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

Accuracy of FreeStyle Libre flash glucose monitoring in patients with type 2 diabetes who migrated from highlands to plains

BACKGROUND

The FreeStyle Libre flash glucose monitoring (FGM) system entered the Chinese market in 2017 to complement the self-monitoring of blood glucose. Due to its increased usage in clinics, the number of studies investigating its accuracy has increased. However, its accuracy has not been investigated in highland popu-lations in China.

AIM

To evaluate measurements recorded using the FreeStyle Libre FGM system compared with capillary blood glucose measured using the enzyme electrode method in patients with type 2 diabetes (T2D) who had migrated within 3 mo from highlands to plains.

METHODS

Overall, 68 patients with T2D, selected from those who had recently migrated from highlands to plains (within 3 mo), were hospitalized at the Department of Endocrinology from August to October 2017 and underwent continuous glucose monitoring (CGM) with the FreeStyle Libre FGM system for 14 d. Throughout the study period, fingertip capillary blood glucose was measured daily using the enzyme electrode method (Super GL, China), and blood glucose levels were read from the scanning probe during fasting and 2 h after all three meals. Moreover, the time interval between reading the data from the scanning probe and collecting fingertip capillary blood was controlled to < 5 min. The accuracy of the FGM system was evaluated according to the CGM guidelines. Subsequently, the factors influencing the mean absolute relative difference (MARD) of this system were analyzed by a multiple linear regression method.

RESULTS

Pearson’s correlation analysis showed that the fingertip and scanned glucose levels were positively correlated (R = 0.86, P = 0.00). The aggregated MARD of scanned glucose was 14.28 ± 13.40%. Parker's error analysis showed that 99.30% of the data pairs were located in areas A and B. According to the probe wear time of the FreeStyle Libre FGM system, MARD_{1 d} and MARD_{2–14 d} were 16.55% and 14.35%, respectively (t = 1.23, P = 0.22). Multiple stepwise regression analysis showed that MARD did not correlate with blood glucose when the largest amplitude of glycemic excursion (LAGE) was < 5.80 mmol/L but negatively correlated with blood glucose when the LAGE was ≥ 5.80 mmol/L.

CONCLUSION

The FreeStyle Libre FGM system has good accuracy in patients with T2D who had recently migrated from highlands to plains. This system might be ideal for avoiding the effects of high hematocrit on blood glucose monitoring in populations that recently migrated to plains. MARD is mainly influenced by glucose levels and fluctuations, and the accuracy of the system is higher when the blood glucose fluctuation is small. In case of higher blood glucose level fluctuations, deviation in the scanned glucose levels is the highest at extremely low blood glucose levels.

Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems

Comparing the performance of different continuous glucose monitoring (CGM) systems is challenging due to the lack of comprehensive guidelines for clinical study design. In particular, the absence of concise requirements for the distribution of comparator (reference) blood glucose (BG) concentrations and their rate of change (RoC) that are used to evaluate CGM performance, impairs comparability. For this article, several experts in the field of CGM performance testing have collaborated to propose characteristics of the distribution of comparator measurements that should be collected during CGM performance testing. Specifically, it is proposed that at least 7.5% of comparator BG concentrations are <70 mg/dL (3.9 mmol/L) and >300 mg/dL (16.7 mmol/L), respectively, and that at least 7.5% of BG-RoC combinations indicate fast BG changes with impending hypo- or hyperglycemia, respectively. These proposed characteristics of the comparator data can facilitate the harmonization of testing conditions across different studies and CGM systems and ensure that the most relevant scenarios representing real-life situations are established during performance testing. In addition, a study protocol and testing procedure for the manipulation of glucose levels are suggested that enable the collection of comparator data with these characteristics. This work is an important step toward establishing a future standard for the performance evaluation of CGM systems.

Continuous glucose monitoring for automatic real-time assessment of eating events and nutrition: a scoping review

Background

Accurate dietary assessment remains a challenge, particularly in free-living settings. Continuous glucose monitoring (CGM) shows promise in optimizing the assessment and monitoring of ingestive activity (IA, i.e., consumption of calorie-containing foods/beverages), and it might enable administering dietary Just-In-Time Adaptive Interventions (JITAIs).

Objective

In a scoping review, we aimed to answer the following questions: (1) Which CGM approaches to automatically detect IA in (near-)real-time have been investigated? (2) How accurate are these approaches? (3) Can they be used in the context of JITAIs?

