Performance evaluations of continuous glucose monitoring systems: precision absolute relative deviation is part of the assessment

Performance of continuous glucose monitoring in patients with acute respiratory failure: a prospective, single-center observational study

OBJECTIVE

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 of the Freestyle Libre H (professional version of the Libre Pro). in patients with acute respiratory failure (ARF) in the intensive care unit (ICU).

METHODS

52 adult patients with ARF were selected. The performance of CGM was evaluated using arterial blood glucose (aBG) and point-of-care (POC) glucose as reference values. Numerical accuracy was evaluated by the mean absolute relative difference (MARD), Bland-Altman analysis, and %15/15(the percentage of CGM values within 15 mg/dL or 15% of reference values <100 mg/dL or >100mg/dL, respectively), %20/20 and %30/30; Clinical accuracy was assessed by Clarke error grid analysis.

RESULTS

519 and 1504 pairs of aBG/CGM and POC/CGM glucose values were analyzed. The MARD values were 13.8% and 14.7%, respectively. The mean deviation of the Bland‒Altman analysis was 0.82 mmol/L and 0.81 mmol/L. %15/15, %20/20 and %30/30 of aBG values were 62.6%, 75.5%, and 92.4%, respectively; %15/15, %20/20 and %30/30 of POC values were 57.1%, 72.9%, and 88.7%, respectively. The Clarke error grid analysis showed that 97.8% and 99.3% of the values located in the (A+B) zone. Additionally, accuracy of CGM is not affected by general patient factors.

CONCLUSION

This study demonstrated that the accuracy of CGM in patients with ARF is lower than that in most outpatients, and it is not affected by general patient factors. Whether CGM is beneficial to glucose management in ICU needs further evaluation.

Accuracy of continuous glucose monitoring during exercise-related hypoglycemia in individuals with type 1 diabetes

Background

Hypoglycemia is common in individuals with type 1 diabetes, especially during exercise. We investigated the accuracy of two different continuous glucose monitoring systems during exercise-related hypoglycemia in an experimental setting.

Materials and methods

Fifteen individuals with type 1 diabetes participated in two separate euglycemic-hypoglycemic clamp days (Clamp-exercise and Clamp-rest) including five phases: 1) baseline euglycemia, 2) plasma glucose (PG) decline ± exercise, 3) 15-minute hypoglycemia ± exercise, 4) 45-minute hypoglycemia, and 5) recovery euglycemia. Interstitial PG levels were measured every five minutes, using Dexcom G6 (DG6) and FreeStyle Libre 1 (FSL1). Yellow Springs Instruments 2900 was used as PG reference method, enabling mean absolute relative difference (MARD) assessment for each phase and Clarke error grid analysis for each day.

Results

Exercise had a negative effect on FSL1 accuracy in phase 2 and 3 compared to rest (ΔMARD = +5.3 percentage points [(95% CI): 1.6, 9.1] and +13.5 percentage points [6.4, 20.5], respectively). In contrast, exercise had a positive effect on DG6 accuracy during phase 2 and 4 compared to rest (ΔMARD = -6.2 percentage points [-11.2, -1.2] and -8.4 percentage points [-12.4, -4.3], respectively). Clarke error grid analysis showed a decrease in clinically acceptable treatment decisions during Clamp-exercise for FSL1 while a contrary increase was observed for DG6.

Conclusion

Physical exercise had clinically relevant impact on the accuracy of the investigated continuous glucose monitoring systems and their ability to accurately detect hypoglycemia.

Analytical Performance of the Factory-Calibrated Flash Glucose Monitoring System FreeStyle Libre2TM in Healthy Women

Continuous glucose monitoring (CGM) is used clinically and for research purposes to capture glycaemic profiles. The accuracy of CGM among healthy populations has not been widely assessed. This study assessed agreement between glucose concentrations obtained from venous plasma and from CGM (FreeStyle Libre2TM, Abbott Diabetes Care, Witney, UK) in healthy women. Glucose concentrations were assessed after fasting and every 15 min after a standardized breakfast over a 4-h lab period. Accuracy of CGM was determined by Bland-Altman plot, 15/15% sensor agreement analysis, Clarke error grid analysis (EGA) and mean absolute relative difference (MARD). In all, 429 valid CGM readings with paired venous plasma glucose (VPG) values were obtained from 29 healthy women. Mean CGM readings were 1.14 mmol/L (95% CI: 0.97 to 1.30 mmol/L, p < 0.001) higher than VPG concentrations. Ratio 95% limits of agreement were from 0.68 to 2.20, and a proportional bias (slope: 0.22) was reported. Additionally, 45% of the CGM readings were within ±0.83 mmol/L (±15 mg/dL) or ±15% of VPG, while 85.3% were within EGA Zones A + B (clinically acceptable). MARD was 27.5% (95% CI: 20.8, 34.2%), with higher MARD values in the hypoglycaemia range and when VPG concentrations were falling. The FreeStyle Libre2TM CGM system tends to overestimate glucose concentrations compared to venous plasma samples in healthy women, especially during hypoglycaemia and during glycaemic swings.

Clinical Use of a 180-Day Implantable Glucose Monitoring System in Dogs with Diabetes Mellitus: A Case Series

Simple Summary

A novel continuous glucose monitoring system (CGMS) equipped with a long-term sensor has recently been developed for humans with diabetes mellitus. The sensor is inserted under the skin and continuously measures the glucose in the interstitial fluid over a period of up to 180 days. The aim of this study was to describe, for the first time, the clinical use of this novel CGMS in three diabetic dogs (DD). The insertion and use of the device were straightforward and well tolerated by the dogs. Some device-related issues, such as sensor dislocation and trouble with daily calibrations, were reported. A good correlation between the glucose values measured by this CGMS and those obtained with a flash glucose monitoring system and a portable-blood glucose meter, previously validated for use in DD, was found (rs = 0.85 and rs = 0.81, respectively). The functional life of the sensor was 180 days in two of the three dogs, and the use of the device provided high satisfaction to the owners. This innovative device might be considered a future alternative for continuous glucose monitoring in dogs with diabetes mellitus.

Abstract

The novel Eversense XL continuous glucose monitoring system (Senseonics, Inc., Germantown, Maryland) has recently been developed for monitoring diabetes in humans. The sensor is fully implanted and has a functional life of up to 180 days. The present study describes the use of Eversense XL in three diabetic dogs (DD) with good glycemic control managed by motivated owners. The insertion and use of the device were straightforward and well tolerated by the dogs. During the wearing period, some device-related drawbacks, such as sensor dislocation and daily calibrations, were reported. A good correlation between the glucose values measured by the Eversense XL and those obtained with two commercially available devices, previously validated for use in DD, was found (r_s = 0.85 and r_s = 0.81, respectively). The life of the sensor was 180 days in two of the DD and provided high satisfaction. This innovative device might be considered a future alternative for home glucose monitoring in DD.

