Introduction

The purpose of this research is to provide recommendations for the management of glycemic control in critically ill patients.

Methods

Twenty-one experts issued recommendations related to one of the five pre-defined categories (glucose target, hypoglycemia, carbohydrate intake, monitoring of glycemia, algorithms and protocols), that were scored on a scale to obtain a strong or weak agreement. The GRADE (Grade of Recommendation, Assessment, Development and Evaluation) system was used, with a strong recommendation indicating a clear advantage for an intervention and a weak recommendation indicating that the balance between desirable and undesirable effects of an intervention is not clearly defined.

Results

A glucose target of less than 10 mmol/L is strongly suggested, using intravenous insulin following a standard protocol, when spontaneous food intake is not possible. Definition of the severe hypoglycemia threshold of 2.2 mmol/L is recommended, regardless of the clinical signs. A general, unique amount of glucose (enteral/parenteral) to administer for any patient cannot be suggested. Glucose measurements should be performed on arterial rather than venous or capillary samples, using central lab or blood gas analysers rather than point-of-care glucose readers.

Conclusions

Thirty recommendations were obtained with a strong (21) and a weak (9) agreement. Among them, only 15 were graded with a high level of quality of evidence, underlying the necessity to continue clinical studies in order to improve the risk-to-benefit ratio of glucose control.

The description of a new score of nutrition risk in critically ill patients in the previous issue of Critical Care is very appropriate and timely. However, the use of this score will probably not help the clinician to improve the prescription of nutrition therapy, especially when major uncertainties are raised about the definition of adequate nutrition. The validation of the score will require the use of outcome variables susceptible to influence by nutrition, such as surrogate markers of muscle function. Meanwhile the educational value of a score of nutrition risk is undisputed in settings where the use of scores is incorporated into the usual practice.

The use or misuse of statins in critically ill patients recently attracted the attention of intensive care clinicians. Indeed, statins are probably the most common chronic treatment before critical illness and some recent experimental and clinical data demonstrated their beneficial effects during sepsis, acute lung injury (ALI)/acute respiratory distress syndrome (ARDS), or after aneurismal subarachnoidal hemorrhage (aSAH). Due to the heterogeneity of current studies and the lack of well-designed prospective studies, definitive conclusions for systematic and large-scale utilization in intensive care units cannot be drawn from the published evidence. Furthermore, the extent of statins side effects in critically ill patients is still unknown. For the intensive care clinician, it is a matter of individually identifying the patient who can benefit from this therapy according to the current literature. The purpose of this review is to describe the mechanisms of actions of statins and to synthesize the clinical data that underline the relevant effects of statins in the particular setting of critical care, in an attempt to guide the clinician through his daily practice.

Background

Effective tight glycemic control (TGC) can improve outcomes in critical care patients, but it is difficult to achieve consistently. Insulin sensitivity defines the metabolic balance between insulin concentration and insulin-mediated glucose disposal. Hence, variability of insulin sensitivity can cause variable glycemia. This study quantifies and compares the daily evolution of insulin sensitivity level and variability for critical care patients receiving TGC.

Methods

This is a retrospective analysis of data from the SPRINT TGC study involving patients admitted to a mixed medical-surgical ICU between August 2005 and May 2007. Only patients who commenced TGC within 12 hours of ICU admission and spent at least 24 hours on the SPRINT protocol were included (N = 164). Model-based insulin sensitivity (SI) was identified each hour. Absolute level and hour-to-hour percent changes in SI were assessed on cohort and per-patient bases. Levels and variability of SI were compared over time on 24-hour and 6-hour timescales for the first 4 days of ICU stay.

Results

Cohort and per-patient median SI levels increased by 34% and 33% (p < 0.001) between days 1 and 2 of ICU stay. Concomitantly, cohort and per-patient SI variability decreased by 32% and 36% (p < 0.001). For 72% of the cohort, median SI on day 2 was higher than on day 1. The day 1–2 results are the only clear, statistically significant trends across both analyses. Analysis of the first 24 hours using 6-hour blocks of SI data showed that most of the improvement in insulin sensitivity level and variability seen between days 1 and 2 occurred during the first 12–18 hours of day 1.

