Real-time continuous glucose monitoring in an intensive care unit: better accuracy in patients with septic shock

Accuracy of continuous glucose monitoring systems in intensive care unit patients: a scoping review

PURPOSE

Glycemic control poses a challenge in intensive care unit (ICU) patients and dysglycemia is associated with poor outcomes. Continuous glucose monitoring (CGM) has been successfully implemented in the type 1 diabetes out-patient setting and renewed interest has been directed into the transition of CGM into the ICU. This scoping review aimed to provide an overview of CGM accuracy in ICU patients to inform future research and CGM implementation.

METHODS

We systematically searched PubMed and EMBASE between 5th of December 2023 and 21st of May 2024 and reported findings in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline for scoping reviews (PRISMA-ScR). We assessed studies reporting the accuracy of CGM in the ICU and report study characteristics and accuracy outcomes.

RESULTS

We identified 2133 studies, of which 96 were included. Most studies were observational (91.7%), conducted in adult patients (74%), in mixed ICUs (47.9%), from 2014 and onward, and assessed subcutaneous CGM systems (80%) using arterial blood samples as reference test (40.6%). Half of the studies (56.3%) mention the use of a prespecified reference test protocol. The mean absolute relative difference (MARD) ranged from 6.6 to 30.5% for all subcutaneous CGM studies. For newer factory calibrated CGM, MARD ranged from 9.7 to 20.6%. MARD for intravenous CGM was 5-14.2% and 6.4-13% for intraarterial CGM.

CONCLUSIONS

In this scoping review of CGM accuracy in the ICU, we found great diversity in accuracy reporting. Accuracy varied depending on CGM and comparator, and may be better for intravascular CGM and potentially lower during hypoglycemia.

Accuracy and Potential Interferences of Continuous Glucose Monitoring Sensors in the Hospital

For years, the standard of care for monitoring dysglycemia in hospitalized patients was capillary blood glucose (CBG) testing with point-of-care glucose meters. Recently, there has been a revolution in novel factory-calibrated continuous glucose monitoring (CGM) systems. Newer CGMs are smaller and less expensive, have improved accuracy and longer wear time, and do not require fingerstick CBG for calibration, resulting in increased utilization in ambulatory settings. Consequently, hospitals have noticed increased usability of CGMs among hospitalized patients and expect a progressive continued increase. During the COVID-19 pandemic, there was a critical need for innovative approaches to glycemic monitoring, with several pilot implementation projects using CGM in the intensive care unit and non-intensive care unit settings, further boosting the evidence in this area. Hence, recent guidelines have provided recommendations for the use of CGM in specific hospital scenarios and highlighted the potential of CGM to overcome CBG limitations for glucose monitoring in the inpatient setting. In this review, we provide the following: 1) an up-to-date review of the accuracy of the newer CGMs in hospitalized patients, 2) a discussion of standards for CGM accuracy metrics, 3) a contemporary overview of potential interferences that may cause inaccuracies or poor CGM performance, and 4) required steps for full regulatory approval of CGMs in the hospital and future research steps to advance the field forward.

Intensive insulin therapy in sepsis patients: Better data enables better intervention

In clinics, sepsis is a critical disease that often develops into shock and multiple organ dysfunction, leading to a serious threat of death. Patients with sepsis are often accompanied by stress hyperglycemia which is an independent risk factor for poor prognosis in sepsis. Thus, the treatment for stress hyperglycemia has attracted more and more attention, among which intensive insulin therapy is widely concerned. However, the benefits and harms of intensive insulin therapy for sepsis patients remain controversial. What the existing literature discusses mostly are the clinical benefit and hypoglycemia risk of intensive insulin therapy, but there is no conclusion on the target range of blood glucose control, the applicable patients, the timing of treatment initiation, and how to avoid the risk. In this study, we have analyzed and summarized the existing literature, hoping to determine the adverse and clinical benefit of intensive insulin therapy in sepsis. And we attempt to assemble better evidence to propose a better recommendation on hyperglycemia intervention for sepsis patients.

Effect of Ethanol Consumption on the Accuracy of a Glucose Oxidase-Based Subcutaneous Glucose Sensor in Subjects with Type 1 Diabetes

Continuous glucose monitors (CGM) have improved the management of patients with type 1 diabetes (T1D), with glucose oxidase (GOx)-based sensors being the most used. However, they are potentially subject to both electrochemical and enzymatic interferences, including those related to changes of pH. The objective of this study is to investigate the effect of ethanol, given as beer along with a mixed meal, on the accuracy of a commercial GOx-CGM. Data from 12 T1D participants in a randomized crossover trial to evaluate the effect of meal composition and alcohol consumption on postprandial glucose concentration were used. Absolute error (AE) and mean absolute relative difference (MARD) were calculated. The differences between the alcohol and nonalcohol scenarios were assessed using the Mann−Whitney U and Wilcoxon signed-rank tests. The AE in the alcohol study was low, but significantly greater as compared to the study without alcohol (p-value = 0.0418). The MARD was numerically but not significantly greater. However, both variables were greater at pH < 7.36 and significantly affected by time only in the alcohol arm. In T1D, alcohol consumption affects the accuracy of a GOx-CGM. This effect could be at least partially related to the ethanol-induced changes in pH.

