A comparison of two insulin infusion protocols in the medical intensive care unit by continuous glucose monitoring.

BACKGROUND: Achieving good glycemic control in intensive care units (ICU) requires a safe and efficient insulin infusion protocol (IIP). We aimed to compare the clinical performance of two IIPs (Leuven versus modified Yale protocol) in patients admitted to medical ICU, by using continuous glucose monitoring (CGM). This is a pooled data analysis of two published prospective randomized controlled trials. CGM monitoring was performed in 57 MICU patients (age 64 ± 12 years, APACHE-II score 28 ± 7, non-diabetic/diabetic: 36/21). The main outcome measures were percentage of time in normoglycemia (80-110 mg/dl) and in hypoglycemia (<60 mg/dl), and glycemic variability (standard deviation, coefficient of variation, mean amplitude of glucose excursions, mean of daily differences). RESULTS: Twenty-two subjects were treated using the Leuven protocol and 35 by the Yale protocol; >63,000 CGM measurements were available. The percentage of time in normoglycemia (80-110 mg/dl) was higher (37 ± 15 vs. 26 ± 11%, p = 0.001) and percentage of time spent in hypoglycemia was lower (0[0-2] vs. 5[1-8]%, p = 0.001) in the Yale group. Median glycemia did not differ between groups (118[108-128] vs. 128[106-154] mg/dl). Glycemic variability was less pronounced in the Yale group (median SD 28[21-37] vs. 47[31-71] mg/dl, p = 0.001; CV 23[19-31] vs. 36[26-50]%, p = 0.001; MODD 35[26-41] vs. 60[33-94] mg/dl, p = 0.001). However, logistic regression could not identify type of IIP, diabetes status, age, BMI, or APACHE-II score as independent parameters for strict glucose control. CONCLUSIONS: The Yale protocol provided better average glycemia, more time spent in normoglycemia, less time in hypoglycemia, and less glycemic variability than the Leuven protocol, but was not independently associated with strict glycemic control.

Randomized Evaluation of Glycemic Control in the Medical Intensive Care Unit Using Real-Time Continuous Glucose Monitoring (REGIMEN Trial).

BACKGROUND AND OBJECTIVE: Hyperglycemia occurs commonly in patients admitted to medical intensive care units (MICUs). Whether real-time (RT) continuous glucose monitoring (CGM) improves glycemic control and variability and reduces hypoglycemia in severely ill MICU patients with an Acute Physiology and Chronic Health Evaluation II (APACHE-II) score of ≥20 has not been studied. SUBJECTS AND METHODS: Thirty-five patients (66 ± 10 years of age; APACHE-II score, 28 ± 6) were randomly assigned to RT-CGM (n = 16) using the GlucoDay(®)S (A. Menarini Diagnostics, Florence, Italy) device or to blinded CGM. Insulin was infused using a modified Yale protocol targeting a blood glucose level between 80 and 120 mg/dL. Outcome measures were percentage of time in normoglycemia (80-110 mg/dL) and in hypoglycemia (<60 mg/dL), glycemic variability (SD, coefficient of variation, mean amplitude of glucose excursions, and mean of daily differences), and CGM accuracy (error grid analyses, Bland-Altman bias plot, and mean absolute relative deviation). RESULTS: During 96 h of monitoring, glycemia reached target (80-110 mg/dL) in 37 ± 15%, was between 70 and 180 mg/dL in 91 ± 10%, and <60 mg/dL in 2 ± 2% of the time. In the RT-CGM group glycemia averaged 119 ± 17 mg/dL versus 122 ± 11 mg/dL in the control group. Parameters of glucose variability and percentages of time at target glycemia and in hypoglycemia were similar between groups. GlucoDayS values and arterial glycemia correlated well, with 98.6% of data falling in Zones A and B of the error grid analysis. Mean absolute relative devation was 11.2%. CONCLUSIONS: RT-CGM did not ameliorate glucose control or variability; neither did it reduce the number of hypoglycemic events, but our insulin infusion protocol led to overall good glucose control without a significant hypoglycemia risk, making further improvement difficult.

Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems.

