagues repeated their study in medical ICU patients (Leuven II study) [5]. Although failing to reproduce the improvement in survival in the entire set of patients, this study demonstrated a reduction in morbidity in the patients randomized to IIT with a reduction in mortality in the subset of patients with an ICU stay of 3 days or more. Using a similar study design these authors repeated their study in a pediatric ICU (mostly cardiac surgery patients) and demonstrated an outcome very similar to the Leuven I study [6]. Following the Leuven I study, 14 randomized controlled trials in various patient populations including mixed ICUs, neurosurgical, neurological, coronary, trauma, and pediatric ICUs have been performed (see Table 1). Without exception all of these studies demonstrated no outcome benefit (NOB) from tight glycemic control in acutely ill patients. NICE-SUGAR, the largest trial to date (n = 6022), demonstrated a 2.6 % absolute increase in 90-day mortality in patients randomized to IIT (p = 0.02) [7]. Three of these studies demonstrated harm, with almost all of the studies demonstrating a significant increase in the risk of both moderate and severe hypoglycemia. Even mild hypoglycemia in ICU patients is associated with an increased risk of death [8]. The mechanism(s) by which hypoglycemia increases the risk of death in critically ill patients has (have) not been investigated. However, it is likely that hypoglycemia increases the risk of fatal arrhythmias [9]. Furthermore, cell death *Correspondence: marikpe@evms.edu 2 Eastern Virginia Medical School, 825 Fairfax Av, Suite 410, Norfolk, VA 23507, USA Full author information is available at the end of the article

Using Continuous Glucose Monitoring Data and Detrended Fluctuation Analysis to Determine Patient Condition: A Review.

Patients admitted to critical care often experience dysglycemia and high levels of insulin resistance, various intensive insulin therapy protocols and methods have attempted to safely normalize blood glucose (BG) levels. Continuous glucose monitoring (CGM) devices allow glycemic dynamics to be captured much more frequently (every 2-5 minutes) than traditional measures of blood glucose and have begun to be used in critical care patients and neonates to help monitor dysglycemia. In an attempt to obtain a better insight relating biomedical signals and patient status, some researchers have turned toward advanced time series analysis methods. In particular, Detrended Fluctuation Analysis (DFA) has been a topic of many recent studies in to glycemic dynamics. DFA investigates the "complexity" of a signal, how one point in time changes relative to its neighboring points, and DFA has been applied to signals like the inter-beat-interval of human heartbeat to differentiate healthy and pathological conditions. Analyzing the glucose metabolic system with such signal processing tools as DFA has been enabled by the emergence of high quality CGM devices. However, there are several inconsistencies within the published work applying DFA to CGM signals. Therefore, this article presents a review and a "how-to" tutorial of DFA, and in particular its application to CGM signals to ensure the methods used to determine complexity are used correctly and so that any relationship between complexity and patient outcome is robust.

Glucose Management in Critically Ill Medical and Surgical Patients

Currently, many providers treat hyperglycemia in the critically ill based on guidelines suggesting target glucose ranges between 140 and 180 mg/dL. However, recent literature has attempted to challenge this by comparing the effect of intensive insulin therapy (IIT) to conventional insulin therapy. Four studies examining the impact of IIT and conventional insulin therapy on mortality in critically ill patients were examined and analyzed. The outcomes from these studies are mixed with neither therapy showing marked improvement in morbidity and mortality rates; in fact, these studies showed a trend toward increased mortality related to an increased incidence of hypoglycemia with IIT. Factors such as days of mechanical ventilation, infection rates, length of stay in the ICU, and incidence of organ failure were included as secondary end points. The data suggest IIT may improve patient outcomes in some areas, but the data are not statistically significant, and adoption of an IIT protocol is not recommended at this time.

Glycaemic control in Australia and New Zealand before and after the NICE-SUGAR trial: a translational study.

