Clinical review: Consensus recommendations on measurement of blood glucose and reporting glycemic control in critically ill adults

Time in blood glucose range 70 to 140 mg/dl >80% is strongly associated with increased survival in non-diabetic critically ill adults

Introduction

Hyperglycemia, hypoglycemia and increased glucose variability are independently associated with increased risk of death in critically ill adults. The relationship between time in targeted blood glucose range (TIR) and mortality is not well described and may be a factor that has confounded the results of the major interventional trials of intensive insulin therapy.

Methods

We conducted a retrospective analysis of prospectively collected data involving 3,297 patients with intensive care unit (ICU) lengths of stay (LOS) of ≥1.0 day who were admitted between 1 January 2009 and 31 December 2013 to a single mixed medical-surgical ICU. We investigated the relationship between TIR 70 to 140 mg/dl with mortality and compared outcomes of non-diabetics (NON) and individuals with diabetes mellitus (DM), including stratifying by TIR above (TIR-hi) and below (TIR-lo) the median value for the NON and DM groups.

Results

There were 85,799 blood glucose (BG) values for the NON group and 32,651 for the DM group, and we found that 75.5% and 54.8%, respectively, were between 70 and 140 (P <0.0001). The median (interquartile range) TIR (%) values for the NON and DM groups were 80.6% (61.4% to 94.0%) and 55.0% (35.5% to 71.1%), respectively (P <0.0001). For the NON group, mortality was 8.47% and 15.71% for TIR-hi and TIR-lo, respectively (P <0.0001). For the DM group, mortality was 16.09% and 14.44% for TIR-hi and TIR-lo, respectively (P = NS). We observed similar relationships for the NON group when we stratified by ICU LOS or severity of illness, especially in the most severely ill patients. There was a cumulative interaction of indices of hypoglycemia, hyperglycemia or glucose variability with TIR. Multivariable analysis demonstrated, for the NON group, that TIR-hi was independently associated with increased survival (P =0.0019). For the NON group, the observed-to-expected mortality ratios for TIR-hi and TIR-lo, based on Acute Physiology and Chronic Health Evaluation IV methodology, were 0.53 and 0.78, respectively. In contrast, among those in the DM group, there was no clear relationship between TIR 70 to 140 mg/dl and survival.

Conclusions

Independently of ICU LOS and severity of illness, TIR 70 to 140 mg/dl >80% is strongly associated with survival in critically ill patients without diabetes. These findings have implications for the design of clinical protocols for glycemic control in critically ill patients as well for the design of future interventional trials of intensive insulin therapy.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-015-0908-7) contains supplementary material, which is available to authorized users.

The impact of measurement frequency on the domains of glycemic control in the critically ill--a Monte Carlo simulation

The role of blood glucose (BG) measurement frequency on the domains of glycemic control is not well defined. This Monte Carlo mathematical simulation of glycemic control in a cohort of critically ill patients modeled sets of 100 patients with simulated BG-measuring devices having 5 levels of measurement imprecision, using 2 published insulin infusion protocols, for 200 hours, with 3 different BG-measurement intervals-15 minutes (Q15'), 1 hour (Q1h), and 2 hours (Q2h)-resulting in 1,100,000 BG measurements for 3000 simulated patients. The model varied insulin sensitivity, initial BG value and rate of gluconeogenesis. The primary outcomes included rates of hyperglycemia (BG > 180 mg/dL), hypoglycemia (BG < 70 and 40 mg/dL), proportion of patients with elevated glucose variability (within-patient coefficient of variation [CV] > 20%), and time in range (BG ranges 80-150 mg/dL and 80-180 mg/dL). Percentages of hyperglycemia, hypoglycemia at both thresholds, and patients with elevated glucose variability as well as time outside glycemic targets were substantially higher in simulations with measurement interval Q2h compared to those with measurement interval Q1h and moderately higher in simulations with Q1h than in those with Q15'. Higher measurement frequency mitigated the deleterious effect of high measurement imprecision, defined as CV ≥ 15%. This Monte Carlo simulation suggests that glycemic control in critically ill patients is more optimal with a BG measurement interval no longer than 1h, with further benefit obtained with use of measurement interval of 15'. These findings have important implications for the development of glycemic control standards.

Insulin infusion therapy in critically ill patients

While dysglycemia (hyperglycemia, hypoglycemia and glucose variability) is clearly associated with increased mortality in critically ill patients, target range of blood glucose control remains controversial. Standardized insulin infusion protocols constitute the basis of treatment of these patients. The choice of protocol and its implementation is a great challenge. In this article, we review the published data to help define the essential elements that compose a good protocol and apply the right conditions to make it safe and effective.

Point accuracy and reliability of an interstitial continuous glucose-monitoring device in critically ill patients: a prospective study

Introduction

There is a need for continuous glucose monitoring in critically ill patients. The objective of this trial was to determine the point accuracy and reliability of a device designed for continuous monitoring of interstitial glucose levels in intensive care unit patients.

Methods

We evaluated point accuracy by comparing device readings with glucose measurements in arterial blood by using blood gas analyzers. Analytical and clinical accuracy was expressed in Bland-Altman plots, glucose prediction errors, and Clarke error grids. We used a linear mixed model to determine which factors affect the point accuracy. In addition, we determined the reliability, including duration of device start-up and calibration, skips in data acquisition, and premature disconnections of sensors.