The relationship between both interstitial and blood glucose remains a debated topic, on which there is still no consensus. The experimental evidence suggests that blood and interstitial fluid glucose levels are correlated by a kinetic equilibrium, which as a consequence has a time and magnitude gradient in glucose concentration between blood and interstitium. Furthermore, this equilibrium can be perturbed by several physiological effects (such as foreign body response, wound-healing effect, etc.), with a consequent reduction of interstitial fluid glucose versus blood glucose correlation. In the present study, the impact of operating in the interstitium on continuous glucose monitoring systems (CGMs) will be discussed in depth, both for the application of CGMs in the management of diabetes and in other critical areas, such as tight glycaemic control in critically ill patients.

GlucoMen Day continuous glucose monitoring system: a screening for enzymatic and electrochemical interferents.

BACKGROUND: While most of the common drugs with the potential to interfere with continuous glucose monitoring (CGM) systems are accessible over the counter and can be assumed by CGM patients without medical supervision, many other chemicals are frequently used to treat critically ill patients. Continuous glucose monitoring reading accuracy may also be compromised in patients characterized by abnormally high concentrations of physiological interferents. In this article, 22 species selected from endogenous and exogenous chemicals were screened as possible interferents of GlucoMen®Day (GMD), the new microdialysis-based CGM system from A. Menarini Diagnostics. METHOD: Interference testing was performed according to the EP7-A2 guideline (Clinical and Laboratory Standards Institute 2005). Interference was evaluated at two levels of glucose, with each interferent additionally tested at two concentrations. Furthermore, two configurations of the GMD disposable sensor kit--one designed for subcutaneous application, the other for direct intravascular CGM--were challenged with interferent-spiked serum and blood samples, respectively. RESULTS: With the exception of dopamine (however, at very high, nonphysiological concentrations), no interference was observed for all the tested substances. Interestingly, none of the common electrochemical interferents (including ascorbic acid, acetaminophen, and salicylic acid, which represent the major specificity issue for the competing CGM systems) significantly affected the system's output. CONCLUSIONS: These results provide clear insights into the advantages offered by the use of a microdialysis-based CGM system that additionally relies on the detection of hydrogen peroxide at low operating potential. GlucoMen Day may become the CGM system of choice for those patients who require either regular administration of drugs or their glycemia to be tightly controlled in the intensive care unit or similar environments.

Minimizing the impact of time lag variability on accuracy evaluation of continuous glucose monitoring systems.

BACKGROUND: Despite all commercially available continuous glucose monitoring (CGM) systems being designed to operate in the extracellular interstitial fluid, and even though there is a well-recognized time lag between the interstitial and the venous compartments, the accuracy of the CGM device readings is still evaluated against the glucose concentration in venous blood (VB) samples, thus resulting in a perceived decrease in accuracy. This article explains how different time lag compensation methods (no compensation, compensation with a fixed delay, compensation with a variable delay based on an intercompartmental diffusional model) have an impact on how CGM accuracy is evaluated. METHODS: The data set used consisted of 210 CGM/blood glucose data pairs from 18 diabetes subjects (15 type 1 and 3 type 2) selected from a data base collected during two independent clinical trials. All CGM measurements were performed using the GlucoMen ®Day CGM system (A. Menarini Diagnostics, Italy), and the reference VB glucose measurements by means of a standard laboratory instrument. For each applied time lag compensation method, the CGM accuracy evaluation was performed as recommended by the POCT05-A consensus guideline. RESULTS: The perceived accuracy of the CGM device significantly improved when applying both the fixed or the variable delay compensation method. However, it is worth noting how the variable delay method, which relies on a closer description of the intercompartmental diffusion processes, provided the best perception of the clinical accuracy of the device. CONCLUSIONS: When assessing the accuracy of a CGM system, a crucial step in data analysis is to account for time lag, which enables minimization of the apparent decline in system accuracy.

Glucose variability in diabetic pregnancy.