Conclusions

Critically ill patients have significantly lower and more variable insulin sensitivity on day 1 than later in their ICU stay and particularly during the first 12 hours. This rapid improvement is likely due to the decline of counter-regulatory hormones as the acute phase of critical illness progresses. Clinically, these results suggest that while using TGC protocols with patients during their first few days of ICU stay, extra care should be afforded. Increased measurement frequency, higher target glycemic bands, conservative insulin dosing, and modulation of carbohydrate nutrition should be considered to minimize safely the outcome glycemic variability and reduce the risk of hypoglycemia.

The major interventional trials of intensive insulin therapy in critically ill patients have reached divergent results. The present viewpoint article explores some of the potential reasons, including differences in monitoring technology and protocol design and performance, the occurrence of severe hypoglycemia and changes in the standard of care since publication of the landmark single-center trial. Recently published data detailing the deleterious effect of hypoglycemia are discussed, as is the emerging body of literature describing the important impact of glycemic variability on the risk of mortality in heterogeneous populations of acutely ill and severely ill patients. These new findings have important implications for the design of future interventional trials of intensive insulin therapy in the intensive care unit setting.

Background

Hypoglycemia is associated with increased mortality in critically ill patients. The impact of hypoglycemia on resource utilization has not been investigated. The objective of this investigation was to evaluate the association of hypoglycemia, defined as a blood glucose concentration (BG) < 70 mg/dL, and intensive care unit (ICU) length of stay (LOS) in three different cohorts of critically ill patients.

Methods

This is a retrospective investigation of prospectively collected data, including patients from two large observational cohorts: 3,263 patients admitted to Stamford Hospital (ST) and 2,063 patients admitted to three institutions in The Netherlands (NL) as well as 914 patients from the GLUCONTROL trial (GL), a multicenter prospective randomized controlled trial of intensive insulin therapy.

Results

Patients with hypoglycemia were more likely to be diabetic, had higher APACHE II scores, and higher mortality than did patients without hypoglycemia. Patients with hypoglycemia had longer ICU LOS (median [interquartile range]) in ST (3.0 [1.4-7.1] vs. 1.2 [0.8-2.3] days, P < 0.0001), NL (5.2 [2.6-10.3] vs. 2.0 [1.3-3.2] days, P < 0.0001), and GL (9 [5-17] vs. 5 [3-9] days, P < 0.0001). For the entire cohort of 6,240 patients ICU LOS was 1.8 (1.0-3.3) days for those without hypoglycemia and 3.0 (1.5-6.7) days for those with a single episode of hypoglycemia (P < 0.0001). This was a consistent finding even when patients were stratified by severity of illness or survivor status. There was a strong positive correlation between the number of episodes of hypoglycemia and ICU LOS among all three cohorts.

Conclusions

This multicenter international investigation demonstrated that hypoglycemia was consistently associated with significantly higher ICU LOS in heterogeneous cohorts of critically ill patients, independently of severity of illness and survivor status. More effective methods to prevent hypoglycemia in these patients may positively impact their cost of care.

Novel insights into the metabolic alterations of critical illness were published in Critical Care in 2009. The association between early hypoglycaemia/high glycemic variability and poor outcome was confirmed. Improvements in the understanding of the pathophysiological mechanisms of stress hyperglycemia and potential progress in the bedside management of glucose control were presented. With regard to enteral nutrition, some alterations of gastrointestinal physiology were better delineated. The relationship between the achievement of nutritional goals and outcomes was further investigated. Finally, understanding of some critical-illness-related endocrine and neuromuscular disorders improved through new experimental and clinical findings.

Background

In-silico virtual patients and trials offer significant advantages in cost, time and safety for designing effective tight glycemic control (TGC) protocols. However, no such method has fully validated the independence of virtual patients (or resulting clinical trial predictions) from the data used to create them. This study uses matched cohorts from a TGC clinical trial to validate virtual patients and in-silico virtual trial models and methods.

Methods

Data from a 211 patient subset of the Glucontrol trial in Liege, Belgium. Glucontrol-A (N = 142) targeted 4.4-6.1 mmol/L and Glucontrol-B (N = 69) targeted 7.8-10.0 mmol/L. Cohorts were matched by APACHE II score, initial BG, age, weight, BMI and sex (p > 0.25). Virtual patients are created by fitting a clinically validated model to clinical data, yielding time varying insulin sensitivity profiles (SI(t)) that drives in-silico patients.