Results

We included 50 patients in whom we used 105 sensors. Five patients from whom we could not collect the predefined minimum number of four consecutive comparative blood draws were excluded from the point accuracy analysis. Therefore, we had 929 comparative samples from 100 sensors in 45 patients (11 (7 to 28) samples per patient) during 4,639 hours (46 (27 to 134) hours per patient and 46 (21 to 69) hours per sensor) for the accuracy analysis. Point accuracy did not meet the International Organization for Standardization (ISO) 14971 standard for insulin dosing accuracy but did improve with increasing numbers of calibrations and was better in patients who did not have a history of diabetes. Out of 105 sensors, 60 were removed prematurely for a variety of reasons. The device start-up time was 49 (43 to 58) minutes. The number of skips in data acquisition was low, resulting in availability of real-time data during 95% (89% to 98%) of the connection time per sensor.

Conclusions

The point accuracy of a device designed for continuous real-time monitoring of interstitial glucose levels was relatively low in critically ill patients. The device had few downtimes, but one third of the sensors were removed prematurely because of unresolved sensor- or device-related problems.

Trial registration

Netherlands Trial Registry number: NTR3827. Registered 30 January 2013.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-015-0757-4) contains supplementary material, which is available to authorized users.

Real-time continuous glucose monitoring versus conventional glucose monitoring in critically ill patients: a systematic review study protocol

INTRODUCTION

Stress-induced hyperglycaemia, which has been shown to be associated with an unfavourable prognosis, is common among critically ill patients. Additionally, it has been reported that hypoglycaemia and high glucose variabilities are also associated with adverse outcomes. Thus, continuous glucose monitoring (CGM) may be the optimal method to detect severe hypoglycaemia, hyperglycaemia and decrease glucose excursion. However, the overall accuracy and reliability of CGM systems and the effects of CGM systems on glucose control and prognosis in critically ill patients remain inconclusive. Therefore, we will conduct a systematic review and meta-analysis to clarify the associations between CGM systems and clinical outcome.

METHODS AND ANALYSIS

We will search PubMed, EMBASE and the Cochrane Library from inception to October 2014. Studies comparing CGM systems with any other glucose monitoring methods in critically ill patients will be eligible for our meta-analysis. The primary endpoints include the incidence of hypoglycaemia and hyperglycaemia, mean glucose level, and percentage of time within the target range. The second endpoints include intensive care unit (ICU) mortality, hospital mortality, duration of mechanical ventilation, length of ICU and hospital stay, and the Pearson correlation coefficient and the results of error grid analysis. In addition, we will record all complications (eg, acquired infections) in control and intervention groups and local adverse events in intervention groups (eg, bleeding or infections).

ETHICS AND DISSEMINATION

Ethics approval is not required as this is a protocol for a systematic review. The findings will be disseminated in a peer-reviewed journal and presented at a relevant conference.

TRIAL REGISTRATION NUMBER

PROSPERO registration number: CRD42014013488.

The relationship between serum potassium, potassium variability and in-hospital mortality in critically ill patients and a before-after analysis on the impact of computer-assisted potassium control

Introduction

The relationship between potassium regulation and outcome is not known. Our first aim in the present study was to determine the relationship between potassium level and variability in (ICU) stay and outcome. The second aim was to evaluate the impact of a computer-assisted potassium regulation protocol.

Methods

We performed a retrospective before-after study including all patients >15 years of age admitted for more than 24 hours to the ICU of our university teaching hospital between 2002 and 2011. Potassium control was fully integrated with computerized glucose control (glucose and potassium regulation program for intensive care patients (GRIP-II)). The potassium metrics that we determined included mean potassium, potassium variability (defined as the standard deviation of all potassium levels) and percentage of ICU time below and above the reference range (3.5 through 5.0 mmol/L). These metrics were determined for the first ICU day (early phase) and the subsequent ICU days (late phase; that is, day 2 to day 7). We also compared potassium metrics and in-hospital mortality before and after GRIP-II was implemented in 2006.

Results

Of all 22,347 ICU admissions, 10,451 (47%) patients were included. A total of 206,987 potassium measurements were performed in these patients. Glucose was regulated by GRIP-II in 4,664 (45%) patients. The overall in-hospital mortality was 22%. There was a U-shaped relationship between the potassium level and in-hospital mortality (P <0.001). Moreover, potassium variability was independently associated with outcome. After implementation of GRIP-II, in the late phase the time below 3.5 mmol/L decreased from 9.2% to 3.9% and the time above 5.0 mmol/L decreased from 6.1% to 5.2%, and potassium variability decreased from 0.31 to 0.26 mmol/L (all P <0.001). The overall decrease in in-hospital mortality from 23.3% before introduction of GRIP-II to 19.9% afterward (P <0.001) was not related to a specific potassium subgroup.

Conclusions

Hypokalemia, hyperkalemia and potassium variability were independently associated with increased mortality. Computerized potassium control clearly resulted in improved potassium metrics.