BACKGROUND: Fetal overgrowth is the most important complication of gestational (GDM) and pregestational diabetes mellitus. METHODS: We correlated maternal glucose profiles, as detected by continuous glucose monitoring (CGM), with fetal growth parameters for 80 pregnant women (32 with type 1 diabetes, 31 with GDM, and 17 healthy controls). Glucose profiles were monitored in the first, second, and third trimesters of pregnancy for type 1 diabetes women and in the second and third trimesters for GDM women and controls. To analyze glycemic variability, we considered the mean amplitude of glycemic excursion, mean glycemia, the continuous overlapping net glycemic action (CONGA), the SD, the High Blood Glucose Index (HBGI), the Low Blood Glucose Index, and the interquartile range (IQR). RESULTS: Mean age was the same for the three groups. Prepregnancy body mass index was higher for the women with diabetes (GDM and type 1) than for controls. The newborn's mean birth weight and ponderal index were higher, although not significantly so, for the women with diabetes than for controls. For the type 1 diabetes patients, ponderal index correlated with the HBGI in the first trimester, CONGA1 and IQR in the second, and mean glycemia and SD in the third. For GDM patients, ponderal index correlated with mean glycemia and the HBGI in the second trimester. CONCLUSIONS: Fetal exposure to glycemic variability and hyperglycemia seems to be important in determining fetal overgrowth in pregnant women with diabetes. Optimal glucose control and less glucose variability are needed as early as possible in both type 1 diabetes and GDM patients to ensure normal fetal growth.

Evaluating the clinical accuracy of GlucoMen®Day: a novel microdialysis-based continuous glucose monitor.

BACKGROUND: The objective of this work was to determine the clinical accuracy of GlucoMen®Day, a new microdialysis-based continuous glucose monitoring system (CGMS) from A. Menarini Diagnostics (Florence, Italy). Accuracy evaluation was performed using continuous glucose-error grid analysis (CG-EGA), as recommended by the Performance Metrics for Continuous Interstitial Glucose Monitoring; Approved Guideline (POCT05-A). METHODS: Two independent clinical trials were carried out on patients with types 1 and 2 diabetes mellitus, the glycemic levels of whom were monitored in an in-home setting for 100-hour periods. A new multiparametric algorithm was developed and used to compensate in real-time the GlucoMen®Day signal. The time lag between continuous glucose monitoring (CGM) and reference data was first estimated using the Poincaré plot method. The entire set of CGM/reference data pairs was then evaluated following the CG-EGA criteria, which allowed an estimation of the combined point and rate accuracy stratified by glycemic ranges. RESULTS: With an estimated time lag of 11 minutes, the linear regression analysis of the CGM/reference glucose values yielded r = 0.92. The mean absolute error (MAE) was 11.4 mg/dl. The calculated mean absolute rate deviation (MARD) was 0.63 mg/dl/min. The data points falling within the A+B zones of CG-EGA were 100% in hypoglycemia, 95.7% in euglycemia, and 95.2% in hyperglycemia. CONCLUSIONS: The GlucoMen®Day system provided reliable, real-time measurement of subcutaneous glucose levels in patients with diabetes for up to 100 hours. The device showed the ability to follow rapid glycemic excursions and detect severe hypoglycemic events accurately. Its accuracy parameters fitted the criteria of the state-of-the-art consensus guideline for CGMS, with highly consistent results from two independent studies.

Surface plasmon resonance imaging (SPRi)-based sensing: a new approach in signal sampling and management.

Surface plasmon resonance imaging (SPRi) is at the forefront of optical sensing, allowing real-time and label free simultaneous multi-analyte measurements. It represents an interesting technology for studying a broad variety of affinity interactions with impact in chemistry, both in fundamental and applied research. Signal sampling and management is a key step in SPRi measurements to achieve successful performances. This work aims to develop a strategy for selecting the sensing areas, called Regions of Interest (ROIs), to be sampled for recording SPRi signals that could results in improved sensor performances. The approach has been evaluated using antigen-antibody interaction: anti-human IgGs are immobilized on the chip surface in an array format, while the specific ligand (hIgG antigen) is in solution. This approach has general applicability and demonstrates that rational selection of sensitive areas and standard management of SPRi data has dramatic impact on sensor behaviour. The criteria of the method are: (a) creation of high density maps of ROIs, (b) evaluation of the SPRi binding signals on all the ROIs during a pre-analysis step, (c) 3D elaboration of the results, and (d) ranking of the ROIs for their final selection in further biosensor analysis. Using standard solution of antigen, three different ROIs selection approaches have been compared for their analytical performances. The proposed innovative method results to be the best one for SPRi-based sensing applications.