Methods

We systematically searched four databases until October 2023 and included publications in English or German that used CGM-based approaches for human (all ages) IA detection. Eligible publications included a ground-truth method as a comparator. We synthesized the evidence qualitatively and critically appraised publication quality.

Results

Of 1,561 potentially relevant publications identified, 19 publications (17 studies, total N = 311; for 2 studies, 2 publications each were relevant) were included. Most publications included individuals with diabetes, often using meal announcements and/or insulin boluses accompanying meals. Inpatient and free-living settings were used. CGM-only approaches and CGM combined with additional inputs were deployed. A broad range of algorithms was tested. Performance varied among the reviewed methods, ranging from unsatisfactory to excellent (e.g., 21% vs. 100% sensitivity). Detection times ranged from 9.0 to 45.0 min.

Conclusion

Several CGM-based approaches are promising for automatically detecting IA. However, response times need to be faster to enable JITAIs aimed at impacting acute IA. Methodological issues and overall heterogeneity among articles prevent recommending one single approach; specific cases will dictate the most suitable approach.

Clinical Performance Evaluation of Continuous Glucose Monitoring Systems: A Scoping Review and Recommendations for Reporting

The use of different approaches for design and results presentation of studies for the clinical performance evaluation of continuous glucose monitoring (CGM) systems has long been recognized as a major challenge in comparing their results. However, a comprehensive characterization of the variability in study designs is currently unavailable. This article presents a scoping review of clinical CGM performance evaluations published between 2002 and 2022. Specifically, this review quantifies the prevalence of numerous options associated with various aspects of study design, including subject population, comparator (reference) method selection, testing procedures, and statistical accuracy evaluation. We found that there is a large variability in nearly all of those aspects and, in particular, in the characteristics of the comparator measurements. Furthermore, these characteristics as well as other crucial aspects of study design are often not reported in sufficient detail to allow an informed interpretation of study results. We therefore provide recommendations for reporting the general study design, CGM system use, comparator measurement approach, testing procedures, and data analysis/statistical performance evaluation. Additionally, this review aims to serve as a foundation for the development of a standardized CGM performance evaluation procedure, thereby supporting the goals and objectives of the Working Group on CGM established by the Scientific Division of the International Federation of Clinical Chemistry and Laboratory Medicine.

Magneto-Mechanically Triggered Thick Films for Drug Delivery Micropumps

Given the demanding use of controlled drug delivery systems, our attention was focused on developing a magnetic film that can be triggered in the presence of a magnetic field for both drug delivery and the actuating mechanism in micropump biomedical microelectromechanical systems (BioMEMS). Magnetic alginate films were fabricated in three steps: the co-precipitation of iron salts in an alkaline environment to obtain magnetite nanoparticles (Fe₃O₄), the mixing of the obtained nanoparticles with a sodium alginate solution containing glycerol as a plasticizer and folic acid as an active substance, and finally the casting of the final solution in a Petri dish followed by cross-linking with calcium chloride solution. Magnetite nanoparticles were incorporated in the alginate matrix because of the well-established biocompatibility of both materials, a property that would make the film convenient for implantable BioMEMS devices. The obtained film was analyzed in terms of its magnetic, structural, and morphological properties. To demonstrate the hypothesis that the magnetic field can be used to trigger drug release from the films, we studied the release profile in an aqueous medium (pH = 8) using a NdFeB magnet as a triggering factor.

Validity of continuous glucose monitoring for categorizing glycemic responses to diet: implications for use in personalized nutrition

BACKGROUND

Continuous glucose monitor (CGM) devices enable characterization of individuals' glycemic variation. However, there are concerns about their reliability for categorizing glycemic responses to foods that would limit their potential application in personalized nutrition recommendations.

OBJECTIVES

We aimed to evaluate the concordance of 2 simultaneously worn CGM devices in measuring postprandial glycemic responses.

METHODS

Within ZOE PREDICT (Personalised Responses to Dietary Composition Trial) 1, 394 participants wore 2 CGM devices simultaneously [n = 360 participants with 2 Abbott Freestyle Libre Pro (FSL) devices; n = 34 participants with both FSL and Dexcom G6] for ≤14 d while consuming standardized (n = 4457) and ad libitum (n = 5738) meals. We examined the CV and correlation of the incremental area under the glucose curve at 2 h (glucoseiAUC0-2 h). Within-subject meal ranking was assessed using Kendall τ rank correlation. Concordance between paired devices in time in range according to the American Diabetes Association cutoffs (TIRADA) and glucose variability (glucose CV) was also investigated.