Accuracy of a feasibility version of an intravenous continuous glucose monitor in volunteers with diabetes and hospitalized patients

BACKGROUND

A feasibility version of the GlucoClear™ continuous glucose monitoring system (Edwards Lifesciences, Irvine, CA), the intravenous blood glucose (IVBG) system, developed to facilitate glycemic management, was evaluated.

MATERIALS AND METHODS

Two pilot studies were conducted. Ten volunteers with diabetes (1,725 matched pairs) and 10 patients scheduled for intensive care unit (ICU) admission following surgery (1,393 matched pairs) were studied. The patients' blood glucose concentrations were monitored by the IVBG system every 5 min for up to 72 h. The accuracy of the IVBG system was calculated and compared with the Yellow Springs Instrument (YSI) (Yellows Springs, OH) and Radiometer (Copenhagen, Denmark) measurements to determine the percentage of matched pairs that met 15/20%, 10/15%, 12/12.5%, and 10/10% assessment criteria. Performance was calculated as the percentage of the total measurements that would have been displayed in an unblinded study. Adverse events were monitored.

RESULTS

The accuracy of the IVBG system met the International Organization for Standardization ISO 15197 15/20% criterion (99.07% in volunteers, 99.43% in the ICU, and both vs. YSI) and the stricter 10/15% criterion (96.17% in volunteers, 96.77% in the ICU, and both vs. YSI) over the 72-h period and across a broad range of blood glucose concentrations. Performance was 89.97% in the ICU study. The adverse device effects included induration of the peripheral vein, mild bruising, and mild hematoma. In the volunteers, there were patency problems with six catheters.

CONCLUSIONS

The IVBG system is safe, accurate, and reliable. This minimally invasive system was not affected by potentially interfering medications. Real-time measurements, alarms, and trends provided by the IVBG system might support glycemic control protocols and prevent glycemic events in critically ill patients.

Year in review 2013: Critical Care--metabolism

Novel insights into the metabolic alterations of critical illness, including new findings on association between blood glucose at admission and poor outcome, were published in Critical Care in 2013. The role of diabetic status in the relation of the three domains of glycemic control (hyperglycemia, hypoglycemia, and glycemic variability) was clarified: the association between mean glucose, high glucose variability, and ICU mortality was stronger in the non-diabetic than in diabetic patients. Improvements in the understanding of pathophysiological mechanisms of stress hyperglycemia were presented. Novel developments for the management of glucose control included automated closed-loop algorithms based on subcutaneous glucose measurements and microdialysis techniques. In the field of obesity, some new hypotheses that could explain the ‘obesity paradox’ were released, and a role of adipose tissue in the response to stress was suggested by the time course of adipocyte fatty-acid binding protein concentrations. In the field of nutrition, beneficial immunological effects have been associated with early enteral nutrition. Early enteral nutrition was significantly associated with potential beneficial effects on the phenotype of lymphocytes. Uncertainties regarding the potential benefits of small intestine feeding compared with gastric feeding were further investigated. No significant differences were observed between the nasogastric and nasojejunal feeding groups in the incidence of mortality, tracheal aspiration, or exacerbation of pain. The major risk factors to develop diarrhea in the ICU were described. Finally, the understanding of disorders associated with trauma and potential benefits of blood acidification was improved by new experimental findings.

Glucose control in the intensive care unit by use of continuous glucose monitoring: what level of measurement error is acceptable?

BACKGROUND

Accuracy and frequency of glucose measurement is essential to achieve safe and efficacious glucose control in the intensive care unit. Emerging continuous glucose monitors provide frequent measurements, trending information, and alarms. The objective of this study was to establish the level of accuracy of continuous glucose monitoring (CGM) associated with safe and efficacious glucose control in the intensive care unit.

METHODS

We evaluated 3 established glucose control protocols [Yale, University of Washington, and Normoglycemia in Intensive Care Evaluation and Surviving Using Glucose Algorithm Regulation (NICE-SUGAR)] by use of computer simulations. Insulin delivery was informed by intermittent blood glucose (BG) measurements or CGM levels with an increasing level of measurement error. Measures of glucose control included mean glucose, glucose variability, proportion of time glucose was in target range, and hypoglycemia episodes.

RESULTS

Apart from the Washington protocol, CGM with mean absolute relative deviation (MARD) ≤ 15% resulted in similar mean glucose as with the use of intermittent BG measurements. Glucose variability was also similar between CGM and BG-informed protocols. Frequency and duration of hypoglycemia were not worse by use of CGM with MARD ≤ 10%. Measures of glucose control varied more between protocols than at different levels of the CGM error.

CONCLUSIONS

The efficacy of CGM-informed and BG-informed commonly used glucose protocols is similar, but the risk of hypoglycemia may be reduced by use of CGM with MARD ≤ 10%. Protocol choice has greater influence on glucose control measures than the glucose measurement method.

Conservative fluid therapy in septic shock: an example of targeted therapeutic minimization

Intravenous fluids (IVFs) represent a basic therapeutic intervention utilized in septic shock. Unfortunately, the optimal method for administering IVFs to maximize patient outcomes is unknown. A meta-analysis of four randomized trials of goal-directed therapy did not demonstrate a significant reduction in mortality (odds ratio 0.609; 95% confidence interval 0.363 to 1.020; P = 0.059), whereas 18 trials with historical controls showed a significant increase in survival (odds ratio 0.580; 95% confidence interval 0.501 to 0.672; P < 0.0001). Based on these data, clinicians should be aware of the potential for harm due to the excessive administration of IVFs to patients with septic shock.