IntroductionThere is no information on the uptake of Intensive Insulin Therapy (IIT) before the Normoglycemia in Intensive Care Evaluation and Surviving Using Glucose Algorithm Regulation (NICE-SUGAR) trial in Australia and New Zealand (ANZ) and on the bi-national response to the trial, yet such data would provide important information on the evolution of ANZ practice in this field. We aimed to study ANZ glycaemic control before and after the publication of the results of the NICE-SUGAR trial.MethodsWe analysed glucose control in critically ill patients across Australia and New Zealand during a two-year period before and after the publication of the NICE-SUGAR study. We used the mean first day glucose (Glu1) (a validated surrogate of ICU glucose control) to define practice. The implementation of an IIT protocol was presumed if the median of Glu1 measurements was <6.44 mmol/L for a given ICU. Hypoglycaemia was categorised as severe (glucose ≤2.2 mmol/L) or moderate (glucose ≤3.9 mmol/L).ResultsWe studied 49 ICUs and 176,505 patients. No ICU practiced IIT before or after NICE-SUGAR. Overall, Glu1 increased from 7.96 (2.95) mmol/L to 8.03 (2.92) mmol/L (P <0.0001) after NICE-SUGAR. Similar increases were noted in all patient subgroups studied (surgical, medical, insulin dependent diabetes mellitus, ICU stay >48/<48 hours). The rate of severe and moderate hypoglycaemia before and after NICE-SUGAR study were 0.59% vs. 0.55% (P =0.33) and 6.62% vs. 5.68% (P <0.0001), respectively. Both crude and adjusted mortalities declined over the study period.ConclusionsIIT had not been adopted in ANZ before the NICE-SUGAR study and glycaemic control corresponded to that delivered in the control arm of NICE-SUGAR trial. There were only minor changes in practice after the trial toward looser glycaemic control. The rate of moderate hypoglycaemia and mortality decreased along with such changes.

Risk factors for hypoglycaemia in neurocritical care patients

To identify risk factors for hypoglycaemia in neurocritical care patients receiving intensive insulin therapy (IIT). We performed a nested case-control study. All first episodes of hypoglycaemia (glucose <80 mg/dL, <4.4 mmol/L) in neurocritical care patients between 1 March 2006 and 31 December 2007 were identified. Patients were treated according to the local IIT protocol, with target blood glucose levels between 4.5 and 6.0 mmol/L (81.0-108.0 mg/dL). The first hypoglycaemic event of every patient (index moment) was used to match to a control patient. Possible risk factors preceding the index moment were scored using hospital records and analysed with conditional logistic regression. Of 786 neurocritical care patients, 449 developed hypoglycaemia (57.1 %). Independent risk factors for hypoglycaemia were lowering nutrition 6 h before the index moment without insulin dose reduction (odds ratio (OR) 5.25, 95 % confidence interval (95 % CI) 1.32-20.88), mechanical ventilation (OR 2.59, 95 % CI 1.56-4.29), lowering the dosage of norepinephrine 3 h before the index moment (OR 2.44, 95 % CI 1.07-5.55), a hyperglycaemic event (>10 mmol/L, >180.0 mg/dL) in the 24 h preceding the index moment (OR 2.40, 95 % CI 1.26-4.58), gastric residual in the 6 h preceding the index moment without insulin dose reduction (OR 1.76, 95 % CI 1.05-2.96) and dosage of insulin at the index moment (OR 0.83, 95 % CI 0.76-0.90). Hypoglycaemia occurs in a considerable proportion of neurocritical care patients. We recommend the identification of these risk factors in these patients to avoid the occurrence of hypoglycaemia.

Intensive Insulin Therapy Increases the Risk of Hypoglycemia in Neurocritical Care Patients

Intensive insulin therapy protocols are widely used in intensive care medicine. A disadvantage of these protocols may be the occurrence of hypoglycemic episodes. Neurocritical care patients are particularly vulnerable to the effects of hypoglycemia. We aimed to study the risk of hypoglycemia in neurocritical care patients in relation to intensive insulin therapy. To determine the effects of 2 different intensive insulin therapy protocols on glucose levels and hypoglycemia incidence, we collected data before and after implementation of the protocols in 2 university hospitals. The risk of hypoglycemia (blood glucose level below 3.0 mmol/L) was studied retrospectively with logistic regression analyses. In hospital A, data were obtained on 152 patients before implementation of the protocol and on 649 patients after implementation of the protocol. In hospital B, data were obtained on 111 patients before implementation of the protocol and on 118 patients thereafter. Implementation of intensive insulin therapy protocols increased the time spent in the desired blood glucose range of 4.6 to 6.0 mmol/L in both hospitals, but increased the risk of hypoglycemia: the absolute risk of hypoglycemia during intensive care unit admission increased in hospital A from 14.5% to 20.3% (adjusted odds ratio=1.3; 95% confidence interval: 0.8-2.3) and in hospital B from 3.6% to 29.7% (adjusted odds ratio=28.6; 95% confidence interval: 5.9-138.9). Implementation of intensive insulin therapy protocols in neurocritical care patients not only seems to increase the time spent in the desired blood glucose range, but also seems to increase the risk of hypoglycemia. The risk of hypoglycemia strongly depends on characteristics of the intensive insulin therapy protocol.