In Vivo Monitoring of Glucose Using Ultrasound-Induced Resonance in Implantable Smart Hydrogel Microstructures

A novel glucose sensor is presented using smart hydrogels as biocompatible implantable sensing elements, which eliminates the need for implanted electronics and uses an external medical-grade ultrasound transducer for readout. The readout mechanism uses resonance absorption of ultrasound waves in glucose-sensitive hydrogels. In vivo glucose concentration changes in the interstitial fluid lead to swelling or deswelling of the gels, which changes the resonance behavior. The hydrogels are designed and shaped such as to exhibit specific mechanical resonance frequencies while remaining sonolucent to other frequencies. Thus, they allow conventional and continued ultrasound imaging, while yielding a sensing signal at specific frequencies that correlate with glucose concentration. The resonance frequencies can be tuned by changing the shape and mechanical properties of the gel structures, such as to allow for multiple, colocated implanted hydrogels with different sensing characteristics or targets to be employed and read out, without interference using the same ultrasound transducer, by simply toggling frequencies. The fact that there is no need for any implantable electronics, also opens up the path toward future use of biodegradable hydrogels, thus creating a platform that allows injection of sensors that do not need to be retrieved when they reach the end of their useful lifespan.

Noninvasive Glucose Monitor Using Dielectric Spectroscopy

OBJECTIVE

The Alertgy noninvasive continuous glucose monitor (ANICGM) is a novel wristband device that reports glucose levels without entailing skin puncture. This study evaluated the performance of the ANICGM compared to a Food and Drug Administration-approved glucose meter in patients with type 2 diabetes.

METHODS

The ANICGM device measures changes in the electromagnetic field generated by its sensor to produce a dielectric spectrum. The data contained within this spectrum are used in tandem with machine learning algorithms to estimate blood glucose levels. Values from the ANICGM were collected, sent to the Alertgy lab, formatted, and compared with fingerstick blood glucose levels, which were measured using the Accuchek Inform II glucometer. Fifteen patients completed three 120-minute sessions. The mean absolute relative difference (MARD) was calculated.

RESULTS

MARD values were compared between study days 2 and 3. The MARD for day 2 was 18.5% (95% CI, 12.8-42.2%), and the MARD for day 3 was 15.3% (95% CI, 12.3-18.4%). The difference in the MARD between days 2 and 3 was not statistically significant (P = .210).

CONCLUSION

The resulting MARDs suggest that further investigation into the use of dielectric spectroscopy for glucose monitoring should be explored.

Effect of postprandial moderate-intensity walking for 15-min on glucose homeostasis in type 2 diabetes mellitus patients

Aim

Diabetes patients usually have a low activity level and complain about lack of time. Therefore, we investigated the effect of short time, postprandial moderate-intensity exercise on glucose homeostasis in type 2 diabetes patients.

Methods

Eleven patients with type 2 diabetes were recruited. Patients spent the first day of the study without exercise (non-exercise day; NE day). In the second day, they walked at moderate-intensity (40% of the maximum heart rate reserve) for 15 min, 30 min after each meal (exercise day; E day). Glucose homeostasis was estimated by a continuous glucose monitor (CGM). All meals during the study were of standard composition. We compared NE day and E day concerning 24-h glucose homeostasis and 3 h postprandial glucose levels by the incremental area under the curve (iAUC) method. Medications were not changed during the study.

Results

The number of patients under basal supported oral therapy, intensive insulin therapy and oral hypoglycemic agents (OHA) were 5, 4 and 2, respectively. The blood glucose standard deviation over 24 h and the iAUC for the 24-h glycemic variability (NE day vs. E day; 34,765 [21,424-56,014] vs. 23,205 [15,323-39,779]) were smaller in E day than in NE day.

Conclusion

These results suggest that postprandial moderate-intensity walking, easily performable in daily life activities, was effective for improving glucose homeostasis. Further study should be performed to clarify the relationship between postprandial walk and drug therapy (insulin and OHA), including insulin secretory ability.

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.

Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space

High-quality performance of medical devices for glucose monitoring is important for a safe and efficient usage of this diagnostic option by patients with diabetes. The mean absolute relative difference (MARD) parameter is used most often to characterize the measurement performance of systems for continuous glucose monitoring (CGM). Calculation of this parameter is relatively easy and comparison of the MARD numbers between different CGM systems appears to be straightforward on the first glance. However, a closer look reveals that a number of complex aspects make interpretation of the MARD numbers provided by the manufacturer for their CGM systems difficult. In this review, these aspects are discussed and considerations are made for a systematic and appropriate evaluation of the MARD in clinical trials. The MARD should not be used as the sole parameter to characterize CGM systems, especially when it comes to nonadjunctive usage of such systems.

Kalman Filter-Based Novel Methodology to Assess Insulin Pump Accuracy

Background: Insulin pump or continuous subcutaneous insulin infusion (CSII) system is a widely adopted contemporary treatment for type 1 diabetes and is a major component of an artificial pancreas (AP). CSII accuracy is essential for glycemic control and to-date such metric has not been given sufficient study, especially at the range of the lowest basal rate. The gold-standard assessment method IEC (International Electrotechnical Commission) 60601-2-24 has some limitations. Our study presents a new accurate and reactive method for CSII system evaluation based on direct flow measurement. Materials and Methods: A leading-edge assessment method based on a double measurement approach utilizing a direct mass flow meter and a time-stamped microgravimetric bench test was combined with a Bayesian-based mathematical filter (Kalman). The performance of this new method was evaluated while assessing the delivery precision of an off-the-shelf insulin pump at several basal rates. The proposed methodology offers a double reading-volume and flow rate-which provides direct instantaneous flow rate. CSII dose errors were evaluated using mean absolute relative dispersion (MARD) at different time intervals windows over the whole test. Results: The metrological aspect of the measurements and filtering performance were consistent. CSII precision is shown to be different in terms of the flow rate value: MARD_15min (2 UI/h) = 12.7%, MARD_15min (0.5 UI/h) = 20.4%, and MARD_15min (0.1 UI/h) = 65.0%. MARD_240min (2 UI/h) = 8.1%, (0.5 UI/h), MARD_240min (0.5 UI/h) = 18.8%, and MARD_240min (0.1 UI/h) = 18.4%. Instantaneous flow rate results highlight an irregular stroke-based delivery. Conclusion: This new method to assess insulin pump administration has been validated and highlights the current imprecision in insulin delivery, especially for the lowest basal rate, which is mainly used in pediatric cases and AP system delivery. This leading-edge method should be used to precisely compare several CSII performances in those contexts.