Modeling of effect of glucose sensor errors on insulin dosage and glucose bolus computed by LOGIC-Insulin

BACKGROUND

Effective and safe glycemic control in critically ill patients requires accurate glucose sensors and adequate insulin dosage calculators. The LOGIC-Insulin calculator for glycemic control has recently been validated in the LOGIC-1 randomized controlled trial. In this study, we aimed to determine the allowable error for intermittent and continuous glucose sensors, on the basis of the LOGIC-Insulin calculator.

METHODS

A gaussian simulation model with a varying bias (0%-20%) and CV (-20% to +20%) simulated blood glucose values from the LOGIC-1 study (n = 149 patients) in 10 Monte Carlo steps. A clinical error grid system was developed to compare the simulated LOGIC-Insulin-directed intervention with the nominal intervention (0% bias, 0% CV). The severity of error measuring the clinical effect of the simulated LOGIC-Insulin intervention was graded as type B, C, and D errors. Type D errors were classified as acutely life-threatening (0% probability preferred).

RESULTS

The probability of all types of errors was lower for continuous sensors compared with intermittent sensors. The maximum total error (TE), defined as the first TE introducing a type B/C/D error, was similar for both sensor types. To avoid type D errors, TEs <15.7% for intermittent sensors and <17.8% for continuous sensors were required. Mean absolute relative difference thresholds for type C errors were 7.1% for intermittent and 11.0% for continuous sensors.

CONCLUSIONS

Continuous sensors had a lower probability for clinical errors than intermittent sensors at the same accuracy level. These simulations demonstrated the suitability of the LOGIC-Insulin control system for use with continuous, as well as intermittent, sensors.

Glucose control in intensive care: usability, efficacy and safety of Space GlucoseControl in two medical European intensive care units

BACKGROUND

The Space GlucoseControl system (SGC) is a nurse-driven, computer-assisted device for glycemic control combining infusion pumps with the enhanced Model Predictive Control algorithm (B. Braun, Melsungen, Germany). We aimed to investigate the performance of the SGC in medical critically ill patients.

METHODS

Two open clinical investigations in tertiary centers in Graz, Austria and Zurich, Switzerland were performed. Efficacy was assessed by percentage of time within the target range (4.4-8.3 mmol/L; primary end point), mean blood glucose, and sampling interval. Safety was assessed by the number of hypoglycemic episodes (≤2.2 mmol/L) and the percentage of time spent below this cutoff level. Usability was analyzed with a standardized questionnaire given to involved nursing staff after the trial.

RESULTS

Forty medical critically ill patients (age, 62 ± 15 years; body mass index, 30.0 ± 8.9 kg/m2; APACHE II score, 24.8 ± 5.4; 27 males; 8 with diabetes) were included for a period of 6.5 ± 3.7 days (n = 20 in each center). The primary endpoint (time in target range 4.4 to 8.3 mmol/l) was reached in 88.3% ± 9.3 of the time and mean arterial blood glucose was 6.7 ± 0.4 mmol/l. The sampling interval was 2.2 ± 0.4 hours. The mean daily insulin dose was 87.2 ± 64.6 IU. The adherence to the given insulin dose advice was high (98.2%). While the percentage of time spent in a moderately hypoglycemic range (2.2 to 3.3 mmol/L) was low (0.07 ± 0.26% of the time), one severe hypoglycemic episode (<2.2 mmol/L) occurred (2.5% of patients or 0.03% of glucose readings).

CONCLUSIONS

SGC is a safe and efficient method to control blood glucose in critically ill patients as assessed in two European medical intensive care units.

Glucose control in the ICU: is there a time for more ambitious targets again?

During the last 2 decades, the treatment of hyperglycemia in critically ill patients has become one of the most discussed topics in the intensive medicine field. The initial data suggesting significant benefit of normalization of blood glucose levels in critically ill patients using intensive intravenous insulin therapy have been challenged or even neglected by some later studies. At the moment, the need for glucose control in critically ill patients is generally accepted yet the target glucose values are still the subject of ongoing debates. In this review, we summarize the current data on the benefits and risks of tight glucose control in critically ill patients focusing on the novel technological approaches including continuous glucose monitoring and its combination with computer-based algorithms that might help to overcome some of the hurdles of tight glucose control. Since increased risk of hypoglycemia appears to be the major obstacle of tight glucose control, we try to put forward novel approaches that may help to achieve optimal glucose control with low risk of hypoglycemia. If such approaches can be implemented in real-world practice the entire concept of tight glucose control may need to be revisited.

Glucose prediction by analysis of exhaled metabolites - a systematic review

Background

In critically ill patients, glucose control with insulin mandates time– and blood–consuming glucose monitoring. Blood glucose level fluctuations are accompanied by metabolomic changes that alter the composition of volatile organic compounds (VOC), which are detectable in exhaled breath. This review systematically summarizes the available data on the ability of changes in VOC composition to predict blood glucose levels and changes in blood glucose levels.