Characteristics and effects of nurse dosing over-rides on computer-based intensive insulin therapy protocol performance

To determine characteristics and effects of nurse dosing over-rides of a clinical decision support system (CDSS) for intensive insulin therapy (IIT) in critical care units. Retrospective analysis of patient database records and ethnographic study of nurses using IIT CDSS. The authors determined the frequency, direction-greater than recommended (GTR) and less than recommended (LTR)- and magnitude of over-rides, and then compared recommended and over-ride doses' blood glucose (BG) variability and insulin resistance, two measures of IIT CDSS associated with mortality. The authors hypothesized that rates of hypoglycemia and hyperglycemia would be greater for recommended than over-ride doses. Finally, the authors observed and interviewed nurse users. 5.1% (9075) of 179,452 IIT CDSS doses were over-rides. 83.4% of over-ride doses were LTR, and 45.5% of these were ≥ 50% lower than recommended. In contrast, 78.9% of GTR doses were ≤ 25% higher than recommended. When recommended doses were administered, the rate of hypoglycemia was higher than the rate for GTR (p = 0.257) and LTR (p = 0.033) doses. When recommended doses were administered, the rate of hyperglycemia was lower than the rate for GTR (p = 0.003) and LTR (p < 0.001) doses. Estimates of patients' insulin requirements were higher for LTR doses than recommended and GTR doses. Nurses reported trusting IIT CDSS overall but appeared concerned about recommendations when administering LTR doses. When over-riding IIT CDSS recommendations, nurses overwhelmingly administered LTR doses, which emphasized prevention of hypoglycemia but interfered with hyperglycemia control, especially when BG was >150 mg/dl. Nurses appeared to consider the amount of a recommended insulin dose, not a patient's trend of insulin resistance, when administering LTR doses overall. Over-rides affected IIT CDSS protocol performance.

Glycemic Control: How Tight in the Intensive Care Unit?

Determining the optimal level of glycemic control in critical illness has proven difficult since the original Leuven study conclusions were published in 2001. Conflicting evidence, scientific methodologies, hospital cultures, and a-priori biases have challenged many clinical practice patterns. Specifically, the prioritization of patient safety has resulted in many practitioners changing from a glycemic control target of 80-110 mg/dL to a more liberal target of 140-180 mg/dL. However, a detailed examination of the evidence can provide a more population-specific glycemic control strategy. This position paper presents an approach for cardiac surgery patients in the intensive care unit (ICU) consistent with extant evidence and real-life variables. We argue that in the cardiac surgery ICU, glycemic targets may be as low as 80-110 mg/dL when formal intensive insulin therapy and nutrition support protocols are used with low rates of hypoglycemia, patient safety mechanisms, properly trained staff, and a supportive hospital administration all in force. Cardiac surgery ICUs that already follow this model may continue with 80-110 mg/dL blood glucose targets, whereas others may advance their blood glucose targets in a stepwise fashion: from 140 to 180 mg/dL to 110-140 mg/dL to 80-110 mg/dL, on the basis of their performance.