Glucose Variations During Driving in People With Type 1 Diabetes Using a Continuous Glucose Monitoring System

OBJECTIVE

Hypoglycemic events during driving are life-threatening complications in people with type 1 diabetes (T1D). While preliminary studies showed increased glucose demand in driving simulations, we investigated interstitial fluid (ISF) glucose when driving under real-life circumstances.

RESEARCH DESIGN AND METHODS

We measured ISF glucose in 10 participants with stable T1D during a 2-h driving course using a continuous glucose monitoring system.

RESULTS

Our data show a driving-associated rise of ISF glucose. Initially increasing glucose was followed by decreasing values. Under control conditions at the same time of the day without driving, no specific glucose changes were observed.

CONCLUSIONS

Real-life driving may have caused an initial glucose increase followed by decreasing glucose values in this cohort with well-controlled T1D. These findings may be limited to the selected study population.

Multivariable Artificial Pancreas for Various Exercise Types and Intensities

BACKGROUND

Exercise challenges people with type 1 diabetes in controlling their glucose concentration (GC). A multivariable adaptive artificial pancreas (MAAP) may lessen the burden.

METHODS

The MAAP operates without any user input and computes insulin based on continuous glucose monitor and physical activity signals. To analyze performance, 18 60-h closed-loop experiments with 96 exercise sessions with three different protocols were completed. Each day, the subjects completed one resistance and one treadmill exercise (moderate continuous training [MCT] or high-intensity interval training [HIIT]). The primary outcome is time spent in each glycemic range during the exercise + recovery period. Secondary measures include average GC and average change in GC during each exercise modality.

RESULTS

The GC during exercise + recovery periods were within the euglycemic range (70-180 mg/dL) for 69.9% of the time and within a safe glycemic range for exercise (70-250 mg/dL) for 93.0% of the time. The exercise sessions are defined to begin 30 min before the start of exercise and end 2 h after start of exercise. The GC were within the severe hypoglycemia (<55 mg/dL), moderate hypoglycemia (55-70 mg/dL), moderate hyperglycemia (180-250 mg/dL), and severe hyperglycemia (>250 mg/dL) for 0.9%, 1.3%, 23.1%, and 4.8% of the time, respectively. The average GC decline during exercise differed with exercise type (P = 0.0097) with a significant difference between the MCT and resistance (P = 0.0075). To prevent large GC decreases leading to hypoglycemia, MAAP recommended carbohydrates in 59% of MCT, 50% of HIIT, and 39% of resistance sessions.

CONCLUSIONS

A consistent GC decline occurred in exercise and recovery periods, which differed with exercise type. The average GC at the start of exercise was above target (185.5 ± 56.6 mg/dL for MCT, 166.9 ± 61.9 mg/dL for resistance training, and 171.7 ± 41.4 mg/dL HIIT), making a small decrease desirable. Hypoglycemic events occurred in 14.6% of exercise sessions and represented only 2.22% of the exercise and recovery period.

Current and Emerging Trends in Point-of-Care Technology and Strategies for Clinical Validation and Implementation

BACKGROUND

Point-of-care technology (POCT) provides actionable information at the site of care to allow rapid clinical decision-making. With healthcare emphasis shifting toward precision medicine, population health, and chronic disease management, the potential impact of POCT continues to grow, and several prominent POCT trends have emerged or strengthened in the last decade.

CONTENT

This review summarizes current and emerging trends in POCT, including technologies approved or cleared by the Food and Drug Administration or in development. Technologies included have either impacted existing clinical diagnostics applications (e.g., continuous monitoring and targeted nucleic acid testing) or are likely to impact diagnostics delivery in the near future. The focus is limited to in vitro diagnostics applications, although in some sections, technologies beyond in vitro diagnostics are also included given the commonalities (e.g., ultrasound plug-ins for smart phones). For technologies in development (e.g., wearables, noninvasive testing, mass spectrometry and nuclear magnetic resonance, paper-based diagnostics, nanopore-based devices, and digital microfluidics), we also discuss their potential clinical applications and provide perspectives on strategies beyond technological and analytical proof of concept, with the end goal of clinical implementation and impact.

SUMMARY

The field of POCT has witnessed strong growth over the past decade, as evidenced by new clinical or consumer products or research and development directions. Combined with the appropriate strategies for clinical needs assessment, validation, and implementation, these and future POCTs may significantly impact care delivery and associated outcomes and costs.

Accuracy and precision of flash glucose monitoring sensors inserted into the abdomen and upper thigh compared with the upper arm

Nowadays, most Belgian patients with type 1 diabetes use flash glucose monitoring (FreeStyle Libre [FSL]; Abbott Diabetes Care, Alameda, California) to check their glucose values, but some patients find the sensor on the upper arm too visible. The aim of the present study was to compare the accuracy and precision of FSL sensors when placed on different sites. A total of 23 adults with type 1 diabetes used three FSL sensors simultaneously for 14 days on the upper arm, abdomen and upper thigh. FSL measurements were compared with capillary blood glucose (BG) measurements obtained with a built-in FSL BG meter. The aggregated mean absolute relative difference was 11.8 ± 12.0%, 18.5 ± 18.4% and 12.3 ± 13.8% for the arm, abdomen (P = .002 vs arm) and thigh (P = .5 vs arm), respectively. Results of Clarke error grid analysis for the arm and thigh were similar (zone A: 84.9% vs 84.5%; P = .6), while less accuracy was seen for the abdomen (zone A: 69.4%; P = .01). Apart from the first day, the accuracy of FSL sensors on the arm and thigh was more stable across the 14-day wear duration than accuracy of sensors on the abdomen, which deteriorated mainly during week 2 (P < .0005). The aggregated precision absolute relative difference was markedly lower for the arm/thigh (10.9 ± 11.9%) compared with the arm/abdomen (20.9 ± 22.8%; P = .002). Our results indicate that the accuracy and precision of FSL sensors placed on the upper thigh are similar to the upper arm, whereas the abdomen performed unacceptably poorly.

Limits to the Evaluation of the Accuracy of Continuous Glucose Monitoring Systems by Clinical Trials

Systems for continuous glucose monitoring (CGM) are evolving quickly, and the data obtained are expected to become the basis for clinical decisions for many patients with diabetes in the near future. However, this requires that their analytical accuracy is sufficient. This accuracy is usually determined with clinical studies by comparing the data obtained by the given CGM system with blood glucose (BG) point measurements made with a so-called reference method. The latter is assumed to indicate the correct value of the target quantity. Unfortunately, due to the nature of the clinical trials and the approach used, such a comparison is subject to several effects which may lead to misleading results. While some reasons for the differences between the values obtained with CGM and BG point measurements are relatively well-known (e.g., measurement in different body compartments), others related to the clinical study protocols are less visible, but also quite important. In this review, we present a general picture of the topic as well as tools which allow to correct or at least to estimate the uncertainty of measures of CGM system performance.