Methods

A systematic search was performed in PubMed. Studies were included when an association between blood glucose levels and VOCs in exhaled air was investigated, using a technique that allows for separation, quantification and identification of individual VOCs. Only studies on humans were included.

Results

Nine studies were included out of 1041 identified in the search. Authors of seven studies observed a significant correlation between blood glucose levels and selected VOCs in exhaled air. Authors of two studies did not observe a strong correlation. Blood glucose levels were associated with the following VOCs: ketone bodies (e.g., acetone), VOCs produced by gut flora (e.g., ethanol, methanol, and propane), exogenous compounds (e.g., ethyl benzene, o–xylene, and m/p–xylene) and markers of oxidative stress (e.g., methyl nitrate, 2–pentyl nitrate, and CO).

Conclusion

There is a relation between blood glucose levels and VOC composition in exhaled air. These results warrant clinical validation of exhaled breath analysis to monitor blood glucose levels.

Continuous glucose control in the ICU: report of a 2013 round table meeting

Achieving adequate glucose control in critically ill patients is a complex but important part of optimal patient management. Until relatively recently, intermittent measurements of blood glucose have been the only means of monitoring blood glucose levels. With growing interest in the possible beneficial effects of continuous over intermittent monitoring and the development of several continuous glucose monitoring (CGM) systems, a round table conference was convened to discuss and, where possible, reach consensus on the various aspects related to glucose monitoring and management using these systems. In this report, we discuss the advantages and limitations of the different types of devices available, the potential advantages of continuous over intermittent testing, the relative importance of trend and point accuracy, the standards necessary for reporting results in clinical trials and for recognition by official bodies, and the changes that may be needed in current glucose management protocols as a result of a move towards increased use of CGM. We close with a list of the research priorities in this field, which will be necessary if CGM is to become a routine part of daily practice in the management of critically ill patients.

Hyperglycemia-induced diaphragm weakness is mediated by oxidative stress

Introduction

A major consequence of ICU-acquired weakness (ICUAW) is diaphragm weakness, which prolongs the duration of mechanical ventilation. Hyperglycemia (HG) is a risk factor for ICUAW. However, the mechanisms underlying HG-induced respiratory muscle weakness are not known. Excessive reactive oxygen species (ROS) injure multiple tissues during HG, but only one study suggests that excessive ROS generation may be linked to HG-induced diaphragm weakness. We hypothesized that HG-induced diaphragm dysfunction is mediated by excessive superoxide generation and that administration of a specific superoxide scavenger, polyethylene glycol superoxide dismutase (PEG-SOD), would ameliorate these effects.

Methods

HG was induced in rats using streptozotocin (60 mg/kg intravenously) and the following groups assessed at two weeks: controls, HG, HG + PEG-SOD (2,000U/kg/d intraperitoneally for seven days), and HG + denatured (dn)PEG-SOD (2000U/kg/d intraperitoneally for seven days). PEG-SOD and dnPEG-SOD were administered on day 8, we measured diaphragm specific force generation in muscle strips, force-pCa relationships in single permeabilized fibers, contractile protein content and indices of oxidative stress.

Results

HG reduced diaphragm specific force generation, altered single fiber force-pCa relationships, depleted troponin T, and increased oxidative stress. PEG-SOD prevented HG-induced reductions in diaphragm specific force generation (for example 80 Hz force was 26.4 ± 0.9, 15.4 ± 0.9, 24.0 ± 1.5 and 14.9 ± 0.9 N/cm² for control, HG, HG + PEG-SOD, and HG + dnPEG-SOD groups, respectively, P <0.001). PEG-SOD also restored HG-induced reductions in diaphragm single fiber force generation (for example, Fmax was 182.9 ± 1.8, 85.7 ± 2.0, 148.6 ± 2.4 and 90.9 ± 1.5 kPa in control, HG, HG + PEG-SOD, and HG + dnPEG-SOD groups, respectively, P <0.001). HG-induced troponin T depletion, protein nitrotyrosine formation, and carbonyl modifications were largely prevented by PEG-SOD.

Conclusions

HG-induced reductions in diaphragm force generation occur largely at the level of the contractile proteins, are associated with depletion of troponin T and increased indices of oxidative stress, findings not previously reported. Importantly, administration of PEG-SOD largely ablated these derangements, indicating that superoxide generation plays a major role in hyperglycemia-induced diaphragm dysfunction. This new mechanistic information could explain how HG alters diaphragm function during critical illness.

Continuous glucose monitoring in the surgical intensive care unit: concordance with capillary glucose

BACKGROUND

The role of intensive glycemic control (IGC) in the surgical intensive care unit (SICU) remains controversial. Continuous glucose monitoring systems (CGMSs) may mitigate the major risk of IGC, namely hypoglycemia, and improve clinical outcomes.

METHODS

All patients admitted to the SICU requiring insulin infusion were eligible. CGMS (Medtronic Guardian REAL-Time CGM, Northridge, CA) was placed in the subcutaneous tissue of the abdomen or thigh and calibrated every 8 hours, based on capillary (fingerstick) blood glucose (CBG) readings. Monitors were changed every 72 hours until 144 hours of observation was complete or insulin infusion stopped. CGM data were compared with CBG at least every 2 hours. Other data collected included demographics, diagnoses, fluid balance, doses of vasopressors and/or steroids, and any intravenous or enteral glucose source. CGMS and CBG readings were compared (mean and median absolute difference, correlation coefficients, Bland-Altman plots, and Clarke error grids).