Intensive insulin therapy improves insulin sensitivity and mitochondrial function in severely burned children*

To institute intensive insulin therapy protocol in an acute pediatric burn unit and study the mechanisms underlying its benefits. Prospective, randomized study. An acute pediatric burn unit in a tertiary teaching hospital. Children, 4-18 yrs old, with total body surface area burned > or =40% and who arrived within 1 wk after injury were enrolled in the study. Patients were randomized to one of two groups. Intensive insulin therapy maintained blood glucose levels between 80 and 110 mg/dL. Conventional insulin therapy maintained blood glucose < or =215 mg/dL. Twenty patients were included in the data analysis consisting of resting energy expenditure, whole body and liver insulin sensitivity, and skeletal muscle mitochondrial function. Studies were performed at 7 days postburn (pretreatment) and at 21 days postburn (posttreatment). Resting energy expenditure significantly increased posttreatment (1476 +/- 124 to 1925 +/- 291 kcal/m(2) x day; p = .02) in conventional insulin therapy as compared with a decline in intensive insulin therapy. Glucose infusion rate was identical between groups before treatment (6.0 +/- 0.8 conventional insulin therapy vs. 6.8 +/- 0.9 mg/kg x min intensive insulin therapy; p = .5). Intensive insulin therapy displayed a significantly higher glucose clamp infusion rate posttreatment (9.1 +/- 1.3 intensive insulin therapy versus 4.8 +/- 0.6 mg/kg x min conventional insulin therapy, p = .005). Suppression of hepatic glucose release was significantly greater in the intensive insulin therapy after treatment compared with conventional insulin therapy (5.0 +/- 0.9 vs. 2.5 +/- 0.6 mg/kg x min; intensive insulin therapy vs. conventional insulin therapy; p = .03). States 3 and 4 mitochondrial oxidation of palmitate significantly improved in intensive insulin therapy (0.9 +/- 0.1 to 1.7 +/- 0.1 microm O(2)/CS/mg protein/min for state 3, p = .004; and 0.7 +/- 0.1 to 1.3 +/- 0.1 microm O(2)/CS/mg protein/min for state 4, p < .002), whereas conventional insulin therapy remained at the same level of activity (0.9 +/- 0.1 to 0.8 +/- 0.1 microm O(2)/CS/mg protein/min for state 3, p = .4; 0.6 +/- 0.03 to 0.7 +/- 0.1 microm O(2)/CS/mg protein/min, p = .6). Controlling blood glucose levels < or =120 mg/dL using an intensive insulin therapy protocol improves insulin sensitivity and mitochondrial oxidative capacity while decreasing resting energy expenditure in severely burned children.

Effects of blood glucose transcription mismatches on a computer-based intensive insulin therapy protocol

Computerized clinical decision support systems (CDSS) for intensive insulin therapy (IIT) generate recommendations using blood glucose (BG) values manually transcribed from testing devices to computers, a potential source of error. We quantified the frequency and effect of blood glucose transcription mismatches on IIT protocol performance. We examined 38 months of retrospective data for patients treated with CDSS IIT in two intensive care units at one teaching hospital. A manually transcribed BG value not equal to a corresponding device value was deemed mismatched. For mismatches we recalculated CDSS recommendations using device BG values. We compared matched and mismatched data in terms of CDSS alerts, blood glucose variability, and dosing. Of 189,499 CDSS IIT instances, 5.3% contained mismatched BG values. Mismatched data triggered 93 false alerts and failed to issue 170 alerts for nurses to notify physicians. Four of six BG variability measures differed between matched and mismatched data. Overall insulin dose was greater for matched than mismatched [matched 3.8 (1.6-6.0), median (interquartile range, IQR), versus 3.6 (1.6-5.7); p < 0.001], but recalculated and actual dose were similar. In mismatches preceding hypoglycemia, recalculated insulin dose was significantly lower than actual dose [recalculated 2.7 (0.4-5.0), median (IQR), versus 3.5 (1.4-5.6)]. In mismatches preceding hyperglycemia, recalculated insulin dose was significantly greater than actual dose [recalculated 4.7 (3.3-6.2), median (IQR), versus 3.3 (2.4-4.3); p < 0.001]. Administration of recalculated doses might have prevented blood glucose excursions. Mismatched blood glucose values can influence CDSS IIT protocol performance.

