Evaluation of Metabolic Control Using a Continuous Subcutaneous Glucose Monitoring System in Patients with Type 1 Diabetes Mellitus who Achieved Insulin Independence after Islet Cell Transplantation

Continuous glucose monitoring (CGM) is today provided by various techniques. This study aims to compare two different CGM-systems: the FreeStyle Libre subcutaneous continuous glucose monitoring system (SC-CGM) and the Eirus intravascular microdialysis continuous glucose monitoring system (MD-CGM) in patients undergoing cardiac surgery. A total of 26 patients were equipped with both the SC-CGM and the MD-CGM systems. The SC-CGM system was placed subcutaneously in the left upper-arm and the MD-CGM system was placed in the superior vena cava. Reference blood glucose values were obtained by analyzing arterial blood in a blood gas analyzer. Reference glucose values were then paired with glucose values from both CGM-systems and analyzed for accuracy. In all, 514 paired MD-CGM/arterial blood gas glucose values and 578 paired SC-CGM/arterial blood gas glucose values were obtained. Mean difference (SD) for the MD-CGM system was 0.9 (15.1) mg/dl and for the SC-CGM system -43.4 (20) mg/dl. ISO criteria (ISO15197:2013) were not met by either CGM system. In the Clarke error grid, all paired samples were within the zones AB for the MD-CGM system, and 94% in zone A. For the SC-CGM system, 99.1% of the paired samples were within zones AB, and 18.9% in zone A. Both the MD-CGM and the SC-CGM systems were reliable and used without complications. These results indicate that the Eirus intravascular microdialysis system monitors glucose continuously with superior accuracy compared to the FreeStyle Libre subcutaneous glucose monitoring system, which repeatedly measured a glucose value that was lower than the reference method.

Objective To compare the effect of the rapid-acting insulin analogues (RAIAs) aspart (NovoRapid) and lispro (Prandilin) on glycemic variations by continuous glucose monitoring system (CGMS) in patients within newly diagnosed type 2 diabetes mellitus (T2DM) receiving continuous subcutaneous insulin infusion (CSII) and metformin intensive therapy. Methods This is a single-blind randomized controlled trial. A total of 110 patients with newly diagnosed T2DM and with hemoglobin A1c (HbA1c%) above 9% was hospitalized and randomly divided into two groups: group Asp (NovoRapid group) and group Lis (Prandilin group). They all received CSII and metformin therapy. Treatments were maintained for 2-3 weeks after the glycaemic target was reached. C-peptide and insulin and fructosamine were determined. CGMS was continuously applied for 4 days after reaching the glycemic target. Results There were no significant differences in daily dosages of insulin, fasting plasma C-P and 2 h postprandial C-P and insulin, and fructosamine at the baseline and endpoint between the groups Asp and Lis. No significant differences were seen in the 24 h mean amplitude of glycemic excursions (MAGE), 24 h mean blood glucose (MBG), the standard deviation of the MBG (SDBG), fasting blood glucose, number of glycemic excursion (NGE), and the incidence of hypoglycemia between the two groups. Similarly, no significant differences were found in areas under the curve (AUC) of glucose above 10.0 mmol/L or the decremental area over the curve (AOC) of glucose below 3.9 mmol/L between the two groups. Conclusions Lispro and aspart had the similar ability to control the glycemic variations in patients with newly diagnosed T2DM. This study was registered with ClinicalTrials.gov, number ChiCTR-IPR-17010338.

Laboratory animals are extensively used in diabetic research. However, it is not known whether the glucose dynamics in laboratory animals are similar to the dynamics in humans. The aim of the present study is to see whether the Medtronic MiniMed continuous subcutaneous glucose monitoring system can be used to record fluctuations of the glucose level in freely moving normal and insulin-treated diabetic rats. The monitoring system was applied during 3 days to normal and diabetic hyperglycemic and hypoglycemic rats treated with insulin implants. Corresponding data from type 1 diabetic patients with poor glycemic control were selected retrospectively in order to note the similarities and differences. In normal rats the subcutaneous glucose level varied slightly (median = 111 mg/dL). In hyperglycemic rats the subcutaneous glucose values fluctuated markedly around a median of 226 mg/dL. The fluctuations formed a short-wave pattern with a low amplitude, superimposed on a long-wave pattern with a high amplitude. The subcutaneous glucose profile seen in type 1 diabetic patients (median = 180 mg/dL) was similar to that observed in hyperglycemic rats. In hypoglycemic rats, the subcutaneous glucose level fluctuated moderately around a median of 55 mg/dL. In these rats the fluctuations formed a short-wave pattern with low amplitude, without any obvious long-wave pattern. The subcutaneous glucose values conformed to corresponding blood glucose measurements. We conclude that the Medtronic MiniMed continuous glucose monitoring system can be used to record the subcutaneous glucose level over time in freely moving rats.