RESULTS

Twenty-four patients were enrolled (11 men; mean [SD] age, 59 [14.1] years; mean [SD] body mass index 37.9 [10.1] kg/m; mean [SD] fluid resuscitation in the first 24 hours, 6.1 [3.5] L; 17 requiring vasopressor therapy). Correlation coefficient between CGMS and CBG was 0.61 (p < 0.001). The mean (SD) absolute difference was 22.0 [21.9] mg/dL and the median absolute difference was 16.0 mg/dL (interquartile rage, 7-31 mg/dL). The Bland-Altman plot did not identify any trends in accuracy. Clarke error grid analysis demonstrated that 98.92% of data points were in Zone A (71.30%), indicating agreement with CBG ± 20%, or Zone B (27.62%) (divergent but discrepancy would likely not lead to patient harm). Just 0.81% of data points were in Zone C (potentially dangerous overcorrection likely), and only 0.27% were in Zones D or E (potentially dangerous failure to detect hypoglycemia/hyperglycemia).

CONCLUSION

CGMS seems reasonably accurate in the SICU, despite widespread use of pressors and large-volume resuscitation. Further investigation into the accuracy and precision of these devices to assist clinicians in achieving IGC is warranted.

LEVEL OF EVIDENCE

Diagnostic study, level III.

Accuracy and limitations of continuous glucose monitoring using spectroscopy in critically ill patients

BACKGROUND

OptiScanner devices, continuous glucose monitoring devices that perform automated blood draws via a central venous catheter and create plasma through centrifugation, measure plasma glucose levels through mid-infrared spectroscopy at the bedside. The objective of this study was to determine accuracy and practicality of the devices in critically ill patients attempting glycemic control.

METHODS

The plasma glucose level was measured by the devices and in comparative plasma samples using Yellow Springs Instrument (YSI) plasma analyzers. After adding several previously unrecognized interferences in the interference library, we reanalyzed the mid-infrared signals and compared the resulting plasma glucose level with the reference value. Results are presented in Clarke error grids, glucose prediction errors and Bland-Altman plots and expressed as correlation coefficients.

RESULTS

We analyzed 463 comparative samples from 71 patients (median 6 (4 to 9) samples per patient). After calibrating the system, a Clarke error grid showed 100% of the values in zones A or B. The glucose predictor error demonstrated that 86% of the glucose values < 75 mg/dL were within ± 15 mg/dL of the YSI results and 95% ≥ 75 mg/dL were within 20% of the comparative YSI results. Bland-Altman plot showed a bias of -0.6 with limit of agreement of -24.6 to 23.3. The Pearson correlation coefficient was 0.93 and R2 was 0.87. In one third of the patients the devices had to be disconnected prematurely (that is before planned disconnection) because of repeated occlusion alarms suggesting blood draw errors.

CONCLUSION

The devices needed calibration for several previously unrecognized interferences. Thereafter, accuracy of the device to measure plasma glucose levels in 'our cohort' of critically ill patients improved, but external validation is highly recommended. The automated blood draw system of the devices needs further improvement to make this device of value for clinical use (trial registration (Netherlands Trial Register): NTR2864).

Tight computerized versus conventional glucose control in the ICU: a randomized controlled trial

PURPOSE

The blood glucose target range and optimal method to reach this range remain a matter of debate in the intensive care unit (ICU). A computer decision support system (CDSS) might improve the outcome of ICU patients through facilitation of a tighter blood glucose control.

METHODS

We conducted a multi-center randomized trial in 34 French ICU. Adult patients expected to require treatment in the ICU for at least 3 days were randomly assigned without blinding to undergo tight computerized glucose control with the CDSS (TGC) or conventional glucose control (CGC), with blood glucose targets of 4.4-6.1 and <10.0 mmol/L, respectively. The primary outcome was all-cause death within 90 days after ICU admission.

RESULTS

Of the 2,684 patients who underwent randomization to the TGC and CGC treatment groups, primary outcome was available for 1,335 and 1,311 patients, respectively. The baseline characteristics of these treatment groups were similar in terms of age (61 ± 16 years), SAPS II (51 ± 19), percentage of surgical admissions (40.0%) and proportion of diabetic patients (20.3%). A total of 431 (32.3%) patients in the TGC group and 447 (34.1%) in the CGC group had died by day 90 (odds ratio for death in the TGC 0.92; 95% confidence interval 0.78-1.78; p = 0.32). Severe hypoglycemia (<2.2 mmol/L) occurred in 174 of 1,317 patients (13.2%) in the TGC group and 79 of 1,284 patients (6.2%) in the CGC group (p < 0.001).

CONCLUSIONS

Tight computerized glucose control with the CDSS did not significantly change 90-day mortality and was associated with more frequent severe hypoglycemia episodes in comparison with conventional glucose control.