Implementation of an Inpatient Diabetes Management Team in the University Hospital Setting

A long history of clinical evidence points out the untoward effects of hyperglycemia in humans. Hyperglycemia acutely impairs leukocyte function, immunoglobulin action, wound healing, cardiac metabolism, glomerular filtration, and endothelial function.1 In addition, the stress of critical illness causes an increase in counterregulatory hormones. This leads to alterations in carbohydrate metabolism by increasing peripheral glucose demand and enhancing hepatic glucose production and insulin resistance, which results in a relative insulin deficiency and hyperglycemia.2 Moreover, clinical interventions also predispose patients to hyperglycemia, particularly the use of corticosteroids, vasopressors, and enteral or parenteral nutrition.3 In a study by Umpierrez et al.,4 hyperglycemia (defined as a fasting blood glucose level > 126 mg/dl or a random blood glucose level > 200 mg/dl on two separate occasions) occurred in 38% of hospitalized patients. Twenty-six percent of these patients with hyperglycemia had a known history of diabetes, but 12% had no history of diabetes. Newly discovered hyperglycemia was associated with longer hospital stays, higher admission rates to the intensive care unit, and a greater chance of being discharged to a rehabilitation facility than of being discharged home. The take-home message is that hyperglycemia is common in patients during hospitalization, and this hyperglycemia is associated with adverse outcomes. A variety of approaches, most involving development and use of intensive insulin therapy protocols to improve glucose management in the hospital setting, seem to improve metabolic outcomes. Whether these approaches improve actual outcomes of morbidity and mortality is not yet known outside of the critical care setting. Several early clinical trials suggest a benefit of intensive glucose control in the critical care setting on morbidity (especially infection), length of stay, hospital costs, and mortality in selected groups of patients.5,6 More recently, clinical trials involving intensive insulin therapy in critical care units …

Pilot Evaluation of a Prototype Critical Care Blood Glucose Monitor in Normal Volunteers

Availability of a highly accurate in-hospital automated blood glucose (BG) monitor could facilitate implementation of intensive insulin therapy protocols through effective titration of insulin therapy, improved BG control, and avoidance of hypoglycemia. We evaluated a functional prototype BG monitor designed to perform frequent automated blood sampling for glucose monitoring. Sixteen healthy adult volunteer subjects had intravenous catheter insertions in a forearm or hand vein and were studied for 8 hours. The prototype monitor consisted of an autosampling unit with a precise computer-controlled reversible syringe pump and a glucose analytical section. BG was referenced against a Yellow Springs Instrument (YSI) laboratory analyzer. Sampling errors for automated blood draws were assessed by calculating the percent of failed draws, and BG data were analyzed using the Bland and Altman technique. Out of 498 total sample draws, unsuccessful draws were categorized as follow: 11 (2.2%) were due to autosampler technical problems, 21 (4.2%) were due to catheter-related failures, and 37 (7.4%) were BG meter errors confirmed by a glucometer-generated error code. Blood draw difficulties or failures related to the catheter site (e.g., catheter occlusion or vein collapse) occurred in 6/15 (40%) subjects. Mean BG bias versus YSI was 0.20 +/- 12.6 mg/dl, and mean absolute relative difference was 10.4%. Automated phlebotomy can be performed in healthy subjects using this prototype BG monitor. The BG measurement technology had suboptimal accuracy based on a YSI reference. A more accurate BG point-of-care testing meter and strip technology have been incorporated into the future version of this monitor. Development of such a monitor could alleviate the burden of frequent BG testing and reduce the risk of hypoglycemia in patients on insulin therapy.

Intensive insulin therapy on infection rate, days in NICU, in-hospital mortality and neurological outcome in severe traumatic brain injury patients: A randomized controlled trial