Model fit and intra-patient (forward) prediction errors are used to validate individual in-silico virtual patients. Self-validation (tests A protocol on Group-A virtual patients; and B protocol on B virtual patients) and cross-validation (tests A protocol on Group-B virtual patients; and B protocol on A virtual patients) are used in comparison to clinical data to assess ability to predict clinical trial results.

Results

Model fit errors were small (<0.25%) for all patients, indicating model fitness. Median forward prediction errors were: 4.3, 2.8 and 3.5% for Group-A, Group-B and Overall (A+B), indicating individual virtual patients were accurate representations of real patients. SI and its variability were similar between cohorts indicating they were metabolically similar.

Self and cross validation results were within 1-10% of the clinical data for both Group-A and Group-B. Self-validation indicated clinically insignificant errors due to model and/or clinical compliance. Cross-validation clearly showed that virtual patients enabled by identified patient-specific SI(t) profiles can accurately predict the performance of independent and different TGC protocols.

Conclusions

This study fully validates these virtual patients and in silico virtual trial methods, and clearly shows they can accurately simulate, in advance, the clinical results of a TGC protocol, enabling rapid in silico protocol design and optimization. These outcomes provide the first rigorous validation of a virtual in-silico patient and virtual trials methodology.

Hypoglycemia is a common and serious problem among patients with diabetes mellitus. It is also perceived as the most important obstacle to tight glucose control using intensive insulin therapy in critically ill patients. Because glucose is an obligatory metabolic fuel for the brain, hypoglycemia always represents an emergency that signals the inability of the brain to meet its energy needs. When left untreated, hypoglycemia can result in permanent brain damage and ultimately, death. In the context of critical illness that limits endogenous glucose production and increases glucose utilization, inadequate nutrition, or insufficient provision of glucose, intensive insulin therapy is the most frequent cause of hypoglycemia. Neurogenic and neuroglycopenic symptoms of hypoglycemia can remain unknown because of the underlying critical illness and sedation. Thus, close and reliable monitoring of the glycemic level is crucial in detecting hypoglycemia. In prospective randomized controlled studies comparing the effects of two glucose regimens, intensive insulin therapy aimed to reach strict glucose control (<110 mg/dl) but increased the incidence of severe hypoglycemia (<40 mg/dl) by four- to sixfold. Severe hypoglycemia is statistically associated with adverse outcomes in intensive care unit patients, although a direct causal relationship has not been demonstrated.

In 2008, the interest in metabolic and endocrine issues and their consequences in critically ill patients was high. A large proportion of the research papers related to these issues was related to the metabolism of glucose and its control and to the changes in body composition, including muscular weakness. In Critical Care, original reports from investigations of glucose physiology and clinical data from observational and interventional studies were published. Important reports of the effects of hormone analogues, such as vasopressin and hydrocortisone, and early antioxidants in selected subpopulations were also available in 2008.

Introduction

Intensive care unit mortality is strongly associated with organ failure rate and severity. The sequential organ failure assessment (SOFA) score is used to evaluate the impact of a successful tight glycemic control (TGC) intervention (SPRINT) on organ failure, morbidity, and thus mortality.

Methods

A retrospective analysis of 371 patients (3,356 days) on SPRINT (August 2005 - April 2007) and 413 retrospective patients (3,211 days) from two years prior, matched by Acute Physiology and Chronic Health Evaluation (APACHE) III. SOFA is calculated daily for each patient. The effect of the SPRINT TGC intervention is assessed by comparing the percentage of patients with SOFA ≤5 each day and its trends over time and cohort/group. Organ-failure free days (all SOFA components ≤2) and number of organ failures (SOFA components >2) are also compared. Cumulative time in 4.0 to 7.0 mmol/L band (cTIB) was evaluated daily to link tightness and consistency of TGC (cTIB ≥0.5) to SOFA ≤5 using conditional and joint probabilities.

Results

Admission and maximum SOFA scores were similar (P = 0.20; P = 0.76), with similar time to maximum (median: one day; IQR: [1,3] days; P = 0.99). Median length of stay was similar (4.1 days SPRINT and 3.8 days Pre-SPRINT; P = 0.94). The percentage of patients with SOFA ≤5 is different over the first 14 days (P = 0.016), rising to approximately 75% for Pre-SPRINT and approximately 85% for SPRINT, with clear separation after two days. Organ-failure-free days were different (SPRINT = 41.6%; Pre-SPRINT = 36.5%; P < 0.0001) as were the percent of total possible organ failures (SPRINT = 16.0%; Pre-SPRINT = 19.0%; P < 0.0001). By Day 3 over 90% of SPRINT patients had cTIB ≥0.5 (37% Pre-SPRINT) reaching 100% by Day 7 (50% Pre-SPRINT). Conditional and joint probabilities indicate tighter, more consistent TGC under SPRINT (cTIB ≥0.5) increased the likelihood SOFA ≤5.