RESULTS

The CV of glucoseiAUC0-2 h for standardized meals was 3.7% (IQR: 1.7%-7.1%) for intrabrand device and 12.5% (IQR: 5.1%-24.8%) for interbrand device comparisons. Similar estimates were observed for ad libitum meals, with intrabrand and interbrand device CVs of glucoseiAUC0-2 h of 4.1% (IQR: 1.8%-7.1%) and 16.6% (IQR: 5.5%-30.7%), respectively. Kendall τ rank correlation showed glucoseiAUC0-2h-derived meal rankings were agreeable between paired CGM devices (intrabrand: 0.9; IQR: 0.8-0.9; interbrand: 0.7; IQR: 0.5-0.8). Paired CGMs also showed strong concordance for TIRADA with a intrabrand device CV of 4.8% (IQR: 1.9%-9.8%) and an interbrand device CV of 3.2% (IQR: 1.1%-6.2%).

CONCLUSIONS

Our data demonstrate strong concordance of CGM devices in monitoring glycemic responses and suggest their potential use in personalized nutrition.This trial was registered at clinicaltrials.gov as NCT03479866.

Strategic design and improvement of the internal electron transfer of heme b domain-fused glucose dehydrogenase for use in direct electron transfer-type glucose sensors

A fusion enzyme composed of an Aspergillus flavus-derived flavin adenine dinucleotide glucose dehydrogenase (AfGDH) and an electron transfer domain of Phanerochaete chrysosporium-derived cellobiose dehydrogenase (Pcyb) was previously reported to show the direct electron transfer (DET) ability to an electrode. However, its slow intramolecular electron transfer (IET) rate from the FAD to the heme, limited the sensor signals. In this study, fusion FADGDH (Pcyb-AfGDH) enzymes were strategically redesigned by performing docking simulation, following surface-electrostatic potential estimation in the predicted area. Based on these predictions, we selected the amino acid substitution on Glu324, or on Asn408 to Lys to increase the positive charge at the rim of the interdomain region. Pcyb-AfGDH mutants were recombinantly produced using Pichia pastoris as the host microorganism, and their IET was evaluated. Spectroscopic observations showed that the Glu324Lys (E324K) and Asn408Lys (N408K) Pcyb-AfGDH mutants showed approximately 1.70- and 9.0-fold faster IET than that of wildtype Pcyb-AfGDH, respectively. Electrochemical evaluation revealed that the mutant Pcyb-AfGDH-immobilized electrodes showed higher DET current values than that of the wildtype Pcyb-AfGDH-immobilized electrodes at pH 6.5, which was approximately 9-fold higher in the E324K mutant and 15-fold higher in the N408K mutant, than in the wildtype. Glucose enzyme sensors employing N408K mutant was able to measure glucose concentration under physiological condition using artificial interstitial fluid at pH 7.4, whereas the one with wildtype Pcyb-AfGDH was not. These results indicated that the sensor employed the redesigned mutant Pcyb-AfGDH can be used for future continuous glucose monitoring system based on direct electron transfer principle. (247 words).

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.

Performance and Usability of Three Systems for Continuous Glucose Monitoring in Direct Comparison

BACKGROUND

To be able to compare continuous glucose monitoring (CGM) systems, they have to be worn in parallel by the same subjects. This study evaluated the performance and usability of three different CGM systems in direct comparison.

METHOD

In this open, prospective study at two sites, 54 patients with diabetes wore three CGM systems each (Dexcom G5™ Mobile CGM system [DG5], Guardian™ Connect system [GC], and a Roche CGM system [RCGM]) in parallel for 6 or 7 days in a mixed inpatient and outpatient setting. Capillary comparison measurements were performed using a self-monitoring of blood glucose (SMBG) system. During study site visits, glucose excursions were induced. Performance of the systems was evaluated by calculating mean absolute relative differences (MARD, calculated as absolute differences for glucose concentrations <100 mg/dL and as relative differences for glucose concentrations ≥100 mg/dL), and mean relative differences (MRD, bias) between CGM and SMBG results. In addition, usability of the systems was assessed.