Nanopatterned Bulk Metallic Glass Biosensors

Nanopatterning as a surface area enhancement method has the potential to increase signal and sensitivity of biosensors. Platinum-based bulk metallic glass (Pt-BMG) is a biocompatible material with electrical properties conducive for biosensor electrode applications, which can be processed in air at comparably low temperatures to produce nonrandom topography at the nanoscale. Work presented here employs nanopatterned Pt-BMG electrodes functionalized with glucose oxidase enzyme to explore the impact of nonrandom and highly reproducible nanoscale surface area enhancement on glucose biosensor performance. Electrochemical measurements including cyclic voltammetry (CV) and amperometric voltammetry (AV) were completed to compare the performance of 200 nm Pt-BMG electrodes vs Flat Pt-BMG control electrodes. Glucose dosing response was studied in a range of 2 mM to 10 mM. Effective current density dynamic range for the 200 nm Pt-BMG was 10-12 times greater than that of the Flat BMG control. Nanopatterned electrode sensitivity was measured to be 3.28 μA/cm²/mM, which was also an order of magnitude greater than the flat electrode. These results suggest that nonrandom nanotopography is a scalable and customizable engineering tool which can be integrated with Pt-BMGs to produce biocompatible biosensors with enhanced signal and sensitivity.

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.

International Consensus on Use of Continuous Glucose Monitoring

Measurement of glycated hemoglobin (HbA_1c) has been the traditional method for assessing glycemic control. However, it does not reflect intra- and interday glycemic excursions that may lead to acute events (such as hypoglycemia) or postprandial hyperglycemia, which have been linked to both microvascular and macrovascular complications. Continuous glucose monitoring (CGM), either from real-time use (rtCGM) or intermittently viewed (iCGM), addresses many of the limitations inherent in HbA_1c testing and self-monitoring of blood glucose. Although both provide the means to move beyond the HbA_1c measurement as the sole marker of glycemic control, standardized metrics for analyzing CGM data are lacking. Moreover, clear criteria for matching people with diabetes to the most appropriate glucose monitoring methodologies, as well as standardized advice about how best to use the new information they provide, have yet to be established. In February 2017, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address these issues. This article summarizes the ATTD consensus recommendations and represents the current understanding of how CGM results can affect outcomes.

International Consensus on Use of Continuous Glucose Monitoring

Measurement of glycated hemoglobin (HbA_1c) has been the traditional method for assessing glycemic control. However, it does not reflect intra- and interday glycemic excursions that may lead to acute events (such as hypoglycemia) or postprandial hyperglycemia, which have been linked to both microvascular and macrovascular complications. Continuous glucose monitoring (CGM), either from real-time use (rtCGM) or intermittently viewed (iCGM), addresses many of the limitations inherent in HbA_1c testing and self-monitoring of blood glucose. Although both provide the means to move beyond the HbA_1c measurement as the sole marker of glycemic control, standardized metrics for analyzing CGM data are lacking. Moreover, clear criteria for matching people with diabetes to the most appropriate glucose monitoring methodologies, as well as standardized advice about how best to use the new information they provide, have yet to be established. In February 2017, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address these issues. This article summarizes the ATTD consensus recommendations and represents the current understanding of how CGM results can affect outcomes.

Accuracy and Time Delay of Glucose Measurements of Continuous Glucose Monitoring and Bedside Artificial Pancreas During Hyperglycemic and Euglycemic Hyperinsulinemic Glucose Clamp Study

BACKGROUND

Glucose values of continuous glucose monitoring (CGM) have time delays compared with plasma glucose (PG) values. The artificial pancreas (STG-55, Nikkiso, Japan) (AP), which measures venous blood glucose directly, also has a time delay because of the long tubing lines from sampling vessel to the glucose sensor. We investigate accuracy and time delay of CGM and AP in comparison with PG values during 2-step glucose clamp study.

METHODS

Seven patients with type 2 diabetes and 2 healthy volunteers were included in this study. CGM (Enlite sensor, Medtronic, Northridge, CA, USA) was attached on the day before the experiment. Hyperglycemic (200 mg/dL) clamp was performed for 90 minutes, followed by euglycemic (100 mg/dL) hyperinsulinemic (100 μU/mL) clamp for 90-120 minutes using AP. CGM sensor glucose was calibrated just before and after the clamp study. AP and CGM values were compared with PG values.

RESULTS

AP values were significantly lower than PG values at 5, 30 minute during hyperglycemic clamp. In comparison, CGM value at 0 minute was significantly higher, and its following values were almost significantly lower than PG values. The time delay of AP and CGM values to reach maximum glucose levels were 5.0 ± 22.3 (NS) and 28.6 ± 32.5 ( P < .05) min, respectively. Mean absolute rate difference of CGM was significantly higher than AP (24.0 ± 7.6 vs 15.3 ± 4.6, P < .05) during glucose rising period (0-45 min); however, there were no significant differences during other periods.

CONCLUSIONS

Both CGM and AP failed to follow plasma glucose values during nonphysiologically rapid glucose rising, but indicated accurate values during physiological glucose change.

Extensive Assessment of Blood Glucose Monitoring During Postprandial Period and Its Impact on Closed-Loop Performance

BACKGROUND

Closed-loop (CL) systems aims to outperform usual treatments in blood glucose control and continuous glucose monitors (CGM) are a key component in such systems. Meals represents one of the main disturbances in blood glucose control, and postprandial period (PP) is a challenging situation for both CL system and CGM accuracy.

METHODS

We performed an extensive analysis of sensor's performance by numerical accuracy and precision during PP, as well as its influence in blood glucose control under CL therapy.

RESULTS

During PP the mean absolute relative difference (MARD) for both sensors presented lower accuracy in the hypoglycemic range (19.4 ± 12.8%) than in other ranges (12.2 ± 8.6% in euglycemic range and 9.3 ± 9.3% in hyperglycemic range). The overall MARD was 12.1 ± 8.2%. We have also observed lower MARD for rates of change between 0 and 2 mg/dl. In CL therapy, the 10 trials with the best sensor spent less time in hypoglycemia (PG < 70 mg/dl) than the 10 trials with the worst sensors (2 ± 7 minutes vs 32 ± 38 minutes, respectively).