Objectives Evaluate the impact of an intensive insulin therapy and conventional glucose control protocol during staying in neurological intensive care unit (NICU) on infection rate, days in NICU, in-hospital mortality and long-term neurological outcome in severe traumatic brain injury (TBI) patients. Methods A total of 240 patients with severe TBI (GCS score 3–8) admitted to NICU were prospectively enrolled and randomly assigned either to conventional insulin therapy or to intensive insulin therapy. Patients in intensive glucose control group ( n = 121) received continuous insulin infusion to maintain glucose levels between 4.4 mmol/l (80 mg/dl) and 6.1 mmol/l (110 mg/dl). Patients in the conventional treatment group ( n = 119) were not given insulin unless glucose levels were greater than 11.1 mmol/l (200 mg/dl). Both groups were treated with insulin infusion to maintain normoglycemia after leaving NICU. Comparison was made against conventional insulin therapy using a randomized trial design. The primary outcomes is the mortality rate at 6 months follow-up. The second outcomes including ICU infection rate, duration of ICU stay, in-hospital mortality rate and neurologic outcome at 6 months follow-up. Results There was no significant difference in gender (66% vs. 67% male), age (46 ± 11 years vs. 45 ± 10 years), APACHE II score (30 vs. 29), TISS-28 score (47 vs. 46), and Glasgow Coma Score (GCS, 5.3 vs. 5.3) between the two groups. Overall mortality rates at 6 months follow-up were similar in the 2 groups (61 of 117, 52.1% vs. 62 of 116, 53.4%; P = 0.8). The infection rate during the study was significantly higher in patients who received conventional insulin therapy than that in patients who received intensive insulin therapy (46.2% vs. 31.4%; P < 0.05). The days stay in NICU was shorter in intensive insulin control group than that in conventional therapy group [4.2 days vs. 5.6 days (medians) P < 0.05]. The in-hospital mortality during the study was similar in conventional and intensive therapy groups (34 of 119, 28.6% vs. 35 of 121, 28.9% in the conventional and intensive insulin therapy groups; P = 0.85). The neurologic outcome according to Glasgow Outcome Score (GOS) at 6 months (GOS 5 and 4) was better in the intensive insulin therapy group (34 of 117, 29.1%) than that in the conventional therapy group (26 of 116, 22.4%, P < 0.05). Conclusions Mortality rates at 6 months follow-up are not affected by intensive glucose control in patients with severe TBI. Intensive insulin therapy decreases infection rate and days in NICU and improves the neurological outcome at 6 months follow-up, while has no obvious influence on in-hospital mortality of severe TBI patients.

Blood glucose control and prognosis of critical ill patients

Critically ill patients commonly incorporate with hyperglycemia. Many recent studies have demonstrated that strictly controlling glucose may decrease the morbidity and mortality of complication of patients with critical illness. This review introduces the pathophysiological mechanism and diagnosis of hyperglycemia, the importance and methods of blood glucose control and intensive insulin therapy protocol. Key words: hyperglycemia; critical illness ; glucose control; outcome

An adaptive clinical Type 1 diabetes control protocol to optimize conventional self‐monitoring blood glucose and multiple daily‐injection therapy

AbstractThe objective of this study was to develop a safe, robust and effective protocol for the clinical control of Type 1 diabetes using conventional self‐monitoring blood glucose (SMBG) measurements, and multiple daily injection (MDI) with insulin analogues.A virtual patient method is used to develop an in silico simulation tool for Type 1 diabetes using data from a Type 1 diabetes patient cohort (n=40) . The tool is used to test two prandial insulin protocols, an adaptive protocol (AC) and a conventional intensive insulin therapy (IIT) protocol (CC) against results from a representative control cohort as a function of SMBG frequency. With the prandial protocols, optimal and suboptimal basal insulin replacement using a clinically validated, forced‐titration regimen is also evaluated. A Monte Carlo (MC) analysis using variability and error distributions derived from the clinical and physiological literature is used to test efficacy and robustness. MC analysis is performed for over 1 400 000 simulated patient hours. All results are compared with control data from which the virtual patients were derived.In conditions of suboptimal basal insulin replacement, the AC protocol significantly decreases HbA1c for SMBG frequencies ⩾6/day compared with controls and the CC protocol. With optimal basal insulin, mild and severe hypoglycaemia is reduced by 86–100% over controls for all SMBG frequencies. Control with the CC protocol and suboptimal basal insulin replacement saturates at an SMBG frequency of 6/day. The forced‐titration regimen requires a minimum SMBG frequency of 6/day to prevent increased hypoglycaemia. Overaggressive basal dose titration with the CC protocol at lower SMBG frequencies is likely caused by uncorrected postprandial hyperglycaemia from the previous night.From the MC analysis, a defined peak in control is achieved at an SMBG frequency of 8/day. However, 90% of the cohort meets American Diabetes Association recommended HbA1c with just 2 measurements a day. A further 7.5% requires 4 measurements a day and only 2.5% (1 patient) required 6 measurements a day. In safety, the AC protocol is the most robust to applied MC error. Over all SMBG frequencies, the median for severe hypoglycaemia increases from 0 to 0.12% and for mild hypoglycaemia by 0–5.19% compared with the unrealistic no error simulation. While statistically significant, these figures are still very low and the distributions are well below those of the controls group.An adaptive control protocol for Type 1 diabetes is tested in silico under conditions of realistic variability and error. The adaptive (AC) protocol is effective and safe compared with conventional IIT (CC) and controls. As the fear of hypoglycaemia is a large psychological barrier to appropriate glycaemic control, adaptive model‐based protocols may represent the next evolution of IIT to deliver increased glycaemic control with increased safety over conventional methods, while still utilizing the most commonly used forms of intervention (SMBG and MDI). The use of MC methods to evaluate them provides a relevant robustness test that is not considered in the no error analyses of most other studies. Copyright © 2008 John Wiley &amp; Sons, Ltd.