Continuous Glucose Monitoring in the Hospital

Continuous glucose monitors (CGMs) have suddenly become part of routine care in many hospitals. The coronavirus disease 2019 (COVID-19) pandemic has necessitated the use of new technologies and new processes to care for hospitalized patients, including diabetes patients. The use of CGMs to automatically and remotely supplement or replace assisted monitoring of blood glucose by bedside nurses can decrease: the amount of necessary nursing exposure to COVID-19 patients with diabetes; the amount of time required for obtaining blood glucose measurements, and the amount of personal protective equipment necessary for interacting with patients during the blood glucose testing. The United States Food and Drug Administration (FDA) is now exercising enforcement discretion and not objecting to certain factory-calibrated CGMs being used in a hospital setting, both to facilitate patient care and to obtain performance data that can be used for future regulatory submissions. CGMs can be used in the hospital to decrease the frequency of fingerstick point of care capillary blood glucose testing, decrease hyperglycemic episodes, and decrease hypoglycemic episodes. Most of the research on CGMs in the hospital has focused on their accuracy and only recently outcomes data has been reported. A hospital CGM program requires cooperation of physicians, bedside nurses, diabetes educators, and hospital administrators to appropriately select and manage patients. Processes for collecting, reviewing, storing, and responding to CGM data must be established for such a program to be successful. CGM technology is advancing and we expect that CGMs will be increasingly used in the hospital for patients with diabetes.

Blood glucose and subcutaneous continuous glucose monitoring in critically ill horses: A pilot study

This pilot prospective study reports the feasibility, management and cost of the use of a continuous glucose monitoring (CGM) system in critically ill adult horses and foals. We compared the glucose measurements obtained by the CGM device with blood glucose (BG) concentrations. Neonatal foals (0–2 weeks of age) and adult horses (> 1 year old) admitted in the period of March-May 2016 with clinical and laboratory parameters compatible with systemic inflammatory response syndrome (SIRS) were included. Glucose concentration was monitored every 4 hours on blood samples with a point-of-care (POC) glucometer and with a blood gas analyzer. A CGM system was also placed on six adults and four foals but recordings were successfully obtained only in four adults and one foal. Glucose concentrations corresponded fairly well between BG and CGM, however, there appeared to be a lag time for interstitial glucose levels. Fluctuations of glucose in the interstitial fluid did not always follow the same trend as BG. CGM identified peaks and drops that would have been missed with conventional glucose monitoring. The use of CGM system is feasible in ill horses and may provide clinically relevant information on glucose levels, but there are several challenges that need to be resolved for the system to gain more widespread usability.

Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline

This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.

Perioperative Considerations for Evolving Artificial Pancreas Devices

Type 1 diabetes mellitus is a lifelong condition. It requires intensive patient involvement including frequent glucose measurements and subcutaneous insulin dosing to provide optimal glycemic control to decrease short- and long-term complications of diabetes mellitus without causing hypoglycemia. Variations in insulin pharmacokinetics and responsiveness over time in addition to illness, stress, and a myriad of other factors make ideal glucose control a challenge. Control-to-range and control-to-target artificial pancreas devices (closed-loop artificial pancreas devices [C-APDs]) consist of a continuous glucose monitor, response algorithm, and insulin delivery device that work together to automate much of the glycemic management for an individual while continually adjusting insulin dosing toward a glycemic target. In this way, a C-APD can improve glycemic control and decrease the rate of hypoglycemia. The MiniMed 670G (Medtronic, Fridley, MN) system is currently the only Food and Drug Administration-cleared C-APD in the United States. In this system, insulin delivery is continually adjusted to a glucose concentration, and the patient inputs meal-time information to modify insulin delivery as needed. Data thus far suggest improved glycemic control and decreased hypoglycemic events using the system, with decreased need for patient self-management. Thus, the anticipated use of these devices is likely to increase dramatically over time. There are limited case reports of safe intraoperative use of C-APDs, but the Food and Drug Administration has not cleared any device for such use. Nonetheless, C-APDs may offer an opportunity to improve patient safety and outcomes through enhanced intraoperative glycemic control. Anesthesiologists should become familiar with C-APD technology to help develop safe and effective protocols for their intraoperative use. We provide an overview of C-APDs and propose an introductory strategy for intraoperative study of these devices.