Conclusions

SPRINT TGC resolved organ failure faster, and for more patients, from similar admission and maximum SOFA scores, than conventional control. These reductions mirror the reduced mortality with SPRINT. The cTIB ≥0.5 metric provides a first benchmark linking TGC quality to organ failure. These results support other physiological and clinical results indicating the role tight, consistent TGC can play in reducing organ failure, morbidity and mortality, and should be validated on data from randomised trials.

The results of the NICE-SUGAR (Normoglycaemia in Intensive Care Evaluation Survival Using Glucose Algorithm Regulation) trial were released last March. The primary outcome variable, 90-day mortality, was actually increased in patients randomly assigned to intensive insulin therapy, as compared with an intermediate target range for blood glucose. These findings, reflecting data collected in a set of more than 6,000 patients, clearly refute the external validity of tight glucose control. Future research will probably focus on several questions raised by the divergent results reported from investigations in the field of glucose control in the critically ill.

Introduction

This was a planned substudy from the European observational Sepsis Occurrence in Acutely ill Patients (SOAP) study to investigate the possible impact of insulin-treated diabetes on morbidity and mortality in ICU patients.

Methods

The SOAP study was a cohort, multicenter, observational study which included data from all adult patients admitted to one of 198 participating ICUs from 24 European countries during the study period. For this substudy, patients were classified according to whether or not they had a known diagnosis of insulin-treated diabetes mellitus. Outcome measures included the degree of organ dysfunction/failure as assessed by the sequential organ failure assessment (SOFA) score, the occurrence of sepsis syndromes and organ failure in the ICU, hospital and ICU length of stay, and all cause hospital and ICU mortality.

Results

Of the 3147 patients included in the SOAP study, 226 (7.2%) had previously diagnosed insulin-treated diabetes mellitus. On admission, patients with insulin-treated diabetes were older, sicker, as reflected by higher simplified acute physiology system II (SAPS II) and SOFA scores, and more likely to be receiving hemodialysis than the other patients. During the ICU stay, more patients with insulin-treated diabetes required renal replacement therapy (hemodialysis or hemofiltration) than other patients. There were no significant differences in ICU or hospital lengths of stay or in ICU or hospital mortality between patients with or without insulin-treated diabetes. Using a Cox proportional hazards regression analysis with hospital mortality censored at 28-days as the dependent factor, insulin-treated diabetes was not an independent predictor of mortality.

Conclusions

Even though patients with a history of insulin-treated diabetes are more severely ill and more likely to have renal failure, insulin-treated diabetes is not associated with increased mortality in ICU patients.

The report by Chase and coworkers in the previous issue of Critical Care describes the implementation into clinical practice of the Specialized Relative Insulin Nutrition Table (SPRINT) for tight glycaemic control in critically ill patients. SPRINT is a simple, wheel-based system that modulates both insulin rate and nutritional inputs. It achieved a better glycaemic control in a severely ill critical cohort than their previous method for glycaemic control in a matched historical cohort. Reductions in mortality were also observed.

The impressive benefits related to the use of tight glucose control by intensive insulin therapy have not been reproduced until now in multicenter large-scale prospective randomized trials. Although the reasons for these failures are not entirely clear, we suggest the use of a stepwise approach – Safe, Effective Glucose Control – that will essentially target an intermediate blood glucose level. As compared with genuine tight glucose control, Safe, Effective Glucose Control – already used in many intensive care units worldwide – is intended to decrease the rate of hypoglycemia and the workload, while reducing the adverse effects of severe hyperglycemia.

Three independent studies of tight glucose control were recently stopped prematurely due to an excess mortality in the intensive treatment arm. This commentary briefly discusses the potential mechanisms and reminds the potential benefits of physiological stress hyperglycemia.