Effects of measurement frequency on analytical quality required for glucose measurements in intensive care units: assessments by simulation models

BACKGROUND

Total error allowances have been proposed for glucose meters used in tight-glucose-control (TGC) protocols. It is unclear whether these proposed quality specifications are appropriate for continuous glucose monitoring (CGM).

METHODS

We performed Monte Carlo simulations of patients on TGC protocols. To simulate use of glucose meters, measurements were made hourly. To simulate CGM, glucose measurements were made every 5 min. Glucose was measured with defined bias (varied from -20% to 20%) and imprecision (0% to 20% CV). The measured glucose concentrations were used to alter insulin infusion rates according to established treatment protocols. Changes in true glucose were calculated hourly on the basis of the insulin infusion rate, the modeled patient's insulin sensitivity, and a model of glucose homeostasis. We modeled 18 000 patients, equally divided between the hourly and every-5-min measurement schemas and distributed among 45 combinations of bias and imprecision and 2 treatment protocols.

RESULTS

With both treatment protocols and both measurement frequencies, higher measurement imprecision increased the rates of hypoglycemia and hyperglycemia and increased glycemic variability (SD). These adverse effects of measurement imprecision were lower at the higher measurement frequency. The rate of hypoglycemia at an imprecision (CV) of 5% with hourly measurements was similar to the rate of hypoglycemia at 10% CV when measurements were made every 5 min. With measurements every 5 min, imprecision up to 10% had minimal effects on hyperglycemia or glycemic variability. Effects of simulated analytical bias on glycemia were unaffected by measurement frequency.

CONCLUSIONS

Quality specifications for imprecision of glucose meters are not transferable to CGM.

Performance of the Medtronic Sentrino continuous glucose management (CGM) system in the cardiac intensive care unit

BACKGROUND

Maintaining glucose in the target range, while avoiding hypoglycemia, is challenging in critically ill patients. We investigated the performance and safety of Medtronic Sentrino, a newly developed continuous glucose management (CGM) system for critically ill adults.

METHODS

This was a prospective, single-center, single-arm, open-label study in adult patients with cardiac ICU admission. Sentrino subcutaneous glucose sensors were inserted into patients' thigh with planned study participation of 72 h. Sensor glucose results were displayed, and the system's alerts and alarms fully enabled. Reference blood glucose was collected from central venous catheter and analyzed with a blood gas analyzer. Treatment decisions were made independently of sensor glucose values, according to the existing standard of care.

RESULTS

A total of 21 patients were enrolled; all successfully completed the study. Sensor glucose values were displayed 96% of the time, and 870 paired blood glucose-sensor glucose points were analyzed. Overall mean absolute relative difference (MARD) was 12.8% (95% CI 11.9% to 13.6%). No clinically significant differences in accuracy were seen within subgroups of hemodynamic status (MARD 12.3% and 13.1% for compromised vs stable hemodynamics). Consensus grid analysis showed >99% of sensor glucose values within A/B zones. No device or study-related adverse events were reported. 100% of clinicians found Sentrino easy to use after two patients.

CONCLUSIONS

In our single-center experience, Sentrino CGM system demonstrated good accuracy and reliability, with no device-related adverse events in critically ill cardiac patients, and was easy to use and integrate in the cardiac ICU.

TRIAL REGISTRATION NUMBER

NCT01763567.

Hypoglycemia is associated with increased mortality in patients with acute decompensated liver cirrhosis

PRINCIPALS

The liver plays an important role in glucose metabolism, in terms of glucolysis and gluconeogenesis. Several studies have shown that hyperglycemia in patients with liver cirrhosis is associated with progression of the liver disease and increased mortality. However, no study has ever targeted the influence of hypoglycemia. The aim of this study was to assess the association of glucose disturbances with outcome in patients presenting to the emergency department with acute decompensated liver cirrhosis.

METHODS

Our retrospective data analysis comprised adult (≥ 16 years) patients admitted to our emergency department between January 1, 2002, and December 31, 2012, with the primary diagnosis of decompensated liver cirrhosis.

RESULTS

A total of 312 patients were eligible for study inclusion. Two hundred thirty-one (74.0%) patients were male; 81 (26.0%) were female. The median age was 57 years (range, 51-65 years). Overall, 89 (28.5%) of our patients had acute glucose disturbances; 49 (15.7%) of our patients were hypoglycemic and 40 (12.8%) were hyperglycemic. Patients with hypoglycemia were significantly more often admitted to the intensive care unit than hyperglycemic patients (20.4% vs 10.8%, P < .015) or than normoglycemic patients (20.4% vs 10.3%, P < .011), and they significantly more often died in the hospital (28.6% hypoglycemic vs 7.5% hyperglycemic, P < .024; 28.6% hypoglycemic vs 10.3% normoglycemic P < .049). Survival analysis showed a significantly lower estimated survival for hypoglycemic patients (36 days) than for normoglycemic patients (54 days) or hyperglycemic patients (45 days; hypoglycemic vs hyperglycemic, P < .019; hypoglycemic vs normoglycemic, P < .007; hyperglycemic vs normoglycemic, P < .477).

CONCLUSION

Hypoglycemia is associated with increased mortality in patients with acute decompensated liver cirrhosis. It is not yet clear whether hypoglycemia is jointly responsible for the increased short-term mortality of patients with acute decompensated liver cirrhosis or is only a consequence of the severity of the disease or the complications.