Diabetes Technology Update: Use of Insulin Pumps and Continuous Glucose Monitoring in the Hospital

The use of continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) systems has gained wide acceptance in diabetes care. These devices have been demonstrated to be clinically valuable, improving glycemic control and reducing risks of hypoglycemia in ambulatory patients with type 1 diabetes and type 2 diabetes. Approximately 30-40% of patients with type 1 diabetes and an increasing number of insulin-requiring patients with type 2 diabetes are using pump and sensor technology. As the popularity of these devices increases, it becomes very likely that hospital health care providers will face the need to manage the inpatient care of patients under insulin pump therapy and CGM. The American Diabetes Association advocates allowing patients who are physically and mentally able to continue to use their pumps when hospitalized. Health care institutions must have clear policies and procedures to allow the patient to continue to receive CSII treatment to maximize safety and to comply with existing regulations related to self-management of medication. Randomized controlled trials are needed to determine whether CSII therapy and CGM systems in the hospital are associated with improved clinical outcomes compared with intermittent monitoring and conventional insulin treatment or with a favorable cost-benefit ratio.

A prolonged run-in period of standard subcutaneous microdialysis ameliorates quality of interstitial glucose signal in patients after major cardiac surgery

We evaluated a standard subcutaneous microdialysis technique for glucose monitoring in two critically ill patient populations and tested whether a prolonged run-in period improves the quality of the interstitial glucose signal. 20 surgical patients after major cardiac surgery (APACHE II score: 10.1 ± 3.2) and 10 medical patients with severe sepsis (APACHE II score: 31.1 ± 4.3) were included in this investigation. A microdialysis catheter was inserted in the subcutaneous adipose tissue of the abdominal region. Interstitial fluid and arterial blood were sampled in hourly intervals to analyse glucose concentrations. Subcutaneous adipose tissue glucose was prospectively calibrated to reference arterial blood either at hour 1 or at hour 6. Median absolute relative difference of glucose (MARD), calibrated at hour 6 (6.2 (2.6; 12.4) %) versus hour 1 (9.9 (4.2; 17.9) %) after catheter insertion indicated a significant improvement in signal quality in patients after major cardiac surgery (p < 0.001). Prolonged run-in period revealed no significant improvement in patients with severe sepsis, but the number of extreme deviations from the blood plasma values could be reduced. Improved concurrence of glucose readings via a 6-hour run-in period could only be achieved in patients after major cardiac surgery.

Accuracy and reliability of a subcutaneous continuous glucose monitoring device in critically ill patients

Subcutaneous continuous glucose monitoring (CGM) may have benefits in achieving glycemic control in critically ill patients. The aim of this study was to assess the accuracy and reliability of the FreeStyle Navigator I in critically ill patients and to assess patient related factors influencing the accuracy and reliability. This study is a retrospective analysis of data from a randomized controlled trial conducted in a 20-bed mixed intensive care unit. Analytical accuracy, clinical accuracy and reliability were assessed against arterial blood glucose samples as reference. Assessment was according to recent consensus recommendations with median absolute relative difference (median ARD), Bland-Altman plots, the ISO system accuracy standards (ISO 15197:2013) and Clarke error grid analysis (CEG). We analyzed 2840 paired measurements from 155 critically ill patients. The median ARD of all paired values was 13.3 [6.9-22.1]%. The median ARD was significantly higher in both the hypoglycemic and the hyperglycemic range (32.4 [12.1-53.4]% and 18.7 [10.7-28.3]% respectively, p < 0.001). The Bland-Altman analysis showed a mean bias of - 0.82 mmol/L with a lower limit of agreement (LOA) of - 3.88 mmol/L and an upper LOA of 2.24 mmol/L. A total of 1626 (57.3%) values met the ISO-2013, standards and 1,334 (47%) CGM values were within 12.5% from the reference value. CEG: 71.0% zone A, 25.8% zone B, 0.5% zone C, 2.5% zone D, 0.3% zone E. The median overall real-time data display time was 94.0 ± 14.9% and in 23% of the patients, the sensor measured < 95% of the time. Additionally, data gaps longer than 30 min were found in 48% of the patients. The analytical accuracy of the FreeStyle Navigator I in critically ill patients was suboptimal. Furthermore, the clinical accuracy, did not meet the required standards. The reliability was satisfactory, however, in almost a quarter of the patients the realtime data display was < 95%. The accuracy was considerably and significantly lower in hyper- and hypoglycemic ranges.