RESULTS

Overall MARD was 10.1 ± 2.1 for DG5, 11.5 ± 4.2 for GC, and 11.9 ± 5.6 for RCGM. Performance improved in all systems after the first day of use. All systems showed >99% of values within zones A and B of the consensus error grid. Overall, all CGM systems showed a small negative bias compared to SMBG. Usability of the systems differed regarding patch adhesion rate, failure rate, and patient rating. Most patients preferred GC, but in general all systems were rated positively.

CONCLUSION

All three CGM systems showed similar overall accuracy in this direct comparison, but small differences were observed with regard to specific glucose ranges and usability aspects.

Analyzing the Potential of Advanced Insulin Dosing Strategies in Patients With Type 2 Diabetes: Results From a Hybrid In Silico Study

BACKGROUND

The ongoing improvement of continuous glucose monitoring (CGM) sensors and of insulin pumps are paving the way for a fast implementation of artificial pancreas (AP) for type 1 diabetes (T1D) patients. The case for type 2 diabetes (T2D) patients is less obvious since usually some residual beta cell function allows for simpler therapy approaches, and even multiple daily injections (MDI) therapy is not very widespread. However, the number of insulin dependent T2D patients is vastly increasing and therefore a need for understanding chances and challenges of an automated insulin therapy arises. Based on this background, this article analyzes conditions under which the use of more advanced therapeutic approaches, particularly AP, could bring a substantial improvement and should be considered as a viable therapy option.

METHOD

Data of 14 insulin-treated T2D patients on MDI wearing a CGM device and deviation analysis methods were used to estimate the expected improvements in the clinical outcome by using self-monitoring of blood glucose (SMBG) with advanced carbohydrate counting, a full AP or intermediate approaches, either CGM measurements with MDI therapy or SMBG with insulin pump. HbA1C and time in range (70-140 mg/dl, 70-180 mg/dl, respectively) were used as a performance measure. Outcome measures beyond glycemic control (eg, compliance, patient acceptance) have not been analyzed in this study.

RESULTS

AP has the potential to improve the condition of many poorly controlled insulin-treated T2D patients. However, as the interpatient variability is much higher than in T1D, a prescreening is recommended to select suitable patients.

CONCLUSIONS

Clinical criteria need to be developed for inclusion/exclusion of T2D patients for AP related therapies.

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.

BioMEMS for biosensors and closed-loop drug delivery

The efficacy of pharmaceutical treatments can be greatly enhanced by physiological feedback from the patient using biosensors, though this is often invasive or infeasible. By adapting microelectromechanical systems (MEMS) technology to miniaturize such biosensors, previously inaccessible signals can be obtained, often from inside the patient. This is enabled by the device's extremely small footprint which minimizes both power consumption and implantation trauma, as well as the transport time for chemical analytes, in turn decreasing the sensor's response time. MEMS fabrication also allows mass production which can be easily scaled without sacrificing its high reproducibility and reliability, and allows seamless integration with control circuitry and telemetry which is already produced using the same materials and fabrication steps. By integrating these systems with drug delivery devices, many of which are also MEMS-based, closed loop drug delivery can be achieved. This paper surveys the types of signal transduction devices available for biosensing-primarily electrochemical, optical, and mechanical-looking at their implementation via MEMS technology. The impact of MEMS technology on the challenges of biosensor development, particularly safety, power consumption, degradation, fouling, and foreign body response, are also discussed.

Effect of BGM Accuracy on the Clinical Performance of CGM: An In-Silico Study

BACKGROUND

Standard management of type 1 diabetes (T1D) relies on blood glucose monitoring based on a range of technologies from self-monitoring of blood glucose (BGM) to continuous glucose monitoring (CGM). Even as CGM technology matures, patients utilize BGM for calibration and dosing. The question of how the accuracy of both technologies interact is still not well understood.

METHODS

We use a recently developed data-driven simulation approach to characterize the relationship between CGM and BGM accuracy especially how BGM accuracy impacts CGM performance in four different use cases with increasing levels of reliance on twice daily calibrated CGM. Simulations are used to estimate clinical outcomes and isolate CGM and BGM accuracy characteristics that drive performance.

RESULTS

Our results indicate that meter (BGM) accuracy, and more specifically systematic positive or negative bias, has a significant effect on clinical performance (HbA1c and severe hypoglycemia events) in all use-cases generated for twice daily calibrated CGMs. Moreover, CGM sensor accuracy can amplify or mitigate, but not eliminate these effects.