Performance assessment of a glucose control protocol in septic patients with an automated intermittent plasma glucose monitoring device

BACKGROUND & AIMS

The optimal level and modality of glucose control in critically ill patients is still debated. A protocolized approach and the use of nearly-continuous technologies are recommended to manage hyperglycemia, hypoglycemia and glycemic variability. We recently proposed a pato-physiology-based glucose control protocol which takes into account patient glucose/carbohydrate intake and insulin resistance. Aim of the present investigation was to assess the performance of our protocol with an automated intermittent plasma glucose monitoring device (OptiScanner™ 5000).

METHODS

OptiScanner™ was used in 6 septic patients, providing glucose measurement every 15' from a side-port of an indwelling central venous catheter. Target level of glucose was 80-150 mg/dL. Insulin infusion and kcal with nutritional support were also recorded.

RESULTS

6 septic patients were studied for 319 h (1277 measurements); 58 [45-65] hours for each patient (measurements/patient: 231 [172-265]). Blood glucose was at target for 93 [90-98]% of study time. Mean plasma glucose was 126 ± 11 mg/dL. Only 3 hypoglycemic episodes (78, 78, 69 mg/dL) were recorded. Glucose variability was limited: plasma glucose coefficient of variation was 11.7 ± 4.0% and plasma glucose standard deviation was 14.3 ± 5.5 mg/dL.

CONCLUSIONS

The local glucose control protocol achieved satisfactory glucose control in septic patients along with a high degree of safeness. Automated intermittent plasma glucose monitoring seemed useful to assess the performance of the protocol.

Continuous glucose sensors for glycaemic control in the ICU: have we arrived?

Dr Blixt and colleagues show in an elegant pilot study that the continuous measurement of glucose in venous blood by microdialysis in a central venous catheter is feasible in critically ill patients. The performance of this type of continuous glucose monitoring device equals the performance of the commonly used handheld blood glucose meters. But are we, as ICU physicians and nurses, now ready to implement such continuous blood glucose sensors into the daily practice of the ICU? The only yardstick to this is "are these devices truly helping us ...in our critically ill patients".

Measuring and reporting glycemic control in clinical trials: building a path to consensus

Clinical trials over time have used a variety of approaches for both measuring tight glycemic control and reporting results. The review by Finfer and colleagues in this issue of Critical Care is a step toward consensus within the research community to standardize the way blood glucose is measured and reported in clinical trials. The authors propose using specific measures of central tendency and dispersion for reporting glucose, advocate the use of blood gas analyzers and elimination of point-of-care glucose monitors in the intensive care unit, and comment on performance of continuous glucose monitors. As we await the release of updated rules from the International Standards Organization and process the new rules from the Clinical Laboratory and Standards Institute to regulate glucose monitoring, these recommendations should trigger many more conversations within the field as we strive for uniformity. However, we need to be cautious in prematurely proposing and adopting standards of care that fail to account for newer technology and data in this rapidly growing area of research.

Continuous on-line glucose measurement by microdialysis in a central vein. A pilot study

Introduction

Tight glucose control in the ICU has been proven difficult with an increased risk for hypoglycaemic episodes. Also the variability of glucose may have an impact on morbidity. An accurate and feasible on-line/continuous measurement is therefore desired. In this study a central vein catheter with a microdialysis membrane in combination with an on-line analyzer for continuous monitoring of circulating glucose and lactate by the central route was tested.

Methods

A total of 10 patients scheduled for major upper abdominal surgery were included in this observational prospective study at a university hospital. The patients received an extra central venous catheter with a microdialysis membrane placed in the right jugular vein. Continuous microdialysis measurement proceeded for 20 hours and on-line values were recorded every minute. Reference arterial plasma glucose and blood lactate samples were collected every hour.

Results

Mean microdialysis-glucose during measurements was 9.8 ± 2.4mmol/l.No statistical difference in the readings was seen using a single calibration compared to eighth hour calibration (P =0.09; t-test). There was a close agreement between the continuous reading and the reference plasma glucose values with an absolute difference of 0.6+0.8mmol, or 6.8+9.3% and measurements showed high correlation to plasma readings (r = 0.92). Thelimit of agreement was 23.0%(1.94 mmol/l) compared to arterial plasma values with a line of equality close to zero.However, in a Clarke-Error Grid 93.3% of the values are in the A-area,and the remaining part in the B-area.Mean microdialysis-lactate was 1.3 ± 1.1mmol/l. The measurements showed high correlation to the blood readings (r = 0.93).

Conclusion

Continuous on-line microdialysis glucose measurement in a central vein is a potential useful technique for continuous glucose monitoring in critically ill patients, but more improvements and testingare needed.

Glycemic control in the critically ill - 3 domains and diabetic status means one size does not fit all!

Hyperglycemia, hypoglycemia, and increased glucose variability have each been shown to be independently associated with increased risk of mortality in the critically ill. Sechterberger and colleagues have completed a large observational cohort study that demonstrates that diabetic status modulates these relationships in clinically meaningful ways. These findings corroborate, in a strikingly consistent manner, those of another very recently published large observational study.