First experiences of using the Dexcom ONE CGM system: results from a national survey on the perception of early adopters

In recent years, meters for continuous monitoring of interstitial fluid glucose have been introduced to help people with type 1 diabetes mellitus (T1DM) to achieve better control of their disease. The objective of this project was to summarise the evidence on the clinical effectiveness and cost-effectiveness of the MiniMed(®) Paradigm™ Veo system (Medtronic Inc., Northridge, CA, USA) and the Vibe™ (Animas(®) Corporation, West Chester, PA, USA) and G4(®) PLATINUM CGM (continuous glucose monitoring) system (Dexcom Inc., San Diego, CA, USA) in comparison with multiple daily insulin injections (MDIs) or continuous subcutaneous insulin infusion (CSII), both with either self-monitoring of blood glucose (SMBG) or CGM, for the management of T1DM in adults and children. A systematic review was conducted in accordance with the principles of the Centre for Reviews and Dissemination guidance and the National Institute for Health and Care Excellence Diagnostic Assessment Programme manual. We searched 14 databases, three trial registries and two conference proceedings from study inception up to September 2014. In addition, reference lists of relevant systematic reviews were checked. In the absence of randomised controlled trials directly comparing Veo or an integrated CSII + CGM system, such as Vibe, with comparator interventions, indirect treatment comparisons were performed if possible. A commercially available cost-effectiveness model, the IMS Centre for Outcomes Research and Effectiveness diabetes model version 8.5 (IMS Health, Danbury, CT, USA), was used for this assessment. This model is an internet-based, interactive simulation model that predicts the long-term health outcomes and costs associated with the management of T1DM and type 2 diabetes. The model consists of 15 submodels designed to simulate diabetes-related complications, non-specific mortality and costs over time. As the model simulates individual patients over time, it updates risk factors and complications to account for disease progression. Fifty-four publications resulting from 19 studies were included in the review. Overall, the evidence suggests that the Veo system reduces hypoglycaemic events more than other treatments, without any differences in other outcomes, including glycated haemoglobin (HbA1c) levels. We also found significant results in favour of the integrated CSII + CGM system over MDIs with SMBG with regard to HbA1c levels and quality of life. However, the evidence base was poor. The quality of the included studies was generally low, often with only one study comparing treatments in a specific population at a specific follow-up time. In particular, there was only one study comparing Veo with an integrated CSII + CGM system and only one study comparing Veo with a CSII + SMBG system in a mixed population. Cost-effectiveness analyses indicated that MDI + SMBG is the option most likely to be cost-effective, given the current threshold of £30,000 per quality-adjusted life-year gained, whereas integrated CSII + CGM systems and Veo are dominated and extendedly dominated, respectively, by stand-alone, non-integrated CSII with CGM. Scenario analyses did not alter these conclusions. No cost-effectiveness modelling was conducted for children or pregnant women. The Veo system does appear to be better than the other systems considered at reducing hypoglycaemic events. However, in adults, it is unlikely to be cost-effective. Integrated systems are also generally unlikely to be cost-effective given that stand-alone systems are cheaper and, possibly, no less effective. However, evidence in this regard is generally lacking, in particular for children. Future trials in specific child, adolescent and adult populations should include longer term follow-up and ratings on the European Quality of Life-5 Dimensions scale at various time points with a view to informing improved cost-effectiveness modelling. PROSPERO Registration Number CRD42014013764. The National Institute for Health Research Health Technology Assessment programme.

Diabetes Technology and the Human Factor.

Background: An implantable continuous glucose monitoring (CGM) system (Eversense® XL, Senseonics, Maryland U.S.A) recently received CE Mark for 180-day duration in adults. The current study is the first investigation of the performance of the Eversense XL through 180 days in a primarily adolescent population with type I diabetes (T1D). Methods: This study was a prospective, single-center, single-arm, 180-day evaluation of the effectiveness and safety of the implantable CGM system among Canadian adolescent and adult participants with T1D. Effectiveness measures included mean absolute relative difference (MARD), system agreement with Yellow Springs Instrument (YSI) glucose values, and Clarke Error Grid analysis using paired CGM and reference YSI glucose analyzer values. Adult participants were inserted with two sensors and adolescent participants were inserted with one sensor in the upper arm. CGM system accuracy studies were performed every 30 days. The safety assessment included the incidence of insertion or removal procedure-related and device-related serious adverse events (SAEs) through 180 days post-insertion. Results: Thirty-Six participants (30 adolescent/6 adult, 13 female/23 male, mean age 17±9.2 years, mean BMI 22±4 kg/m2) received the CGM system. One subject withdrew at Day 1 due to intravenous access issues. CGM system agreement with YSI glucose within 15 mg/dL or 15% of YSI glucose values (N = 7163) through 60, 120 and 180 days was 82.9% (95% CI: 78.4%-86.1%), 83.6% (95% CI: 80.4%-85.7%) and 83.4% (95% CI: 79.7%-85.5%), respectively. Overall MARD was 9.4% (95% CI: 8.6%-10.5%). Clarke Error Grid analysis showed 99% of paired values in clinically acceptable error zones A and B. No insertion/removal or device-related SAEs were reported. Conclusions: The Eversense XL CGM system is safe and accurate through 180 days of Sensor wear in a primarily adolescent population. Disclosure R. Aronson: Other Relationship; Self; Novo Nordisk Inc., Janssen Pharmaceuticals, Inc., Sanofi, AstraZeneca. Research Support; Self; Eli Lilly and Company, Becton, Dickinson and Company, Merck & Co., Inc., Senseonics, Boehringer Ingelheim Pharmaceuticals, Inc. R. Rastogi: Employee; Self; Senseonics. C. Mdingi: Employee; Self; Senseonics. X. Chen: Employee; Self; Senseonics. K. Tweden: Employee; Self; Senseonics.