CONCLUSION

As a system, BGM and CGM and their mode of use (use-case) interact to determine clinical outcomes. Clinical outcomes (eg, HbA1c, severe hypoglycemia, time in range) can be closely approximated by linear relationships with two BGM accuracy characteristics, namely error and bias. In turn, the coefficients of this linear relationship are determined by the use-case and by CGM accuracy (MARD).

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.

A Review of the Current Challenges Associated with the Development of an Artificial Pancreas by a Double Subcutaneous Approach

INTRODUCTION

Patients with diabetes type 1 (DM1) struggle daily to achieve good glucose control. The last decade has seen a rush of research groups working towards an artificial pancreas (AP) through the application of a double subcutaneous approach, i.e., subcutaneous (SC) continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion. Few have focused on the fundamental limitations of this approach, especially regarding outcome measures beyond time in range.

METHODS

Based on insulin physiology, the limitations of CGM, SC insulin absorption, meal challenge, and physical activity in DM1 patients, we discuss the limitations of the double SC approach. Finally, we discuss safety measures and the achievements reported in some recent AP studies that have utilized the double SC approach.

RESULTS

Most studies show that a double SC AP increases the time in range compared to a sensor-augmented insulin pump and shortens the time in hypoglycemia. Despite these achievements, the proportion of time spent in hyperglycemia is still roughly 20-40%, and hypoglycemia is still present 1-4% of the time. The main factors limiting further progress are the latency of SC CGM (at least 5-10 min) and the slow pharmacokinetics of SC-delivered fast-acting insulin. The maximum blood insulin level is reached after 45 min and the maximum glucose-lowering effect is observed after 1.5-2 h, while the glucose-lowering effect lasts for at least 5 h.

CONCLUSIONS

Although using a double SC AP leads to significant improvements in glucose control, the SC approach has severe limitations that hamper further progress towards a robust AP.

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.

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.

Accuracy of Continuous Glucose Monitoring in Patients After Total Pancreatectomy with Islet Autotransplantation

BACKGROUND

Among postsurgical and critically ill patients, malglycemia is associated with increased complications. Continuous glucose monitoring (CGM) in the inpatient population may enhance glycemic control. CGM reliability may be compromised by postsurgical complications such as edema or vascular changes. We utilized Clarke Error Grid (CEG) and Surveillance Error Grid (SEG) analysis to evaluate CGM performance after total pancreatectomy with islet autotransplantation.

MATERIALS AND METHODS

This subanalysis evaluated Medtronic Enlite 2 CGM values against YSI serum glucose in seven post-transplant patients (86% female; 38.6 ± 9.4 years) on artificial pancreas for 72 h at transition from intravenous to subcutaneous insulin. Sensor recalibration occurred for absolute relative difference (ARD) ≥20% x2, ≥30% x1, or by investigator discretion based on trend.

RESULTS

Sensor analysis showed mean absolute relative difference (MARD) of 11.0% ± 11.5%. The sensors were recalibrated 8.3 times/day; active sensor was switched 1.4 times/day. Calibration factor was 7.692 ± 3.786 mg/nA·dL (target = 1.5-20 mg/nA·dL). CEG analysis showed 86.1% of pairs in Zone A (clinically accurate zone) and 99.4% of pairs in Zones A + B (low risk of error). SEG analysis of hypoglycemia/hyperglycemia risk showed 92.22% of pairs in the "no risk" zone, 5.96% of pairs in the "slight lower" risk zone, 1.01% of pairs in the "slight higher" risk zone, and only 0.81% of pairs in the "moderate lower" risk zone.

CONCLUSIONS

Overall performance of the Medtronic Enlite 2 CGM in the post-transplant population was reasonably good with "no risk" or "slight lower" risk by SEG analysis and high CGM-YSI agreement by CEG analysis; however, frequent recalibrations were required in this intensive care population.

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.