Continuous glucose monitoring may reveal episodes of unrecognized hypoglycaemia. We evaluated reproducibility and reliability of hypoglycaemic episodes recorded in daily life by the Medtronic MiniMed Continuous Glucose Monitoring System (CGMS). Twenty-nine adult patients with Type 1 diabetes underwent 6 days of continuous subcutaneous glucose monitoring, applying one CGMS on each side of the abdomen. Blood glucose was measured by HemoCue B-Glucose Analyzers six times daily and two different 4-point calibration sets were generated (set A and B). Using these calibration sets, CGMS raw data were recalibrated generating four different CGMS data sets [left-A (left side of abdomen, calibration set A), left-B, right-A and right-B]. Agreement between CGMS data sets was evaluated during hypoglycaemic events, comparing CGMS readings = 2.2 mmol/l with nadir values from corresponding CGMS data sets. CGMS readings were also compared with independent self-monitored blood glucose (SMBG) values. With hypoglycaemia (CGMS readings = 2.2 mmol/l) in calibration set left-A, values below 3.5 mmol/l were present in 99% (95% CI: 95-100%) of samples in left-B, 91% (95% CI: 84-96%) of samples in right-A, and 90% (95% CI: 83-95%) of samples in right B. In 84% of these episodes (95% CI: 59-96%) independent SMBG values were below 3.5 mmol/l. Difference in duration was observed with a median difference of 20 min; (left-A vs. right-B). Hypoglycaemic episodes recorded by CGMS are reproducible and agreement with independent SMBG values is acceptable for retrospective recording of hypoglycaemic events with CGMS.

Continuous, automated and non-invasive blood glucose monitoring systems have long been a goal to assist management of diabetes mellitus. The first continuous, albeit invasive, device available in Australia is the Medtronic MiniMed Continuous Glucose Monitoring System (CGMS), which is available for physician-supervised use to give a continuous blood glucose profile (5-minutely readings, viewable only after download by the physician) for periods of 72 h. With the availability of this technology, there is a need to assess the accuracy, reproducibility and ability to detect significant clinical events (particularly hypoglycaemia) and blood glucose patterns. The question of whether this technique allows long-term improvement of metabolic control also arises. We present four case studies to illustrate the use of CGMS in clinical practice and have reviewed the rapidly emerging literature. We conclude that CGMS is a useful clinical tool in the management of diabetes mellitus, provided that it is appropriately applied and the limitations are understood.

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.

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.