CONCLUSIONS

In terms of accuracy, our results resemble to previously reported. Furthermore, our results showed that sensors with the lowest MARD spent less time in hypoglycemic range, indicating that the performance of CL algorithm to control PP was related to sensor accuracy.

Crosslinked basement membrane-based coatings enhance glucose sensor function and continuous glucose monitoring in vivo

Overcoming sensor-induced tissue reactions is an essential element of achieving successful continuous glucose monitoring (CGM) in the management of diabetes, particularly when used in closed loop technology. Recently, we demonstrated that basement membrane (BM)-based glucose sensor coatings significantly reduced tissue reactions at sites of device implantation. However, the biocompatible BM-based biohydrogel sensor coating rapidly degraded over a less than a 3-week period, which effectively eliminated the protective sensor coating. In an effort to increase the stability and effectiveness of the BM coating, we evaluated the impact of crosslinking BM utilizing glutaraldehyde as a crosslinking agent, designated as X-Cultrex. Sensor performance (nonrecalibrated) was evaluated for the impact of these X-Cultrex coatings in vitro and in vivo. Sensor performance was assessed over a 28-day time period in a murine CGM model and expressed as mean absolute relative difference (MARD) values. Tissue reactivity of Cultrex-coated, X-Cultrex-coated, and uncoated glucose sensors was evaluated over a 28-day time period in vivo using standard histological techniques. These studies demonstrated that X-Cultrex-based sensor coatings had no effect on glucose sensor function in vitro. In vivo, glucose sensor performance was significantly enhanced following X-Cultrex coating throughout the 28-day study. Histological evaluations of X-Cultrex-treated sensors demonstrated significantly less tissue reactivity when compared to uncoated sensors. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 7-16, 2018.

Analysis of the Accuracy and Performance of a Continuous Glucose Monitoring Sensor Prototype: An In-Silico Study Using the UVA/PADOVA Type 1 Diabetes Simulator

BACKGROUND

Computer simulation has been shown over the past decade to be a powerful tool to study the impact of medical devices characteristics on clinical outcomes. Specifically, in type 1 diabetes (T1D), computer simulation platforms have all but replaced preclinical studies and are commonly used to study the impact of measurement errors on glycemia.

METHOD

We use complex mathematical models to represent the characteristics of 3 continuous glucose monitoring systems using previously acquired data. Leveraging these models within the framework of the UVa/Padova T1D simulator, we study the impact of CGM errors in 6 simulation scenarios designed to generate a wide variety of glycemic conditions. Assessment of the simulated accuracy of each different CGM systems is performed using mean absolute relative deviation (MARD) and precision absolute relative deviation (PARD). We also quantify the capacity of each system to detect hypoglycemic events.

RESULTS

The simulated Roche CGM sensor prototype (RCGM) outperformed the 2 alternate systems (CGM-1 & CGM-2) in accuracy (MARD = 8% vs 11.4% vs 18%) and precision (PARD = 6.4% vs 9.4% vs 14.1%). These results held for all studied glucose and rate of change ranges. Moreover, it detected more than 90% of hypoglycemia, with a mean time lag less than 4 minutes (CGM-1: 86%/15 min, CGM-2: 57%/24 min).

CONCLUSION

The RCGM system model led to strong performances in these simulation studies, with higher accuracy and precision than alternate systems. Its characteristics placed it firmly as a strong candidate for CGM based therapy, and should be confirmed in large clinical studies.

Clinical Implications of Accuracy Measurements of Continuous Glucose Sensors

The accuracy of a continuous glucose monitor (CGM) now supports its use by persons with diabetes and clinicians caring for them. This article reviews measures of CGM accuracy, factors contributing to accuracy, comparative accuracy assessment, clinical implications of CGM sensor accuracy, and recent clinical trials that have demonstrated the utility of CGMs.

Significance and Reliability of MARD for the Accuracy of CGM Systems

BACKGROUND

There is a need to assess the accuracy of continuous glucose monitoring (CGM) systems for several uses. Mean absolute relative difference (MARD) is the measure of choice for this. Unfortunately, it is frequently overlooked that MARD values computed with data acquired during clinical studies do not reflect the accuracy of the CGM system only, but are strongly influenced by the design of the study. Thus, published MARD values must be understood not as precise values but as indications with some uncertainty.

DATA AND METHODS

Data from a recent clinical trial, Monte Carlo simulations, and assumptions about the error distribution of the reference measurements have been used to determine the confidence region of MARD as a function of the number and the accuracy of the reference measurements.

RESULTS

The uncertainty of the computed MARD values can be quantified by a newly introduced MARD reliability index (MRI), which independently mirrors the reliability of the evaluation. Thus MARD conveys information on the accuracy of the CGM system, while MRI conveys information on the uncertainty of the computed MARD values.

CONCLUSIONS

MARD values from clinical studies should not be used blindly but the reliability of the evaluation should be considered as well. Furthermore, it should not be ignored that MARD does not take into account the key feature of CGM sensors, the frequency of the measurements. Additional metrics, such as precision absolute relative difference (PARD) should be used as well to obtain a better evaluation of the CGM performance for specific uses, for example, for artificial pancreas.

A Comprehensive Performance Evaluation of Five Blood Glucose Systems in the Hypo-, Eu-, and Hyperglycemic Range

BACKGROUND

The objective was to evaluate the performance (in terms of accuracy, precision, and trueness) of 5 CE-certified and commercially available blood glucose (BG) systems (meters plus test strips) using an innovative clinical-experimental study design with a 3-step glucose clamp approach and frequent capillary BG measurements.

METHODS

Sixteen subjects with type 1 diabetes participated in this open label, single center trial. BG was clamped at 3 levels for 60 minutes each: 60-100-200 mg/dL. Medical staff performed regular finger pricks (up to 10 per BG level) to obtain capillary blood samples for paired BG measurements with the 5 BG systems and a laboratory method as comparison.

RESULTS

Three BG systems displayed significantly lower mean absolute relative deviations (MARD) (ACCU-Chek® Aviva Nano [5.4%], BGStar® [5.1%], iBGStar® [5.3%]) than 2 others (FreeStyle InsuLinx® [7.7%], OneTouch Verio®IQ [10.3%]). The measurement precision of all BG systems was comparable, but relative bias was also lower for the 3 systems with lower MARD (ACCU-Chek [1.3%], BGStar [-0.9%], iBGStar [1.0%]) compared with the 2 others (FreeStyle [-7.2%], OneTouch [8.9%]).

CONCLUSIONS

This 3 range glucose clamp approach enables a systematic performance evaluation of BG systems under controlled and reproducible conditions. The random error of the tested BG systems was comparable, but some showed a lower systematic error than others. These BG systems allow an accurate glucose measurement at low, normal and high BG levels.