Continuous Glucose Monitoring, Future Products, and Update on Worldwide Artificial Pancreas Projects

The development of accurate and easy-to-use continuous glucose monitoring (CGM) improved diabetes treatment by providing additional temporal information on glycemia and glucose trends to patient and physician. Although CGM enables users to lower their average glucose level without an increased incidence of hypoglycemia, this comes at the price of additional patient effort. Automation of insulin administration, also known as closed-loop (CL) or artificial pancreas treatment, has the promise to reduce patient effort and improve glycemic control. CGM data serve as the conditional input for insulin automation devices. The first commercial product for partial automation of insulin administration used insulin delivery shutoff at a predefined glucose level. These systems showed a reduction in hypoglycemia. Insulin-only CL devices show increased time spent in euglycemia and a reduction of hypo- and hyperglycemia. Improved glycemic control, coinciding with a minor decrease in hemoglobin A1c level, was confirmed in recent long-term home studies investigating these devices, paving the way for pivotal studies for commercialization of the artificial pancreas. Although the first results from dual-hormone CL systems are promising, because of increased cost of consumables of these systems, long-term head-to-head studies will have to prove superiority over insulin-only approaches. Now CL glucose control for daily use might finally become reality. Improved continuous glucose sensing technology, miniaturization of electrical devices, and development of algorithms were key in making this possible. Clinical adoption challenges, including device usability and reimbursement, need to be addressed. Time will tell for which patient groups CL systems will be reimbursed and whether these devices can deliver the promise that they hold.

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.

Time Delay of CGM Sensors: Relevance, Causes, and Countermeasures

BACKGROUND

Continuous glucose monitoring (CGM) is a powerful tool to support the optimization of glucose control of patients with diabetes. However, CGM systems measure glucose in interstitial fluid but not in blood. Rapid changes in one compartment are not accompanied by similar changes in the other, but follow with some delay. Such time delays hamper detection of, for example, hypoglycemic events. Our aim is to discuss the causes and extent of time delays and approaches to compensate for these.

METHODS

CGM data were obtained in a clinical study with 37 patients with a prototype glucose sensor. The study was divided into 5 phases over 2 years. In all, 8 patients participated in 2 phases separated by 8 months. A total number of 108 CGM data sets including raw signals were used for data analysis and were processed by statistical methods to obtain estimates of the time delay.

RESULTS

Overall mean (SD) time delay of the raw signals with respect to blood glucose was 9.5 (3.7) min, median was 9 min (interquartile range 4 min). Analysis of time delays observed in the same patients separated by 8 months suggests a patient dependent delay. No significant correlation was observed between delay and anamnestic or anthropometric data. The use of a prediction algorithm reduced the delay by 4 minutes on average.

CONCLUSIONS

Prediction algorithms should be used to provide real-time CGM readings more consistent with simultaneous measurements by SMBG. Patient specificity may play an important role in improving prediction quality.

Multisite Study of an Implanted Continuous Glucose Sensor Over 90 Days in Patients With Diabetes Mellitus

BACKGROUND

Continuous glucose monitoring (CGM), which enables real-time glucose display and trend information as well as real-time alarms, can improve glycemic control and quality of life in patients with diabetes mellitus. Previous reports have described strategies to extend the useable lifetime of a single sensor from 1-2 weeks to 28 days. The present multisite study describes the characterization of a sensing platform achieving 90 days of continuous use for a single, fully implanted sensor.

METHOD

The Senseonics CGM system is composed of a long-term implantable glucose sensor and a wearable smart transmitter. Study subjects underwent subcutaneous implantation of sensors in the upper arm. Eight-hour clinic sessions were performed every 14 days, during which sensor glucose values were compared against venous blood lab reference measurements collected every 15 minutes using mean absolute relative differences (MARDs).

RESULTS

All subjects (mean ± standard deviation age: 43.5 ± 11.0 years; with 10 sensors inserted in men and 14 in women) had type 1 diabetes mellitus. Most (22 of 24) sensors reported glucose values for the entire 90 days. The MARD value was 11.4 ± 2.7% (range, 8.1-19.5%) for reference glucose values between 40-400 mg/dl. There was no significant difference in MARD throughout the 90-day study (P = .31). No serious adverse events were noted.

CONCLUSIONS

The Senseonics CGM, composed of an implantable sensor, external smart transmitter, and smartphone app, is the first system that uses a single sensor for continuous display of accurate glucose values for 3 months.

Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings

INTRODUCTION

The accuracy of continuous glucose monitoring (CGM) systems is often assessed with respect to blood glucose (BG) readings. CGM readings are affected by a physiological and a technical time delay when compared to BG readings. In this analysis, the dependence of CGM performance parameters on the BG rate of change was investigated for 2 CGM systems.

METHODS

Data from a previously published study were retrospectively analyzed. An established CGM system (Dexcom G4, Dexcom, San Diego, CA; system A) and a prototype system (Roche Diagnostics GmbH, Mannheim, Germany; system B) with 2 sensors each were worn by 10 subjects in parallel. Glucose swings were induced to achieve rapidly changing BG concentrations. Mean absolute relative differences (MARD) were calculated in different BG rate-of-change categories. In addition, sensor-to-sensor precision was assessed.