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. 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. Overall aggregate MARD was 11.0% (n = 2392). Aggregate MARD for BG <70 mg/dl was 13.7%; for BG between 70 and 180 mg/dl, MARD was 11.4%; and for BG >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. 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.

Continuous glucose monitoring (CGM) systems have been available for more than 15 years by now. However, market uptake is relatively low in most countries; in other words, relatively few patients with diabetes use CGM systems regularly. One major reason for the reluctance of patients to use CGM systems is the costs associated (i.e., in most countries no reimbursement is provided by the health insurance companies). In case reimbursement is in place, like in the United States, only certain patient groups get reimbursement that fulfills strict indications. This situation is somewhat surprising in view of the mounting evidence for benefits of CGM usage from clinical trials: most meta-analyses of these trials consistently show a clinically relevant improvement of glucose control associated with a reduction in hypoglycemic events. More recent trials with CGM systems with an improved CGM technology showed even more impressive benefits, especially if CGM systems are used in different combinations with an insulin pump (e.g., with automated bolus calculators and low glucose suspend features). Nevertheless, sufficient evidence is not available for all patient groups, and more data on cost-efficacy are needed. In addition, good data from real-world studies/registers documenting the benefits of CGM usage under daily life conditions would be of help to convince healthcare systems to cover the costs of CGM systems. In view of the ongoing improvements in established needle-type CGM systems, the fact that new CGM technology will come to the market soon (e.g., implantable sensors), that CGM-like systems are quite successfully at least in certain markets (like the flash glucose monitoring systems), and that the first artificial pancreas systems will come to the market in the next few years, there is a need to make sure that this major improvement in diabetes therapy becomes more widely available for patients with diabetes, for which better reimbursement is essential.

Glycemic control in critically ill patients has been the topic of an interesting debate during the last decade. An accurate continuous glucose monitoring system is essential to better understand this field. This prospective study thus evaluates the accuracy and technical feasibility of a continuous glucose monitoring system using intravascular microdialysis. Thirty patients undergoing cardiac surgery were monitored using a triple-lumen central venous catheter (Eirus TLC; Eirus Medical AB, Solna, Sweden) with an integrated microdialysis function. The catheter functions as a central venous catheter, enabling blood sampling and administration of infusions and medication while simultaneously providing continuous glucose monitoring. The patients were monitored for up to 48 h postoperatively. As reference, arterial blood gas samples were taken every hour and analyzed in a blood gas analyzer. Six hundred seven paired samples were obtained for analysis. Using Clarke Error Grid analysis, 100% of the paired samples were in Zones A+B, and 97% were in Zone A. Mean difference (bias) was -0.12 mmol/L, and mean absolute relative difference was 5.6%. Of the paired samples, 97.5% were correct according to International Organization for Standardization criteria. Bland-Altman analysis showed bias ± limits of agreement were -0.12 ± 0.7 mmol/L. No hypoglycemic episodes were observed. Central venous microdialysis is an accurate and reliable method for continuous blood glucose monitoring up to 48 h in patients undergoing cardiac surgery. With the microdialysis function integrated in a central venous catheter, no extra device for the continuous glucose monitoring is required. The system may be useful in critically ill patients.