Improving the Glucose Meter Error Grid With the Taguchi Loss Function

Glucose meters often have similar performance when compared by error grid analysis. This is one reason that other statistics such as mean absolute relative deviation (MARD) are used to further differentiate performance. The problem with MARD is that too much information is lost. But additional information is available within the A zone of an error grid by using the Taguchi loss function. Applying the Taguchi loss function gives each glucose meter difference from reference a value ranging from 0 (no error) to 1 (error reaches the A zone limit). Values are averaged over all data which provides an indication of risk of an incorrect medical decision. This allows one to differentiate glucose meter performance for the common case where meters have a high percentage of values in the A zone and no values beyond the B zone. Examples are provided using simulated data.

Impact of CCL2 and CCR2 chemokine/receptor deficiencies on macrophage recruitment and continuous glucose monitoring in vivo

The accumulation of macrophages (MΦ) at the sensor-tissue interface is thought to be a major player in controlling tissue reactions and sensor performance in vivo. Nevertheless until recently no direct demonstration of the causal relationship between MΦ aggregation and loss of sensor function existed. Using a Continuous Glucose Monitoring (CGM) murine model we previously demonstrated that genetic deficiencies of MΦ or depletion of MΦ decreased MΦ accumulation at sensor implantation sites, which led to significantly enhanced CGM performance, when compared to normal mice. Additional studies in our laboratories have also demonstrated that MΦ can act as "metabolic sinks" by depleting glucose levels at the implanted sensors in vitro and in vivo. In the present study we extended these observations by demonstrating that MΦ chemokine (CCL2) and receptor (CCR2) knockout mice displayed a decrease in inflammation and MΦ recruitment at sensor implantation sites, when compared to normal mice. This decreased MΦ recruitment significantly enhanced CGM performance when compared to control mice. These studies demonstrated the importance of the CCL2 family of chemokines and related receptors in MΦ recruitment and sensor performance and suggest chemokine targets for enhancing CGM in vivo.

AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS AND AMERICAN COLLEGE OF ENDOCRINOLOGY 2016 OUTPATIENT GLUCOSE MONITORING CONSENSUS STATEMENT

This document represents the official position of the American Association of Clinical Endocrinologists and American College of Endocrinology. Where there were no randomized controlled trials or specific U.S. FDA labeling for issues in clinical practice, the participating clinical experts utilized their judgment and experience. Every effort was made to achieve consensus among the committee members. Position statements are meant to provide guidance, but they are not to be considered prescriptive for any individual patient and cannot replace the judgment of a clinician.

Performance Comparison of CGM Systems: MARD Values Are Not Always a Reliable Indicator of CGM System Accuracy

BACKGROUND

The ongoing progress of continuous glucose monitoring (CGM) systems results in an increasing interest in comparing their performance, in particular in terms of accuracy, that is, matching CGM readings with reference values measured at the same time. Most often accuracy is evaluated by the mean absolute relative difference (MARD). It is frequently overseen that MARD does not only reflect accuracy, but also the study protocol and evaluation procedure, making a cross-study comparison problematic.

METHODS

We evaluate the effect of several factors on the MARD statistical properties: number of paired reference and CGM values, distribution of the paired values, accuracy of the reference measurement device itself and the time delay between data pairs. All analysis is done using clinical data from 12 patients wearing 6 sensors each.

RESULTS

We have found that a few paired points can have a potentially high impact on MARD. Leaving out those points for evaluation thus reduces the MARD. Similarly, accuracy of the reference measurements greatly affects the MARD as numerical and graphical data show. Results also show that a log-normal distribution of the paired references provides a significantly different MARD than, for example, a uniform distribution.

CONCLUSIONS

MARD is a reasonable parameter to characterize the performance of CGM systems when keeping its limitations in mind. To support clinicians and patients in selecting which CGM system to use in a clinical setting, care should be taken to make MARD more comparable by employing a standardized evaluation procedure.

Modelling, verification, and calibration of a photoacoustics based continuous non-invasive blood glucose monitoring system

This paper examines the use of photoacoustic spectroscopy (PAS) at an excitation wavelength of 905 nm for making continuous non-invasive blood glucose measurements. The theoretical background of the measurement technique is verified through simulation. An apparatus is fabricated for performing photoacoustic measurements in vitro on glucose solutions and in vivo on human subjects. The amplitude of the photoacoustic signals measured from glucose solutions is observed to increase with the solution concentration, while photoacoustic amplitude obtained from in vivo measurements follows the blood glucose concentration of the subjects, indicating a direct proportionality between the two quantities. A linear calibration method is applied separately on measurements obtained from each individual in order to estimate the blood glucose concentration. The estimated glucose values are compared to reference glucose concentrations measured using a standard glucose meter. A plot of 196 measurement pairs taken over 30 normal subjects on a Clarke error grid gives a point distribution of 82.65% and 17.35% over zones A and B of the grid with a mean absolute relative deviation (MARD) of 11.78% and a mean absolute difference (MAD) of 15.27 mg/dl (0.85 mmol/l). The results obtained are better than or comparable to those obtained using photoacoustic spectroscopy based methods or other non-invasive measurement techniques available. The accuracy levels obtained are also comparable to commercially available continuous glucose monitoring systems.

Online Calibration of Glucose Sensors From the Measured Current by a Time-Varying Calibration Function and Bayesian Priors

GOAL

Minimally invasive continuous glucose monitoring (CGM) sensors measure in the subcutis a current signal, which is converted into interstitial glucose (IG) concentration by a calibration process periodically updated using fingerstick blood glucose (BG) references. Though important in diabetes management, CGM sensors still suffer from accuracy problems. Here, we propose a new online calibration method improving accuracy of CGM glucose profiles with respect to manufacturer calibration.

METHOD

The proposed method fits CGM current signal against the BG references collected twice a day for calibration purposes, by a time-varying calibration function whose parameters are identified in a Bayesian framework using a priori second-order statistical knowledge. The distortion introduced by BG-to-IG kinetics is compensated before parameter identification via nonparametric deconvolution.

RESULTS

The method was tested on a database where 108 CGM signals were collected for 7 days by the Dexcom G4 Platinum sensor. Results show the new method drives to a statistically significant accuracy improvement as measured by three commonly used metrics: mean absolute relative difference reduced from 12.73% to 11.47%; percentage of accurate glucose estimates increased from 82.00% to 89.19%; and percentage of values falling in the "A" zone of the Clark error grid increased from 82.22% to 88.86%.

CONCLUSION

The new calibration method significantly improves CGM glucose profiles accuracy with respect to manufacturer calibration.