RESULTS

At BG rates of change of -1 mg/dl/min to 0 mg/dl/min and 0 mg/dl/min to +1 mg/dl/min, MARD results were 12.6% and 11.3% for system A and 8.2% and 10.0% for system B. At rapidly changing BG concentrations (<-3 mg/dl/min and ≥+3 mg/dl/min), higher MARD results were found for both systems, but system B was less affected (system A: 24.9% and 29.6%, system B: 10.6% and 16.3%). The impact of rate of change on sensor-to-sensor precision was less pronounced.

CONCLUSIONS

Both systems were affected by rapidly changing BG concentrations to some degree, although system B was mostly unaffected by decreasing BG concentrations. It would seem that technological advancements in CGM systems might allow for a more precise tracking of BG concentrations even at rapidly changing BG concentrations.

Use of microdialysis-based continuous glucose monitoring to drive real-time semi-closed-loop insulin infusion

Continuous glucose monitoring (CGM) and automated insulin delivery may make diabetes management substantially easier, if the quality of the resulting therapy remains adequate. In this study, a semi-closed-loop control algorithm was used to drive insulin therapy and its quality was compared to that of subject-directed therapy. Twelve subjects stayed at the study site for approximately 70 hours and were provided with the investigational Automated Pancreas System Test Stand (APS-TS), which was used to calculate insulin dosage recommendations automatically. These recommendations were based on microdialysis CGM values and common diabetes therapy parameters. For the first half of their stay, the subjects directed their diabetes therapy themselves, whereas for the second half, the insulin recommendations were delivered by the APS-TS (so-called algorithm-driven therapy). During subject-directed therapy, the mean glucose was 114 mg/dl compared to 125 mg/dl during algorithm-driven therapy. Time in target (90 to 150 mg/dl) was approximately 46% during subject-directed therapy and approximately 58% during algorithm-driven therapy. When subjects directed their therapy, approximately 2 times more hypoglycemia interventions (oral administration of carbohydrates) were required than during algorithm-driven therapy. No hyperglycemia interventions (delivery of addition insulin) were necessary during subject-directed therapy, while during algorithm-driven therapy, 2 hyperglycemia interventions were necessary. The APS-TS was able to adequately control glucose concentrations in the subjects. Time in target was at least comparable or moderately higher during closed-loop control and markedly fewer hypoglycemia interventions were required, thus increasing patient safety.

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.

The artificial pancreas: current status and future prospects in the management of diabetes

Recent advances in insulins, insulin pumps, continuous glucose-monitoring systems, and control algorithms have resulted in an acceleration of progress in the development of artificial pancreas devices. This review discusses progress in the development of external systems that are based on subcutaneous drug delivery and subcutaneous continuous glucose monitoring. There are two major system-level approaches to achieving closed-loop control of blood glucose in diabetic individuals. The unihormonal approach uses insulin to reduce blood glucose and relies on complex safety mitigation algorithms to reduce the risk of hypoglycemia. The bihormonal approach uses both insulin to lower blood glucose and glucagon to raise blood glucose, and also relies on complex algorithms to provide for safety of the user. There are several major strategies for the design of control algorithms and supervision control for application to the artificial pancreas: proportional-integral-derivative, model predictive control, fuzzy logic, and safety supervision designs. Advances in artificial pancreas research in the first decade of this century were based on the ongoing computer revolution and miniaturization of electronic technology. The advent of modern smartphones has created the ability to utilize smartphone technology as the engineering centerpiece of an artificial pancreas. With these advances, an artificial or bionic pancreas is within reach.

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.

6(th) Annual Symposium on Self-Monitoring of Blood Glucose (SMBG) applications and beyond, April 25-27, 2013, Riga, Latvia

International experts in the fields of diabetes, diabetes technology, endocrinology, and pediatrics gathered for the 6(th) Annual Symposium on Self-Monitoring of Blood Glucose (SMBG) Applications and beyond. The aim of this meeting was to continue setting up a global network of experts in this field and provide an international platform for exchange of ideas to improve life for people with diabetes. The 2013 meeting comprised a comprehensive scientific program, parallel interactive workshops, and two keynote lectures. All these discussions were intended to help identify gaps and areas where further scientific work and clinical studies are warranted.