Inpatient Continuous Glucose Monitoring and Glycemic Outcomes

Continuous glucose monitoring (CGM) is commonly used in the outpatient setting to improve diabetes management. CGM can provide real-time glucose trends, detecting hyperglycemia and hypoglycemia before the onset of clinical symptoms. In 2011, at the time the Endocrine Society CGM guidelines were published, the society did not recommend inpatient CGM as its efficacy and safety were unknown. While many studies have subsequently evaluated inpatient CGM accuracy and reliability, glycemic outcome studies have not been widely published. In the non-ICU setting, investigational CGM studies have commonly blinded providers and patients to glucose data. Retrospective review of the glucose data reflects increased hypoglycemia detection with CGM. In the ICU setting, data are inconsistent whether CGM can improve glycemic outcomes. Studies have not focused on hospitalized patients with type 1 diabetes mellitus, the population most likely to benefit from inpatient CGM. This article reviews inpatient CGM glycemic outcomes in the non-ICU and ICU setting.

The Clinical Benefits and Accuracy of Continuous Glucose Monitoring Systems in Critically Ill Patients-A Systematic Scoping Review

Continuous Glucose Monitoring (CGM) systems could improve glycemic control in critically ill patients. We aimed to identify the evidence on the clinical benefits and accuracy of CGM systems in these patients. For this, we performed a systematic search in Ovid MEDLINE, from inception to 26 July 2016. Outcomes were efficacy, accuracy, safety, workload and costs. Our search retrieved 356 articles, of which 37 were included. Randomized controlled trials on efficacy were scarce (n = 5) and show methodological limitations. CGM with automated insulin infusion improved time in target and mean glucose in one trial and two trials showed a decrease in hypoglycemic episodes and time in hypoglycemia. Thirty-two articles assessed accuracy, which was overall moderate to good, the latter mainly with intravascular devices. Accuracy in critically ill children seemed lower than in adults. Adverse events were rare. One study investigated the effect on workload and cost, and showed a significant reduction in both. In conclusion, studies on the efficacy and accuracy were heterogeneous and difficult to compare. There was no consistent clinical benefit in the small number of studies available. Overall accuracy was moderate to good with some intravascular devices. CGM systems seemed however safe, and might positively affect workload and costs.

Accuracy, reliability, feasibility and nurse acceptance of a subcutaneous continuous glucose management system in critically ill patients: a prospective clinical trial

BACKGROUND

Continuous glucose monitoring (CGM) has not yet been implemented in the intensive care unit (ICU) setting. The purpose of this study was to evaluate reliability, feasibility, nurse acceptance and accuracy of the Medtronic Sentrino(®) CGM system in critically ill patients.

METHODS

Sensors were inserted into the subcutaneous tissue of the patient's thigh, quantifying interstitial glucose concentration for up to 72 h per sensor. Reliability and feasibility analysis included frequency of data display, data gaps and reasons for sensor removal. We surveyed nurse acceptance in a questionnaire. For the accuracy analysis, we compared sensor values to glucose values obtained via blood gas analysis. Potential benefits of CGM were investigated in intra-individual analyses of factors, such as glycemic variability or time in target range achieved with CGM compared to that achieved with intermittent glucose monitoring.

RESULTS

The device generated 68,655 real-time values from 31 sensors in 20 critically ill patients. 532 comparative blood glucose values were collected. Data were displayed during 32.5 h [16.0/62.4] per sensor, which is 45.1 % of the expected time of 72 h and 84.8 % of 37.9 h actual monitoring time. 21 out of 31 sensors were removed prematurely. 79.1 % of the nursing staff rated the device as not beneficial; the response rate was one-third. Mean absolute relative difference was 15.3 % (CI 13.5-17.0 %). Clarke error grid: 76.9 % zone A, 21.6 % zone B, 0.2 % zone C, 0.9 % zone D, 0.4 % zone E. Bland-Altman plot: mean bias +0.53 mg/dl, limits of agreement +64.6 and -63.5 mg/dl. Accuracy deteriorated during elevated glycemic variability and in the hyperglycemic range. There was no reduction in dysglycemic events during CGM compared to 72 h before and after CGM. If CGM was measuring accurately, it identified more hyperglycemic events when compared to intermittent measurements. This study was not designed to evaluate potential benefits of CGM on glucose control.

CONCLUSIONS

The subcutaneous CGM system did not perform with satisfactory accuracy, feasibility, or nursing acceptance when evaluated in 20 medical-surgical ICU patients. Low point accuracy and prolonged data gaps significantly limited the potential clinical usefulness of the CGM trend data. Accurate continuous data display, with a MARD < 14 %, showed potential benefits in a subgroup of our patients. Trial registration NCT02296372; Ethic vote Charité EA2/095/14.