SIGNIFICANCE

The proposed algorithm provides a real-time improvement of CGM accuracy, which can be crucial in several CGM-based applications, including the artificial pancreas, thus providing a potential great impact in the diabetes technology research community.

A novel method to detect pressure-induced sensor attenuations (PISA) in an artificial pancreas

Continuous glucose monitors (CGMs) provide real-time interstitial glucose concentrations that are essential for automated treatment of individuals with type 1 diabetes. Miscalibration, noise spikes, dropouts, or pressure applied to the site (e.g., lying on the site while sleeping) can cause inaccurate glucose signals, which could lead to inappropriate insulin dosing decisions. These studies focus on the problem of pressure-induced sensor attenuations (PISAs) that occur overnight and can cause undesirable pump shut-offs in a predictive low glucose suspend system. The algorithm presented here uses real-time CGM readings without knowledge of meals, insulin doses, activity, sensor recalibrations, or fingerstick measurements. The real-time PISA detection technique was tested on outpatient "in-home" data from a predictive low-glucose suspend trial with over 1125 nights of data. A total of 178 sets were created by using different parameters for the PISA detection algorithm to illustrate its range of available performance. The tracings were reviewed via a web-based analysis tool by an engineer with an extensive expertise on analyzing clinical datasets and ~3% of the CGM readings were marked as PISA events which were used as the gold standard. It is shown that 88.34% of the PISAs were successfully detected by the algorithm, and the percentage of false detections could be reduced to 1.70% by altering the algorithm parameters. Use of the proposed PISA detection method can result in a significant decrease in undesirable pump suspensions overnight, and may lead to lower overnight mean glucose levels while still achieving a low risk of hypoglycemia.

Role of vascular networks in extending glucose sensor function: Impact of angiogenesis and lymphangiogenesis on continuous glucose monitoring in vivo

The concept of increased blood vessel (BV) density proximal to glucose sensors implanted in the interstitial tissue increases the accuracy and lifespan of sensors is accepted, despite limited existing experimental data. Interestingly, there is no previous data or even conjecture in the literature on the role of lymphatic vessels (LV) alone, or in combination with BV, in enhancing continuous glucose monitoring (CGM) in vivo. To investigate the impact of inducing vascular networks (BV and LV) at sites of glucose sensor implantation, we utilized adenovirus based local gene therapy of vascular endothelial cell growth factor-A (VEGF-A) to induce vessels at sensor implantation sites. The results of these studies demonstrated that (1) VEGF-A based local gene therapy increases vascular networks (blood vessels and lymphatic vessels) at sites of glucose sensor implantation; and (2) this local increase of vascular networks enhances glucose sensor function in vivo from 7 days to greater than 28 days postsensor implantation. This data provides "proof of concept" for the effective usage of local angiogenic factor (AF) gene therapy in mammalian models in an effort to extend CGM in vivo. It also supports the practice of a variety of viral and nonviral vectors as well as gene products (e.g. anti-inflammatory and anti-fibrosis genes) to engineer "implant friendly tissues" for the usage with implantable glucose sensors as well as other implantable devices.

Characterizing accuracy and precision of glucose sensors and meters

There is need for a method to describe precision and accuracy of glucose measurement as a smooth continuous function of glucose level rather than as a step function for a few discrete ranges of glucose. We propose and illustrate a method to generate a "Glucose Precision Profile" showing absolute relative deviation (ARD) and /or %CV versus glucose level to better characterize measurement errors at any glucose level. We examine the relationship between glucose measured by test and comparator methods using linear regression. We examine bias by plotting deviation = (test - comparator method) versus glucose level. We compute the deviation, absolute deviation (AD), ARD, and standard deviation (SD) for each data pair. We utilize curve smoothing procedures to minimize the effects of random sampling variability to facilitate identification and display of the underlying relationships between ARD or %CV and glucose level. AD, ARD, SD, and %CV display smooth continuous relationships versus glucose level. Estimates of MARD and %CV are subject to relatively large errors in the hypoglycemic range due in part to a markedly nonlinear relationship with glucose level and in part to the limited number of observations in the hypoglycemic range. The curvilinear relationships of ARD and %CV versus glucose level are helpful when characterizing and comparing the precision and accuracy of glucose sensors and meters.

Accuracy of a novel noninvasive transdermal continuous glucose monitor in critically ill patients

Stress hyperglycemia and hypoglycemia are associated with increased morbidity and mortality in the critically ill. Intermittent, random blood glucose (BG) measurements can miss episodes of hyper- and hypoglycemia. The purpose of this study was to determine the accuracy of the Symphony® continuous glucose monitor (CGM) in critically ill cardiac surgery patients. Fifteen adult cardiac surgery patients were evaluated immediately postoperatively in the intensive care unit. Prelude® SkinPrep prepared the skin and a sensor was applied to 2 test sites on each subject to monitor interstitial fluid glucose. Reference BG was sampled at 30- to 60-minute intervals. The skin at the test sites was inspected for adverse effects. Accuracy of the retrospectively analyzed CGM data relative to reference BG values was determined using continuous glucose-error grid analysis (CG-EGA) and mean absolute relative difference (MARD). Using 570 Symphony CGM glucose readings paired with reference BG measurements, CG-EGA showed that 99.6% of the readings were within zones A and B. BG measurements ranged from 73 to 251 mg/dL. The MARD was 12.3%. No adverse device effects were reported. The Symphony CGM system is able to safely, continuously, and noninvasively monitor glucose in the transdermal interstitial fluid of cardiac surgery intensive care unit patients with accuracy similar to that reported with other CGM systems. Future versions of the system will need real-time data analysis, fast warm-up, and less frequent calibrations to be used in the clinical setting.

What Are the Next Steps in Continuous Glucose Monitoring?

The development of glucose sensors for continuous glucose monitoring (CGM) is likely still in its early days. A number of novel approaches-along with many attempts to improve current CGM systems-are in development. The next generation of glucose sensors (NGGS) will also enable, for example, reliable glucose measurement in the low glycemic range. NGGS systems represent an important step forward for closed-loop systems. This commentary discusses a number of aspects that are relevant in this context.

Current Trends in Continuous Glucose Monitoring

The market introduction of systems for continuous glucose monitoring (CGM) some 15 years ago did not immediately revolutionize the treatment of diabetes; however, for a given group of patients, it would almost be inconceivable nowadays to imagine life without CGM. One day the development of insulin pumps together with CGM could culminate in an artificial pancreas system. The performance of the glucose sensors used for glucose measurement in the interstitial fluid in the subcutaneous tissue and the algorithms employed to analyze these data have improved so much over the past decade that current CGM systems by far outperform those of the first generations. This commentary discusses a number of aspects about what we have learned since CGM systems entered the market and what current trends exist in their usage. Some of these are major hurdles facing a more widespread usage of CGM.