Diabetes Technology & TherapeuticsVol. 2, No. supplement 1 Orginal ArticlesContinuous Glucose Monitoring in Previously Unstudied Population SubgroupsTodd M. Gross and Anna ter VeerTodd M. GrossSearch for more papers by this author and Anna ter VeerSearch for more papers by this authorPublished Online:5 Jul 2004https://doi.org/10.1089/15209150050214096AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail FiguresReferencesRelatedDetailsCited byA Standard Approach to Continuous Glucose Monitor Data in Pregnancy for the Study of Fetal Growth and Infant Outcomes Teri L. Hernandez and Linda A. Barbour29 January 2013 | Diabetes Technology & Therapeutics, Vol. 15, No. 2Continuous Glucose Monitoring in Pregnancy: New Frontiers in Clinical Applications and Research1 November 2012 | Journal of Diabetes Science and Technology, Vol. 6, No. 6The Correlation and Accuracy of Glucose Levels between Interstitial Fluid and Venous Plasma by Continuous Glucose Monitoring SystemKorean Diabetes Journal, Vol. 34, No. 6Continuous Glucose Monitoring System in Free-Living Healthy Subjects: Results from a Pilot Study Giuseppe Derosa, Sibilla A.T. Salvadeo, Roberto Mereu, Angela D'Angelo, Leonardina Ciccarelli, Mario N. Piccinni, Ilaria Ferrari, Alessia Gravina, Pamela Maffioli, and Carmine Tinelli6 March 2009 | Diabetes Technology & Therapeutics, Vol. 11, No. 3Preclinical In Vivo Study of a Fluorescence Affinity Sensor for Short-Term Continuous Glucose Monitoring in a Small and Large Animal Model Ralph Dutt-Ballerstadt, Colton Evans, Ashok Gowda, and Roger McNichols13 September 2010 | Diabetes Technology & Therapeutics, Vol. 10, No. 6How to Assess and Compare the Accuracy of Continuous Glucose Monitors? I.M.E. Wentholt, A.A.M. Hart, J.B.L. Hoekstra, and J.H. DeVries8 February 2008 | Diabetes Technology & Therapeutics, Vol. 10, No. 2Future Management Approaches12 July 2013Accuracy of continuous nocturnal glucose monitoring after 48 and 72 hours in type 2 diabetes patients on combined oral and insulin therapyDiabetes & Metabolism, Vol. 30, No. 6Nocturnal hypoglycaemia in type 1 diabetes?consequences and assessment1 January 2004 | Diabetes/Metabolism Research and Reviews, Vol. 20, No. S2The Continuous Glucose Monitoring System During Pregnancy of Women with Type 1 Diabetes Mellitus: Accuracy Assessment Anneloes Kerssen, Harold W. De Valk, and Gerard H.A. Visser12 October 2004 | Diabetes Technology & Therapeutics, Vol. 6, No. 5The Public Health Impact of the MiniMed Continuous Glucose Monitoring System (CGMS®)—An Assessment of the Literature Dale R. Tavris and Azadeh Shoaibi25 August 2004 | Diabetes Technology & Therapeutics, Vol. 6, No. 4Experience with the Continuous Glucose Monitoring System® in a Medical Intensive Care Unit Philip A. Goldberg, Mark D. Siegel, Raymond R. Russell, Robert S. Sherwin, Joshua I. Halickman, Dawn A. Cooper, James D. Dziura, and Silvio E. Inzucchi5 July 2004 | Diabetes Technology & Therapeutics, Vol. 6, No. 3Glucose sensors: toward closed loop insulin deliveryEndocrinology and Metabolism Clinics of North America, Vol. 33, No. 1Enregistrement de la glycémie en continu : quelles retombées ?Annales d'Endocrinologie, Vol. 65Performance assessment of the Medtronic-MiniMed Continuous Glucose Monitoring System and its use for measurement of glycaemic control in Type 1 diabetic subjectsDiabetic Medicine, Vol. 20, No. 12The Accuracy of the CGMS™ in Children with Type 1 Diabetes: Results of the Diabetes Research in Children Network (DirecNet) Accuracy Study5 July 2004 | Diabetes Technology & Therapeutics, Vol. 5, No. 5Accuracy of the continuous glucose monitoring system in inpatient and outpatient conditionsDiabetes & Metabolism, Vol. 29, No. 2Clinical Performance of CGMS in Type 1 Diabetic Patients Treated by Continuous Subcutaneous Insulin Infusion Using Insulin AnalogsDiabetes Care, Vol. 26, No. 3Biosensors for in vivo glucose measurement: can we cross the experimental stageBiosensors and Bioelectronics, Vol. 17, No. 11-12Reproducibility of Glucose Measurements Using the Glucose SensorDiabetes Care, Vol. 25, No. 7Continuous Monitoring of the Subcutaneous Glucose Level in Freely Moving Normal and Diabetic Rats and in Humans with Type 1 Diabetes Reza Jamali, Johnny Ludvigsson, and Simin Mohseni5 July 2004 | Diabetes Technology & Therapeutics, Vol. 4, No. 3What's ahead in glucose monitoring?30 June 2015 | Postgraduate Medicine, Vol. 109, No. 4New technologies and therapeutic approaches for the management of pediatric diabetesCurrent Diabetes Reports, Vol. 1, No. 1 Volume 2Issue supplement 1Dec 2000 To cite this article:Todd M. Gross and Anna ter Veer.Continuous Glucose Monitoring in Previously Unstudied Population Subgroups.Diabetes Technology & Therapeutics.Dec 2000.27-34.http://doi.org/10.1089/15209150050214096Published in Volume: 2 Issue supplement 1: July 5, 2004PDF download

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.