Point and trend accuracy of a continuous intravenous microdialysis-based glucose-monitoring device in critically ill patients: a prospective study

Background

Microdialysis is a well-established technology that can be used for continuous blood glucose monitoring. We determined point and trend accuracy, and reliability of a microdialysis-based continuous blood glucose-monitoring device (EIRUS^®) in critically ill patients.

Methods

Prospective study involving patients with an expected intensive care unit stay of ≥48 h. Every 15 min, device readings were compared with blood glucose values measured in arterial blood during blocks of 8 h per day for a maximum of 3 days. The Clarke error grid, Bland–Altman plot, mean absolute relative difference and glucose prediction error analysis were used to express point accuracy and the rate error grid to express trend accuracy. Reliability testing included aspects of the device and the external sensor, and the special central venous catheter (CVC) with a semipermeable membrane for use with this device.

Results

We collected 594 paired values in 12 patients (65 [26–80; 8–97] (median [IQR; total range]) paired values per patient). Point accuracy: 93.6 % of paired values were in zone A of the Clarke error grid, 6.4 % were in zone B; bias was 4.1 mg/dL with an upper limit of agreement of 28.6 mg/dL and a lower level of agreement of −20.5 mg/dL in the Bland–Altman analysis; 93.6 % of the values ≥75 mg/dL were within 20 % of the reference values in the glucose prediction error analysis; the mean absolute relative difference was 7.5 %. Trend accuracy: 96.4 % of the paired values were in zone A, and 3.3 and 0.3 % were in zone B and zone C of the rate error grid. Reliability: out of 16 sensors, 4 had to be replaced prematurely; out of 12 CVCs, two malfunctioned (one after unintentional flushing by unsupervised nurses of the ports connected to the internal microdialysis chamber, causing rupture of the semipermeable membrane; one for an unknown reason). Device start-up time was 58 [56–67] min; availability of real-time data was 100 % of the connection time.

Conclusions

In this study in critically ill patients who had no hypoglycemic episodes and a limited number of hyperglycemic excursions, point accuracy of the device was moderate to good. Trend accuracy was very good. The device had no downtimes, but 4 out of 16 external sensors and 2 out of 12 CVCs had practical problems.

Electronic supplementary material

The online version of this article (doi:10.1186/s13613-016-0171-3) contains supplementary material, which is available to authorized users.

Accuracy of a real-time continuous glucose monitoring system in children with septic shock: A pilot study

Aims:

The aim of this prospective, observational study was to determine the accuracy of a real-time continuous glucose monitoring system (CGMS) in children with septic shock.

Subjects and Methods:

Children aged 30 days to 18 years admitted to the Pediatric Intensive Care Unit with septic shock were included. A real-time CGMS sensor was used to obtain interstitial glucose readings. CGMS readings were compared statistically with simultaneous laboratory blood glucose (BG).

Results:

Nineteen children were included, and 235 pairs of BG-CGMS readings were obtained. BG and CGMS had a correlation coefficient of 0.61 (P < 0.001) and a median relative absolute difference of 17.29%. On Clarke's error grid analysis, 222 (94.5%) readings were in the clinically acceptable zones (A and B). When BG was < 70, 70–180, and > 180 mg/dL, 44%, 100%, and 76.9% readings were in zones A and B, respectively (P < 0.001). The accuracy of CGMS was not affected by the presence of edema, acidosis, vasopressors, steroids, or renal replacement therapy. On receiver operating characteristics curve analysis, a CGMS reading <97 mg/dL predicted hypoglycemia (sensitivity 85.2%, specificity 75%, area under the curve [AUC] =0.85). A reading > 141 mg/dL predicted hyperglycemia (sensitivity 84.6%, specificity 89.6%, AUC = 0.87).

Conclusion:

CGMS provides a fairly, accurate estimate of BG in children with septic shock. It is unaffected by a variety of clinical variables. The accuracy over extremes of blood sugar may be a concern. We recommend larger studies to evaluate its use for the early detection of hypoglycemia and hyperglycemia.

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.

Effects of pH, lactate, hematocrit and potassium level on the accuracy of continuous glucose monitoring (CGM) in pediatric intensive care unit

Background

Continuous glucose monitoring (CGM) originally was developed for diabetic patients and it may be a useful tool for monitoring glucose changes in pediatric intensive care unit (PICU). Its use is, however, limited by the lack of sufficient data on its reliability at insufficient peripheral perfusion. We aimed to correlate the accuracy of CGM with laboratory markers relevant to disturbed tissue perfusion.