The second study on tight glycaemia control by intensive insulin therapy (IIT) confirmed in medical intensive care unit patients the decrease in hospital mortality reported by the same team in the first IIT trial in surgical patients. However, methodological concerns, the high rate of hypoglycaemia in spite of the infusion of large doses of parenteral glucose and the frequent use of steroids presently preclude considering these results as recommendations in other intensive care units, but rather argue for the need for large-scale assessment of the IIT approach by multi-centre studies to confirm the efficacy and safety of this therapeutic modality.

The issue of tight glucose control with intensive insulin therapy in critically ill patients remains controversial. Although compelling evidence supports this strategy in postoperative patients who have undergone cardiac surgery, the use of tight glucose control has been challenged in other situations, including in medical critically ill patients and in those who have undergone non-cardiac surgery. Similarly, the mechanisms that underlie the effects of high-dose insulin are not fully elucidated. These arguments emphasize the need to study the effects of tight glucose control in a large heterogeneous cohort of intensive care unit patients.

Background

Addition of glutamine to enteral nutrition formulas is consistently associated with a significant decrease in septic morbidity in critically ill patients, possibly related to the attenuation of gut dysfunction. This pilot study was undertaken to compare the effects of enteral administration of two glutamine-enriched formulas containing either additional free glutamine or glutamine-rich proteins, with a standard solution on plasma and mucosal concentrations of glutamine in patients admitted in the Department of Intensive Care.

Methods

Following randomization, glutamine concentration was determined in endoscopically sampled duodenal biopsies and plasma, before and after a 7-day period of continuous administration of the designated solution.

Results

The mucosal concentration of glutamine increased in the duodenal biopsies sampled from patients randomized to the solution containing the glutamine-rich proteins (from 3.6 ± 2.2 to 6.7 ± 5.2 micro-mol/g protein), but not from the others. There were no differences between the 3 groups in the plasma concentrations of glutamine, which remained stable over time.

Conclusion

The source of supplemental glutamine can influence gut mucosal glutamine concentrations, suggesting differences in its availability or utilization.

Objective

Treatment and prevention of hyperglycemia has been advocated for subjects with sepsis. Glucose variability, rather than the glucose level, has also been shown to be an important factor associated with in-hospital mortality, in general, critically ill patients. Our objective was to determine the association between glucose variability and hospital mortality in septic patients and the expression of glucose variability that best reflects this risk.

Design

Retrospective, single-center cohort study.

Setting

Academic, tertiary care hospital.

Patients

Adult subjects hospitalized for >1 day, with a diagnosis of sepsis were included.

Interventions

None.

Measurements

Glucose variability was calculated for all subjects as the average and standard deviation of glucose, the mean amplitude of glycemic excursions, and the glycemic lability index. Hospital mortality was the primary outcome variable. Logistic regression was used to determine the odds of hospital death in relation to measures of glucose variability after adjustment for important covariates.

Main results

Of the methods used to measure glucose variability, the glycemic lability index had the best discrimination for mortality (area under the curve = 0.67, p < 0.001). After adjustment for confounders, including the number of organ failures and the occurrence of hypoglycemia, there was a significant interaction between glycemic lability index and average glucose level, and the odds of hospital mortality. Higher glycemic lability index was not independently associated with mortality among subjects with average glucose levels above the median for the cohort. However, subjects with increased glycemic lability index, but lower average glucose values had almost five-fold increased odds of hospital mortality (odds ratio = 4.73, 95% confidence interval = 2.6 – 8.7) compared with those with lower glycemic lability index.

Conclusions

Glucose variability is independently associated with hospital mortality in septic patients. Strategies to reduce glucose variability should be studied to determine whether they improve the outcomes of septic patients.

Results of randomised controlled trials of tight glycaemic control in hospital inpatients might vary with population and disease state. Individualised therapy for different hospital inpatient populations and identification of patients at risk of hyperglycaemia might be needed. One risk factor that has received much attention is the presence of pre-existing diabetes. So-called stress hyperglycaemia is usually defined as hyperglycaemia resolving spontaneously after dissipation of acute illness. The term generally refers to patients without known diabetes, although patients with diabetes might also develop stress hyperglycaemia—a fact overlooked in many studies comparing hospital inpatients with or without diabetes. Investigators of several studies have suggested that patients with stress hyperglycaemia are at higher risk of adverse consequences than are those with pre-existing diabetes. We describe classification of stress hyperglycaemia, mechanisms of harm, and management strategies.