Maternal hyperglycemia in gestational diabetes mellitus (GDM), especially hyperglycemic excursions, is associated with increased risks of adverse pregnancy outcomes. Continuous glucose monitoring (CGM) system (CGMS) is better than intermittent self-measurements in detecting detailed glucose profiles on the magnitude and duration of glucose fluctuations. Hyperglycemia resulted from impaired β cell function. This study analyzed the characteristics of glycemic variability in GDM with 24-28 gestational weeks and its association with β cell function. Thirty GDM with 24-28 gestational weeks (GDM group) were included in this study, and 20 normal gestational women (NGW group) and 20 normal glucose regulation non-pregnant women (NGRW group) were set as controls. The three groups were monitored using the CGMS for consecutive 72h. The parameters of glycemic variability included the standard deviation of blood glucose (SDBG), mean of continuous 24-h blood glucose (MBG), mean amplitude of glycemic excursions (MAGEs), and mean of daily differences (MODDs). Homeostasis model assessments were applied to access the insulin resistance (HOMA-IR). The early insulinogenic index (ΔI30/ΔG30) and the area under the curve of insulin (AUCI180) derived from 75-g oral glucose tolerance test were applied to evaluate the early-phase insulin secretion and second-phase insulin secretion, respectively. After CGM, MAGE and MBG value increased progressively from NGRW, NGW to GDM group (p<0.05); MODD and SDBG values of GDM group were all higher than those of NGRW and NGW groups (p<0.05), but there are no differences in MODD and SDBG between NGRW and NGW groups (p>0.05). After comparison of β cell function, ΔI30/ΔG30 decreased progressively from NGRW, NGW to GDM group (p<0.05); HOMA-IR and AUCI180 increased progressively from NGRW, NGW to GDM group (p<0.05). MAGE value was correlated with ΔI30/ΔG30 and HOMA-IR in GDM group (r=-0.78 and 0.65, respectively, p<0.05). Multiple linear stepwise regression analysis showed that ΔI30/ΔG30 and HOMA-IR were the independent factors of MAGE (β=-0.61, 0.34, respectively, p<0.05). Glycemic variability in GDM was higher than in normal pregnant women, and glycemic variability evaluated by MAGE correlates well with impaired early-phase insulin secretion in GDM. Further large-scale studies are needed to formulate treatment strategies to make up for the impaired early-phase insulin secretion and flat glycemic variability, and analyze the association between pregnancy outcomes improvement and glycemic variability remission in GDM.

Background There has been growing evidence that the glucose fluctuation is an important contributing factor to the development of coronary artery disease. However, whether large glucose fluctuation, especially hypoglycemia, may be associated with acute myocardial infarction (AMI) remains largely unknown. Aim As new continuous glucose monitoring (CGM) has recently become available to evaluate glucose fluctuation from immediately after an emergency visit, this study sought to investigate glucose fluctuation and the occurrence of hypoglycemia in patients with AMI. Methods In this prospective study, 93 consecutive patients with AMI from April 2017 to November 2018 were enrolled. Subcutaneous interstitial glucose levels were monitored from emergency room to discharge using the CGM System. Based on the CGM data, 24-h mean glucose levels, the time in hyperglycemia and hypoglycemia and the occurrence of hypoglycemia, defined as less than 70 mg/dL, were measured, and the mean amplitude of glycemic excursions (MAGE) were calculated. Results The majority of patients [n=57, 61% (non-DM)] did not have diabetes and 36 patients had diabetes (DM). The occurrence of hypoglycemia within 24 hours after admission was observed in 49 patients [DM: n=11 (30.6%), non-DM: n=38 (66.7%)]. MAGE within 24 hours after admission were 100±47 in DM patients and 67±20 in non-DM patients. The mean time in hypoglycemia within 24 hours after admission was 148 minutes [DM: 100±260 minutes, non-DM: 178±287 minutes]. The occurrence of hypoglycemia during a hospital stay (mean 11.5 days) was detected in 76 patients [DM: n=28 (77.8%), non-DM: n=48 (84.2%)]. Representative case of hypoglycemia Conclusion Not only in DM patients but also in non-DM patients with AMI, large glucose fluctuation and high incidence of hypoglycemia were observed using new CGM system. Further investigations should address the rationale for the early detection and control of glucose fluctuation for AMI patients.

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 &amp; 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.

Performance characterization of an abiotic and fluorescent-based continuous glucose monitoring system in patients with type 1 diabetes

Hypoglycemia can be a symptom in patients with Addison's disease. The common regimen of replacement therapy with oral glucocorticoids results in unphysiological low cortisol levels in the early morning, the time of highest insulin sensitivity. Therefore patients with Addison's disease are at risk for unrecognized and potentially severe nocturnal hypoglycemia also because of a disturbed counterregulatory function. Use of a continuous glucose monitoring system (CGMS) could help to adjust hydrocortisone treatment and to avoid nocturnal hypoglycemia in these patients. Thirteen patients with Addison's disease were screened for hypoglycemia wearing a CGMS for 3-5 days. In one patient we identified a hypoglycemic episode at 3:45 a.m. with a blood glucose level of 46 mg/dL, clearly beneath the 95% tolerance interval of minimal glucose levels between 2 and 4 a.m. (53.84 mg/dL). After the hydrocortisone replacement scheme was changed, the minimum blood glucose level between 2 and 4 a.m. normalized to 87 mg/dL. Continuous glucose monitoring can detect nocturnal hypoglycemia in patients with primary adrenal insufficiency and hence prevent in these patients an impaired quality of life and even serious adverse effects.

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 &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. 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.