Patients and Methods

In 38 pediatric patients (age range, 0–18 years) requiring intensive care we tested the effect of pH, lactate, hematocrit and serum potassium on the difference between CGM and meter glucose measurements. Guardian® (Medtronic®) CGM results were compared to GEM 3000 (Instrumentation laboratory®) and point-of-care measurements. The clinical accuracy of CGM was evaluated by Clarke Error Grid -, Bland-Altman analysis and Pearson’s correlation. We used Friedman test for statistical analysis (statistical significance was established as a p < 0.05).

Results

CGM values exhibited a considerable variability without any correlation with the examined laboratory parameters. Clarke, Bland-Altman analysis and Pearson’s correlation coefficient demonstrated a good clinical accuracy of CGM (zone A and B = 96%; the mean difference between reference and CGM glucose was 1,3 mg/dL, 48 from the 780 calibration pairs overrunning the 2 standard deviation; Pearson’s correlation coefficient: 0.83).

Conclusions

The accuracy of CGM measurements is independent of laboratory parameters relevant to tissue hypoperfusion. CGM may prove a reliable tool for continuous monitoring of glucose changes in PICUs, not much influenced by tissue perfusion, but still not appropriate for being the base for clinical decisions.

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.

Continuous tissue glucose monitoring correlates with measurement of intermittent capillary glucose in patients with distributive shock

BACKGROUND

Intermittent glycemic measurements in patients admitted to the intensive care unit (ICU) can result in episodes of severe hypoglycemia or in a poor control of glycemia range. We designed a study to assess accuracy and reliability of continuous monitoring of tissue glucose for patients with distributive shock.

METHODS

Consecutive patients admitted to the ICU with a diagnosis of distributive shock and the need of insulin infusion for glycemic control were included in the study. These patients were implanted a Continuous Glucose Control Monitoring System (CGMS) with the sensor inserted subcutaneously into the abdominal wall. CGMS values were recorded every 5min. Capillary glucose (CG) was monitored for adjusting insulin perfusion according to the ICU protocol. Correlation between both methods was assessed.

RESULTS

A total of 11,673 CGMS and 348 CG values were recorded. In five patients, CGMS failed to detect tissue glucose. A glucose value <3.33mmol/l (<60mg/dl) was observed in 3.6% of CGMS and in 0.29% CG values. 295 pairs of measurements were included in the statistical analysis for correlation assessment. The intraclass correlation coefficient was 0.706. The Pearson correlation coefficient was 0.71 (p<0.0001, 95% CI 0.65-0.76). The mean of differences between both measurement methods was 0.22mmol/l (3.98mg/dl) (95% CI 0.66-7.31).

CONCLUSIONS

When the Continuous Glucose Control Monitoring System (CGMS) is able to obtain data (75% of the patients), there is correlation between the values obtained by this method and capillary blood glucose in patients with distributive shock. CGMS can detect more episodes of glycemic excursions outside the normal range than intermittent capillary glucose monitoring. Variables that may impair glucose metabolism and peripheral soft tissues perfusion could impair CGMS measurements.

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.

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.

Glucose control in non-critically ill inpatients with diabetes: towards closed-loop

Inpatient glycaemic control remains an important issue due to the increasing number of patients with diabetes admitted to hospital. Morbidity and mortality in hospital are associated with poor glucose control, and cost of hospitalization is higher compared to non-diabetes patients. Guidelines for inpatient glycaemic control in the non-critical care setting have been published. Current recommendations include basal-bolus insulin therapy, regular glucose monitoring, as well as enhancing healthcare provider's role and knowledge. In spite of growing focus, implementation in practice is limited, mainly due to increasing workload burden on staff and fear of hypoglycaemia. Advances in healthcare technology may contribute to an improvement of inpatient diabetes care. Integration of glucose measurements with healthcare records and computerized glycaemic control protocols are currently being used in some institutions. Recent interests in continuous glucose monitoring have led to studies assessing its utilization in inpatients. Automation of glucose monitoring and insulin delivery may provide a safe and efficacious tool for hospital staff to manage inpatient hyperglycaemia, whilst reducing staff workload. This review summarizes the evidence on current approaches to managing inpatient glycaemic control; its utility and limitations. We conclude by discussing the evidence from feasibility studies to date, on the potential use of closed loop in the non-critical care setting and its implication for future studies.

Accuracy of subcutaneous continuous glucose monitoring in critically ill adults: improved sensor performance with enhanced calibrations

OBJECTIVE

Accurate real-time continuous glucose measurements may improve glucose control in the critical care unit. We evaluated the accuracy of the FreeStyle(®) Navigator(®) (Abbott Diabetes Care, Alameda, CA) subcutaneous continuous glucose monitoring (CGM) device in critically ill adults using two methods of calibration.