Impact of macrophage deficiency and depletion on continuous glucose monitoring in vivo

Although it is assumed that macrophages (MQ) have a major negative impact on continuous glucose monitoring (CGM), surprisingly there is no data in the literature to directly support or refute the role of MQ or related foreign body giant cells in the bio-fouling of glucose sensors in vivo. As such, we developed the hypothesis that MQ are key in controlling glucose sensor performance and CGM in vivo and MQ deficiencies or depletion would enhance CGM. To test this hypothesis we determined the presence/distribution of MQ at the sensor tissue interface over a 28-day time period using F4/80 antibody and immunohistochemical analysis. We also evaluated the impact of spontaneous MQ deficiency (op/op mice) and induced-transgenic MQ depletions (Diphtheria Toxin Receptor (DTR) mice) on sensor function and CGM utilizing our murine CGM system. The results of these studies demonstrated: 1) a time dependent increase in MQ accumulation (F4/80 positive cells) at the sensor tissue interface; and 2) MQ deficient mice and MQ depleted C57BL/6 mice demonstrated improved sensor performance (MARD) when compared to normal mice (C57BL/6). These studies directly demonstrate the importance of MQ in sensor function and CGM in vivo.

Evaluation of the performance of a novel system for continuous glucose monitoring

BACKGROUND

The performance of a continuous glucose monitoring (CGM) system in the early stage of development was assessed in an inpatient setting that simulates daily life conditions of people with diabetes. Performance was evaluated at low glycemic, euglycemic, and high glycemic ranges as well as during phases with rapid glucose excursions.

METHODS

Each of the 30 participants with type 1 diabetes (15 female, age 47 ± 12 years, hemoglobin A1c 7.7% ± 1.3%) wore two sensors of the prototype system in parallel for 7 days. Capillary blood samples were measured at least 16 times per day (at least 15 times per daytime and at least once per night). On two subsequent study days, glucose excursions were induced. For performance evaluation, the mean absolute relative difference (MARD) between CGM readings and paired capillary blood glucose readings and precision absolute relative difference (PARD), i.e., differences between paired CGM readings were calculated.

RESULTS

Overall aggregated MARD was 9.2% and overall aggregated PARD was 7.5%. During induced glucose excursions, MARD was 10.9% and PARD was 7.8%. Lowest MARD (8.5%) and lowest PARD (6.4%) were observed in the high glycemic range (euglycemic range, MARD 9.1% and PARD 7.4%; low glycemic range, MARD 12.3% and PARD 12.4%).

CONCLUSIONS

The performance of this prototype CGM system was, particularly in the hypoglycemic range and during phases with rapid glucose fluctuations, better than performance data reported for other commercially available systems. In addition, performance of this prototype sensor was noticeably constant over the whole study period. This prototype system is not yet approved, and performance of this CGM system needs to be further assessed in clinical studies.

Performance evaluation of a continuous glucose monitoring system under conditions similar to daily life

BACKGROUND

This study aimed at evaluating and comparing the performance of a new generation of continuous glucose monitoring (CGM) system versus other CGM systems, under daily lifelike conditions.

METHODS

A total of 10 subjects (7 female) were enrolled in this study. Each subject wore two Dexcom G4™ CGM systems in parallel for the sensor lifetime specified by the manufacturer (7 days) to allow assessment of sensor-to-sensor precision. Capillary blood glucose (BG) measurements were performed at least once per hour during daytime and once at night. Glucose excursions were induced on two occasions. Performance was assessed by calculating the mean absolute relative difference (MARD) between CGM readings and paired capillary BG readings and precision absolute relative difference (PARD), i.e., differences between paired CGM readings.

RESULTS

Overall aggregate MARD was 11.0% (n = 2392). Aggregate MARD for BG &lt;70 mg/dl was 13.7%; for BG between 70 and 180 mg/dl, MARD was 11.4%; and for BG &gt;180 mg/dl, MARD was 8.5%. Aggregate PARD was 7.3%, improving from 11.6% on day 1 to 5.2% on day 7.

CONCLUSIONS

The Dexcom G4 CGM system showed good overall MARD compared with results reported for other commercially available CGM systems. In the hypoglycemic range, where CGM performance is often reported to be low, the Dexcom G4 CGM system achieved better MARD than that reported for other CGM systems in the hypoglycemic range. In the hyperglycemic range, the MARD was comparable to that reported for other CGM systems, whereas during induced glucose excursions, the MARD was similar or slightly worse than that reported for other CGM systems. Overall PARD was 7.3%, improving markedly with sensor life time.

Performance evaluation of three continuous glucose monitoring systems: comparison of six sensors per subject in parallel

BACKGROUND

This study is aimed at comparing the performance of three continuous glucose monitoring (CGM) systems following the Clinical and Laboratory Standards Institute's POCT05-A guideline, which provides recommendations for performance evaluation of CGM systems.

METHODS

A total of 12 subjects with type 1 diabetes were enrolled in this study. Each subject wore six CGM systems in parallel, two sensors of each CGM system [FreeStyle Navigator™ (Navigator), MiniMed Guardian® REAL-Time with Enlite sensor (Guardian), DexCom™ Seven® Plus 3rd generation (Seven Plus)]. Each sensor was used for the lifetime specified by the manufacturer. To follow POCT05-A recommendations, glucose excursions were induced on two separate occasions, and venous and capillary blood glucose (BG) concentrations were obtained every 15 min for five consecutive hours. Capillary BG concentrations were measured at least once per hour during the day and once at night. Parameters investigated were CGM-to-BG differences [mean absolute relative difference (MARD)] and sensor-to-sensor differences [precision absolute relative difference (PARD)].

RESULTS

Compared with capillary BG reference readings, the Navigator showed the lowest MARD, with 12.1% overall and 24.6% in the hypoglycemic range; for the Guardian and the Seven Plus, MARD was 16.2%/34.9% and 16.3%/32.7%, respectively. PARD also was lowest for the Navigator (9.6%/9.8%), followed by the Seven Plus (16.7%/25.5%) and the Guardian (18.1%/20.2%). During induced glucose excursions, MARD between CGM and BG was, again, lowest for the Navigator (14.3%), followed by the Seven Plus (15.8%) and the Guardian (19.2%).

CONCLUSIONS

In this study, two sensors of each of the three CGM systems were compared in a setting following POCT05-A recommendations. The Navigator CGM system achieved more accurate results than the Guardian or the Seven Plus with respect to MARD and PARD. Performance in the hypoglycemic range was markedly worse for all CGM systems when compared with BG results.