Intensive Insulin Therapy in Practice: Can We Do It?

Intensive insulin therapy (IIT) is the standard of care in the ICU, but precise implementation of insulin protocols has been difficult in clinical practice. The authors' objective was to quantify adherence to an IIT protocol in a practice setting, and to describe how adherence impacts overall blood glucose (BG) control. A retrospective analysis of a cohort of critically ill patients treated with IIT was performed. Protocol adherence was evaluated by assessing the timing of BG measurements. Each measurement was categorized according to the time from the previous reading: early (<1 hour), on time (1-3 hours), and late (>3 hours). Outcome measures included mean and median BG for each time category as well as the proportion of values within the target range. In 1106 trauma and surgical ICU patients, 54,139 measurements were available for analysis. The overall mean BG (116 mg/dL) was near the target (80-110 mg/dL), but only 46% of values were within this range. There were 45,806 (86%) measurements on time, 2749 (5%) early, and 4478 (9%) were late. BG values of late measurements were less likely to be within range (34% vs 46% for on time measurements, P<.001). Of late measurements, 19% were >200 mg/dL, 13% were 150-200 mg/dL, and 16% were <60 mg/dL. IIT is difficult to implement precisely in a complex ICU environment. Measurement timing impacts overall BG control, with late measurements more often associated with severe hyperglycemic (BG>150 mg/dL) and hypoglycemic (BG<60 mg/dL) episodes.

Intensive insulin therapy is associated with reduced infectious complications in burn patients

Intensive insulin therapy to control blood glucose levels has reduced mortality in surgical, but not medical, intensive care unit (ICU) patients. Control of blood glucose levels has also been shown to reduce morbidity in surgical ICU patients. There is very little data for use of intensive insulin therapy in the burn patient population. We sought to evaluate our experience with intensive insulin therapy in burn-injured ICU patients with regard to mortality, morbidity, and use of hospital resources. Burn patients admitted to our American College of Surgeons verified burn center ICU from 7/1/2004 to 6/30/2006 were studied. An intensive insulin therapy protocol was initiated for ICU patients admitted starting 7/1/2005 with a blood glucose target of 100-140 mg/dL. The 2 groups of patients studied were control (7/1/2004 to 6/30/2005) and intensive insulin therapy (7/1/2005 to 6/30/2006). All glucose values for the hospitalization were analyzed. Univariate and multivariate analyses were performed. Overall, 152 ICU patients admitted with burn injury were available for study. No difference in mortality was evident between the control and intensive insulin therapy groups. After adjusting for patient risk, the intensive insulin therapy group was found to have a decreased rate of pneumonia, ventilator-associated pneumonia, and urinary tract infection. In patients with a maximum glucose value of greater than 140 mg/dL, the risk for an infection was significantly increased (OR 11.3, 95% CI 4-32, P-value < .001). The presence of a maximum glucose value greater than 140 mg/dL was associated with a sensitivity of 91% and specificity of 62% for an infectious complication. Intensive insulin therapy for burn-injured patients admitted to the ICU was associated with a reduced incidence of pneumonia, ventilator-associated pneumonia, and urinary tract infection. Intensive insulin therapy did not result in a change in mortality or length of stay when adjusting for confounding variables. Measurement of a blood glucose level greater than 140 mg/dL should heighten the clinical suspicion for the presence of an infection in patients with burn injury.