SUBJECTS AND METHODS

In a randomized trial, paired CGM and reference glucose (hourly arterial blood glucose [ABG]) were collected over a 48-h period from 24 adults with critical illness (mean±SD age, 60±14 years; mean±SD body mass index, 29.6±9.3 kg/m(2); mean±SD Acute Physiology and Chronic Health Evaluation score, 12±4 [range, 6-19]) and hyperglycemia. In 12 subjects, the CGM device was calibrated at variable intervals of 1-6 h using ABG. In the other 12 subjects, the sensor was calibrated according to the manufacturer's instructions (1, 2, 10, and 24 h) using arterial blood and the built-in point-of-care glucometer.

RESULTS

In total, 1,060 CGM-ABG pairs were analyzed over the glucose range from 4.3 to 18.8 mmol/L. Using enhanced calibration median (interquartile range) every 169 (122-213) min, the absolute relative deviation was lower (7.0% [3.5, 13.0] vs. 12.8% [6.3, 21.8], P<0.001), and the percentage of points in the Clarke error grid Zone A was higher (87.8% vs. 70.2%).

CONCLUSIONS

Accuracy of the Navigator CGM device during critical illness was comparable to that observed in non-critical care settings. Further significant improvements in accuracy may be obtained by frequent calibrations with ABG measurements.

[Role of continuous subcutaneous glucose monitoring in intensive care]

Critical care associated with stress hyperglycaemia has gained a new view in the last decade since the demonstration of the beneficial effects of strong glycaemic control on the mortality in intensive care units. Strong glycaemic control may, however, induce hypoglycaemia, resulting in increased mortality, too. Pediatric population has an increased risk of hypoglycaemia because of the developing central nervous system. In this view there is a strong need for close monitoring of glucose levels in intensive care units. The subcutaneous continuous glucose monitoring developed for diabetes care is an alternative for this purpose instead of regular blood glucose measurements. It is important to know the limitations of subcutaneous continuous glucose monitoring in intensive care. Decreased tissue perfusion may disturb the results of subcutaneous continuous glucose monitoring, because the measurement occurs in interstitial fluid. The routine use of subcutaneous continuous glucose monitoring in intensive care units is not recommended yet until sufficient data on the reliability of the system are available. The Medtronic subcutaneous continuous glucose monitoring system is evaluated in the review partly based on the authors own results.

Continuous glucose monitoring: 40 years, what we've learned and what's next

After 40 years of research and development, today continuous glucose monitoring (CGM) is demonstrating the benefit it provides for millions with diabetes. To provide in vivo accuracy, new permselective membranes and mediated systems have been developed to prevent enzyme saturation and to minimize interference signals. Early in vivo implanted sensor research clearly showed that the foreign body response was a more difficult issue to overcome. Understanding the biological interface and circumventing the inflammatory response continue to drive development of a CGM sensor with accuracy and reliability performance suitable in a closed-loop artificial pancreas. Along with biocompatible polymer development, other complimentary algorithm and data analysis techniques have improved the performance of commercial systems significantly. For example, the mean average relative difference of Dexcom's CGM system improved from 26 to 14% and its use-life was extended from 3 to 7 d. Significant gains in usability, including size, flexibility, insertion, calibration, and data interface, have been incorporated into new generations of commercial CGM systems. Besides Medtronic, Dexcom, and Abbott, other major players are also investing in CGM. Becton Dickinson is conducting clinical trials with an optical galactose glucose binding system. Development of fully implanted sensor systems fulfills the desire for a discreet, reliable CGM system. Research continues to find innovative ways to help make living with diabetes easier and more normal, and new segments are being pursued (intensive care unit, surgery, behavior modification) in which CGM is being utilized.

Real-time continuous glucose monitoring shows high accuracy within 6 hours after sensor calibration: a prospective study

Accurate and timely glucose monitoring is essential in intensive care units. Real-time continuous glucose monitoring system (CGMS) has been advocated for many years to improve glycemic management in critically ill patients. In order to determine the effect of calibration time on the accuracy of CGMS, real-time subcutaneous CGMS was used in 18 critically ill patients. CGMS sensor was calibrated with blood glucose measurements by blood gas/glucose analyzer every 12 hours. Venous blood was sampled every 2 to 4 hours, and glucose concentration was measured by standard central laboratory device (CLD) and by blood gas/glucose analyzer. With CLD measurement as reference, relative absolute difference (mean±SD) in CGMS and blood gas/glucose analyzer were 14.4%±12.2% and 6.5%±6.2%, respectively. The percentage of matched points in Clarke error grid zone A was 74.8% in CGMS, and 98.4% in blood gas/glucose analyzer. The relative absolute difference of CGMS obtained within 6 hours after sensor calibration (8.8%±7.2%) was significantly less than that between 6 to 12 hours after calibration (20.1%±13.5%, p<0.0001). The percentage of matched points in Clarke error grid zone A was also significantly higher in data sets within 6 hours after calibration (92.4% versus 57.1%, p<0.0001). In conclusion, real-time subcutaneous CGMS is accurate in glucose monitoring in critically ill patients. CGMS sensor should be calibrated less than 6 hours, no matter what time interval recommended by manufacturer.