The accuracy of the GlucoWatch G2 Biographer (GW2B; Cygnus, Inc., Redwood City, CA) was assessed in children and adolescents with type 1 diabetes mellitus (T1DM). During a 24-h clinical research center stay, 89 children and adolescents with T1DM (3.5-17.7 years old) wore 174 GW2Bs and had frequent serum glucose determinations during the day and night and during insulin-induced hypoglycemia and meal-induced hyperglycemia, resulting in 3672 GW2B-reference glucose pairs. The median relative absolute difference between the GW2B and reference glucose values was 16% (25th, 75th percentiles = 7%, 29%). The proposed International Organisation for Standardisation criteria were met for 60% of sensor values. Accuracy was better at higher serum glucose levels than low glucose levels. Accuracy degraded slightly as the sensor aged. Time of day, subject age, gender, or body mass index did not impact GW2B accuracy. There were no cases of serious skin reactions. Although the accuracy of this generation of sensor does not approach that of current home glucose meters, the majority of sensor glucose values are within 20% of the serum glucose. This level of accuracy may be sufficient for detecting trends and modifying diabetes management. Further longitudinal outpatient studies are needed to assess the utility of the GW2B as a management tool to improve glycemic control and decrease the incidence of severe hypoglycemia in children with diabetes.

BackgroundElderly adults with Alzheimer’s disease-related dementia (ADRD) and type 2 diabetes tend to have difficulty in detecting hypoglycemic events. Over time, recurring hypoglycemic events increase the risk for severe consequences, such as hospitalization. Previous studies have shown continuous glucose monitoring (CGM) systems to be one of the best predictors of hypoglycemia, which can be difficult to discern normally. However, CGM systems have not been formally introduced to the ADRD population, so there is a need to understand how CGM can be incorporated into the diabetes care of elderly, cognitively impaired adults.ObjectiveThe goal of this project is to develop a better understanding of how CGM systems can be extended to the ADRD population and what potential barriers may develop.MethodsA narrative review of how CGM systems are currently used by patients and caregivers was conducted using databases such as PubMed and Google Scholar, as well as clinical and CGM manufacturer manuals. Subsequently, a workflow extrapolated to ADRD adults was created based on these sources.FindingsA total of 118 articles, websites, and guides were obtained and evaluated. Current CGM workflows consist of 3-9 steps. A total of five potential areas for improvement have been identified. The newly constructed workflow consists of 9 steps: (1) healthcare visit, (2) CGM education, (3) CGM pick-up, (4) sensor insertion, (5) scan/calibrate, (6) evaluate data, (7) replace sensor, (8) next healthcare visit, and (9) pharmacist alterations.ConclusionCurrent CGM workflows are oversimplified and do not detail processes that can be complicated for adults with diabetes and ADRD and their caregivers. However, more research still needs to be conducted to determine the severity of the identified barriers and how to overcome them. This project can inform future work on the integration of CGM into diabetes care for the ADRD population.

Diabetes technology and devices transform the lives of people with diabetes.

International consensus recommends a set of continuous glucose monitoring (CGM) metrics to assess quality of diabetes therapy. The impact of individual CGM sensors on these metrics has not been thoroughly studied yet. This post hoc analysis aimed at comparing time in specific glucose ranges, coefficient of variation (CV) of glucose concentrations, and glucose management indicator (GMI) between different CGM systems and different sensors of the same system. A total of 20 subjects each wore two Dexcom G5 (G5) sensors and two FreeStyle Libre (FL) sensors for 14 days in parallel. Times in ranges, GMI, and CV were calculated for each 14-day sensor experiment, with up to four sensor experiments per subject. Pairwise differences between different sensors of the same CGM system as well as between sensors of different CGM system were calculated for these metrics. Pairwise differences between sensors of the same model showed larger differences and larger variability for FL than for G5, with some subjects showing considerable differences between the two sensors. When pairwise differences between sensors of different CGM models were calculated, substantial differences were found in some subjects (75th percentiles of differences of time spent <70 mg/dL: 5.0%, time spent >180 mg/dL: 9.2%, and GMI: 0.42%). Relevant differences in CGM metrics between different models of CGM systems, and between different sensors of the same model, worn by the same study subjects were found. Such differences should be taken into consideration when these metrics are used in the treatment of diabetes.

Continuous glucose monitoring systems - Current status and future perspectives of the flagship technologies in biosensor research -

Continuous glucose monitoring (CGM) systems are more informative than the traditional self-monitoring of capillary blood glucose (BG). Although advances in CGM technology have significantly improved the clinical utility of CGM devices compared with earlier versions, it is often difficult to assess the accuracy and precision of current devices due to differences in assessment protocols and reporting of results. Because CGM sensor accuracy can impact both the clinical utility and patient acceptance of CGM use, it is important to consider the performance characteristics seen in the current systems when assessing the clinical value of this technology. Moreover, standardization of the metrics used to assess CGM accuracy and precision are needed to help developers, clinicians, and patients make informed decisions regarding the CGM systems they are considering. In this chapter, we discuss the most commonly used methods for the assessment of CGM system performance, the accuracy and reliability of current CGM systems, and the remaining unsolved technological and physiological hurdles.