How does blood glucose control with metformin influence intensive insulin protocols? Evidence for involvement of oxidative stress and inflammatory cytokines

Recent investigations have revealed that control of hyperglycaemia with insulin improves outcomes. The cornerstone of hyperglycaemia in critically ill patients is insulin resistance and it remains refractory to intensive insulin protocols. We designed this study to evaluate the efficacy and safety of a new intensive insulin therapy (IIT) protocol combined with metformin. Twenty-one patients with systemic inflammatory response syndrome and a blood glucose level of >120 mg/dl admitted to an intensive care unit (ICU) were randomised to receive either intravenous infusion of IIT alone (n=11) or combined with metformin (IIT+MET; n=10) to maintain a blood glucose level (BGL) of 80-120 mg/dl. Blood samples were obtained at baseline and at 48 hours, 96 hours and 7 days after initiation of the study. Samples were analysed for interleukin-6 (IL-6), tumour necrosis factor alpha (TNF-alpha) and nitric oxide (NO) as inflammatory mediators; plasminogen activation inhibitor-1 (PAI-1) as a coagulation mediator; and thiobarbituric reactive substances (TBARS), total antioxidant power (TAP) and total thiol molecules (TTM) as oxidative stress parameters. The addition of metformin to the IIT protocol decreased insulin requirement and concentration of insulin and C-peptide. With both treatments at most time points, the mean plasma levels of IL-6, TNF-alpha, NO, PAI-1 and TBARS were found to be significantly lower compared with baseline. Antioxidant activity was increased in both arms with increasing TAP and TTM (P<0.05). There was no significant difference between the two groups regarding reported beneficial effects on these parameters. Therapeutic Intervention Scoring System-28 (TISS-28) score, an index of nursing workload and number of therapeutic interventions, decreased in the IIT+MET group (P<0.01). We did not observe any occurrence of hyperlactataemia or acidosis in the IIT+MET group. Metformin plus insulin appears to lower the incidence of insulin resistance, lower insulin requirement while maintaining blood glucose level control, and consequently lower the incidence of adverse effects related to high-dose insulin therapy, particularly hypoglycaemia, and also declined nursing workload. Both treatment protocols showed improvements in inflammatory cytokine levels. Further studies with larger sample sizes are warranted to determine the undiscovered facts of insulin-sensitising agents in critically ill patients.

Improvement in Glycemic Control and Outcome Corresponding to Intensive Insulin Therapy Protocol Development

Intensive insulin therapy (IIT) has been shown to reduce mortality and morbidity in longer stay, critically ill patients. However, this has been demonstrated in a single site, whereas two multicentric studies have been terminated prematurely mainly due to hypoglycemia. Other difficulties with IIT include efficacy of glycemic control. This report describes how IIT can be improved by protocol simplification and removal of glucose supplementation. A clinical information system established at each bedspace guided staff through the IIT algorithms. Time spent within predefined glycemic ranges was calculated assuming a linear trend between successive measurements. Three groups were investigated retrospectively: IIT1 protocol,(1) an updated IIT2 version, and intuitive nurse dosing of conventional insulin therapy (CIT). Fifty consecutive, critically ill patients were included in each study group. Patient characteristics were similar in each group. The frequency of CIT and IIT2 blood glucose measurements were 11.6 and 11.5 measurements per day, respectively, while the IIT1 measurements were more frequent (14.5 measurements per day). The mean proportion of time spent in the target glycemic range (4.4-6.1 mmol/liter) was highest in the IIT2 group (34.9%), as compared to the IIT1 (22.9%) and CIT groups (20.3%) (p <.001). Survival at 28 days was 74.5% for IIT2 (highest), 68% for IIT1, and 48% for CIT (p = .02). There were a similar number of those experiencing a severe hypoglycemic event in each group. IIT protocol optimization was associated with increased glycemic control and improved 28-day survival. The better optimized IIT2 protocol provided tighter control than either the IIT1 or CIT protocol, without increased sampling or incidence of hypoglycemia. The clinical effectiveness of the IIT algorithm appeared to be improved by simplifying the protocol to meet the needs of the critical care unit.