The use of continuous glucose monitoring combined with computer-based eMPC algorithm for tight glucose control in cardiosurgical ICU

AIM

In postcardiac surgery patients, we assessed the performance of a system for intensive intravenous insulin therapy using continuous glucose monitoring (CGM) and enhanced model predictive control (eMPC) algorithm.

METHODS

Glucose control in eMPC-CGM group (n = 12) was compared with a control (C) group (n = 12) treated by intravenous insulin infusion adjusted according to eMPC protocol with a variable sampling interval alone. In the eMPC-CGM group glucose measured with a REAL-Time CGM system (Guardian RT) served as input for the eMPC adjusting insulin infusion every 15 minutes. The accuracy of CGM was evaluated hourly using reference arterial glucose and Clarke error-grid analysis (C-EGA). Target glucose range was 4.4-6.1 mmol/L.

RESULTS

Of the 277 paired CGM-reference glycemic values, 270 (97.5%) were in clinically acceptable zones of C-EGA and only 7 (2.5%) were in unacceptable D zone. Glucose control in eMPC-CGM group was comparable to C group in all measured values (average glycemia, percentage of time above, within, and below target range,). No episode of hypoglycemia (<2.9 mmol) occurred in eMPC-CGM group compared to 2 in C group.

CONCLUSION

Our data show that the combination of eMPC algorithm with CGM is reliable and accurate enough to test this approach in a larger study population.

Analysis: continuous glucose monitoring in the intensive care unit

Control of glycemia in hospitalized patients is important; hypoglycemia is associated with increased mortality, and hyperglycemia is associated with adverse outcomes. For these reasons, though no such device is currently available, continuous glucose monitoring (CGM) is an attractive option, especially in the critical care setting. Schierenbeck and coauthors, in this issue of Journal of Diabetes Science and Technology, report on the use of a specialized central catheter designed to monitor glucose continuously in post cardiac surgery patients. This catheter, which was indwelled within the great veins, was specially designed with a separate lumen and membrane that allowed continuous glucose microdialysis. Accuracy was quite good, better than has been reported with the use of commercially-available CGM devices. Ideally, further development of this quite promising catheter-based device would allow it to be used also to deliver fluids and drugs, thus avoiding the need for a second catheter elsewhere.

Using stochastic modelling to identify unusual continuous glucose monitor measurements and behaviour, in newborn infants

Background

Abnormal blood glucose (BG) concentrations have been associated with increased morbidity and mortality in both critically ill adults and infants. Furthermore, hypoglycaemia and glycaemic variability have both been independently linked to mortality in these patients. Continuous Glucose Monitoring (CGM) devices have the potential to improve detection and diagnosis of these glycaemic abnormalities. However, sensor noise is a trade-off of the high measurement rate and must be managed effectively if CGMs are going to be used to monitor, diagnose and potentially help treat glycaemic abnormalities.

Aim

To develop a tool that will aid clinicians in identifying unusual CGM behaviour and highlight CGM data that potentially need to be interpreted with care.

Methods

CGM data and BG measurements from 50 infants at risk of hypoglycaemia were used. Unusual CGM measurements were classified using a stochastic model based on the kernel density method and historical CGM measurements from the cohort. CGM traces were colour coded with very unusual measurements coloured red, highlighting areas to be interpreted with care. A 5-fold validation of the model was Monte Carlo simulated 25 times to ensure an adequate model fit.

Results

The stochastic model was generated using ~67,000 CGM measurements, spread across the glycaemic range ~2-10 mmol/L. A 5-fold validation showed a good model fit: the model 80% confidence interval (CI) captured 83% of clinical CGM data, the model 90% CI captured 91% of clinical CGM data, and the model 99% CI captured 99% of clinical CGM data. Three patient examples show the stochastic classification method in use with 1) A stable, low variability patient which shows no unusual CGM measurements, 2) A patient with a very sudden, short hypoglycaemic event (classified as unusual), and, 3) A patient with very high, potentially un-physiological, glycaemic variability after day 3 of monitoring (classified as very unusual).

Conclusions

This study has produced a stochastic model and classification method capable of highlighting unusual CGM behaviour. This method has the potential to classify important glycaemic events (e.g. hypoglycaemia) as true clinical events or sensor noise, and to help identify possible sensor degradation. Colour coded CGM traces convey the information quickly and efficiently, while remaining computationally light enough to be used retrospectively or in real-time.