Although both strength training (ST) and endurance training (ET) seem to be beneficial in type 2 diabetes mellitus (T2D), little is known about post-exercise glucose profiles. The objective of the study was to report changes in blood glucose (BG) values after a 4-month ET and ST programme now that a device for continuous glucose monitoring has become available. Fifteen participants, comprising four men age 56.5 +/- 0.9 years and 11 women age 57.4 +/- 0.9 years with T2D, were monitored with the MiniMed (Northridge, CA, USA) continuous glucose monitoring system (CGMS) for 48 h before and after 4 months of ET or ST. The ST consisted of three sets at the beginning, increasing to six sets per week at the end of the training period, including all major muscle groups and ET performed with an intensity of maximal oxygen uptake of 60% and a volume beginning at 15 min and advancing to a maximum of 30 min three times a week. A total of 17,549 single BG measurements pretraining (619.7 +/- 39.8) and post-training (550.3 +/- 30.1) were recorded, correlating to an average of 585 +/- 25.3 potential measurements per participant at the beginning and at the end of the study. The change in BG-value between the beginning (132 mg dL(-1)) and the end (118 mg dL(-1)) for all participants was significant (P = 0.028). The improvement in BG-value for the ST programme was significant (P = 0.02) but for the ET no significant change was measured (P = 0.48). Glycaemic control improved in the ST group and the mean BG was reduced by 15.6% (Cl 3-25%). In conclusion, the CGMS may be a useful tool in monitoring improvements in glycaemic control after different exercise programmes. Additionally, the CGMS may help to identify asymptomatic hypoglycaemia or hyperglycaemia after training programmes.

This study evaluated the Medtronic MiniMed Continuous Glucose Monitoring System (CGMS) in patients with type 1 diabetes mellitus who underwent successful islet cell transplantation (ICT). The results are compared to standardized self-monitoring (SMBG) of hyperglycemia and mean amplitude of glycemic excursions (MAGE). We studied 19 patients (mean age 40.0 +/- 6.7 years) in three groups: six patients post-ICT, seven patients awaiting ICT, and six normal volunteers (controls). Continuous glucose monitoring post-ICT showed remarkable glucose stability compared with patients awaiting ICT. The CGMS group showed modestly higher glucoses (mean 111.5 mg/dl) compared with controls (88 mg/dl). Postprandial glucoses in ICT recipients rarely exceeded 180 mg/dl and were similar to controls. There was no difference in asymptomatic hypoglycemia between control and post-ICT groups. However, a higher incidence of hypoglycemia was observed in patients awaiting ICT. HbA1c and MAGE pre- and post-ICT were 8.3 +/- 0.9% and 6 +/- 0.3% (p < 0.001) and 109 +/- 34 and 41 +/- 11 (p < 0.001), respectively. No complications were associated with CGMS. This study suggests ICT significantly improves metabolic control and rate of hypoglycemia when compared with controls and patients awaiting ICT. Similar improvement in metabolic control was observed with SMBG, HbA1c, and MAGE. Although CGMS was not demonstrated to be a superior tool for routine assessment in ICT, it is very helpful in special clinical situations.

The accuracy of continuous glucose monitoring (CGM) systems is crucial for the management of glucose levels in individuals with diabetes mellitus. However, the discussion of CGM accuracy is challenged by an abundance of parameters and assessment methods. The aim of this article is to introduce the Continuous Glucose Deviation Interval and Variability Analysis (CG-DIVA), a new approach for a comprehensive characterization of CGM point accuracy which is based on the U.S. Food and Drug Administration requirements for "integrated" CGM systems. The statistical concept of tolerance intervals and data from two approved CGM systems was used to illustrate the CG-DIVA. The CG-DIVA characterizes the expected range of deviations of the CGM system from a comparison method in different glucose concentration ranges and the variability of accuracy within and between sensors. The results of the CG-DIVA are visualized in an intuitive and straightforward graphical presentation. Compared with conventional accuracy characterizations, the CG-DIVA infers the expected accuracy of a CGM system and highlights important differences between CGM systems. Furthermore, it provides information on the incidence of large errors which are of particular clinical relevance. A software implementation of the CG-DIVA is freely available (https://github.com/IfDTUlm/CGM_Performance_Assessment). We argue that the CG-DIVA can simplify the discussion and comparison of CGM accuracy and could replace the high number of conventional approaches. Future adaptations of the approach could thus become a putative standard for the accuracy characterization of CGM systems and serve as the basis for the definition of future CGM performance requirements.