Real-World Safety of an Implantable Continuous Glucose Sensor Over Multiple Cycles of Use: A Post-Market Registry Study.

Previously, the safety and accuracy of the Eversense continuous glucose monitoring (CGM) system were characterized in three pivotal trials among individuals with type 1 diabetes (T1D) and type 2 diabetes (T2D) with a single 90- or 180-day sensor insertion-removal cycle. The Post-Market Clinical Follow-up (PMCF) registry is a prospective study evaluating the long-term safety and performance of the Eversense CGM system over multiple sensor insertion-removal cycles among adults with T1D and T2D. All patients who had a sensor subcutaneously implanted across 534 participating centers in Europe and South Africa from June 2016 to August 2018 were enrolled. Adverse events (AEs) were recorded at each visit and patients were instructed to inform their clinic if they experienced any AEs between visits. AEs were adjudicated for relatedness to the device, procedure, or drug (dexamethasone acetate). The primary safety endpoint was the rate of related serious adverse events (SAEs) through four sensor insertion-removal cycles. The registry enrolled 3023 patients. As of last follow-up, 5417 sensors had been inserted with a total of 1260 patient-years (PYs) of follow-up: 969 patients had used the system for at least 6 months and 173 patients had used the system for at least 1 year. No related SAEs were reported. The most frequently reported related AEs were sensor location site infection (0.96%; 2.46 events per 100 PYs), inability to remove the sensor upon first attempt (0.76%; 1.90 events per 100 PYs), and adhesive patch location site irritation (0.66%; 1.59 events per 100 PYs). One nonserious allergic reaction to lidocaine was reported, which resolved with administration of an antihistamine. The full intended sensor life was achieved by 91% of 90-day sensors and 75% of 180-day sensors. The PMCF registry provides real-world evidence that the Eversense CGM system is safe over multiple cycles of use.

Longitudinal Analysis of Real-World Performance of an Implantable Continuous Glucose Sensor over Multiple Sensor Insertion and Removal Cycles.

The Eversense® Continuous Glucose Monitoring (CGM) System, with the first long-term, implantable glucose sensor, has been commercially available in Europe and South Africa since 2016 for adults with diabetes. The performance of the sensor over multiple, sequential 90- or 180-day cycles from either real-world experience or clinical studies has not been previously published. The Eversense Data Management System (DMS) was used to evaluate the accuracy of General Data Protection Regulation (GDPR)-compliant sensor glucose (SG) values against self-monitoring of blood glucose (SMBG) from June 2016 through August 2019 among patients with at least four sensor cycles from European and South African health care practices. Mean SG and associated measures of variability, glucose management indicator (GMI), and percent and time in various hypoglycemic, euglycemic, and hyperglycemic ranges were calculated for the 24-h time period over each cycle. In addition, transmitter wear time was evaluated across each sensor wear cycle. Among the 945 users included in the analysis, the mean absolute relative difference (standard deviation [SD]) using 152,206, 174,645, 206,024, and 172,587 calibration matched pairs against SMBG was 11.9% (3.6%), 11.5% (4.0%), 11.8% (4.7%), and 11.5% (4.1%) during the first four sensor cycles, respectively. Mean values of the CGM metrics over the first sensor cycle were 156.5 mg/dL for SG, 54.7 mg/dL for SD, 0.35 for coefficient of variation, and 7.04% for GMI. Percent SG at different glycemic ranges was as follows: <54 mg/dL was 1.1% (16 min), <70 mg/dL was 4.6% (66 min), ≥70-180 mg/dL (time in range) was 64.5% (929 min), >180-250 mg/dL was 22.8% (328 min), and >250 mg/dL was 8.1% (117 min). The median transmitter wear time over the first cycle was 83.2%. CGM metrics and wear time were similar over the subsequent three cycles. This real-world evaluation of adult patients with diabetes using the Eversense CGM System in the home setting demonstrated that the implantable sensor provides consistent stable accuracy and CGM metrics over multiple, sequential sensor cycles with no indication of degradation of sensor performance.

Clinical Practice Recommendations on the Routine Use of Eversense, the First Long-Term Implantable Continuous Glucose Monitoring System.

Background: The use of real-time continuous glucose monitoring (rtCGM) systems has proved to positively impact the management of type 1 diabetes with the potential to lower HbA1c, reduce frequency and time spent in hypoglycemia, and lower glycemic variability. Nevertheless, the acceptance of rtCGM remains below expectations and the dropout rate within the first year has been reported to be 27%. Besides financial reasons due to limited reimbursement, reasons include the need for frequent sensor replacement, the discomfort of wearing a sensor, the presence of adverse skin reactions, or privacy. Thus, novel approaches to rtCGM are desired to overcome these barriers. The first long-term implantable rtCGM system diversifies the field of glucose monitoring further. However, due to its novelty, there are no published clinical practice guidelines available. Aims: The aim of this article is to set the foundation for a best clinical practice for the everyday clinical care using a long-term implantable CGM system. Methods: An international expert panel for the long-term implantable CGM system developed this best practice guidance. All participants were certified and experienced in the use of the Eversense® long-term implantable CGM system. The workflows from the respective clinics were presented, discussed and are summarized in an ideal care workflow outlined in these practice recommendations. Results: The participants agreed on the following aspects: definition of the patient population that will benefit from a long-term implantable CGM device; real-world experience on safety and accuracy of a long-term CGM; definition of the ideal sensor position; description of the optimal process for sensor insertion, removal, and replacement.

Therapy Adjustments Based on Trend Arrows Using Continuous Glucose Monitoring Systems.

Continuous glucose monitoring (CGM) systems use trend arrows to accurately display the anticipated glucose curve for the user. These are used for both "real-time" glucose monitoring and for intermittent scanning glucose monitoring. Trend arrow data are used by people with diabetes to make corrections to their glucose control. It is essential that they are correctly interpreted when adjusting insulin doses and to ensure that appropriate treatment decisions are made. The aim of this article is to provide general treatment guidance for diabetes teams and for people with diabetes using CGM in the context of trend arrows. This is based on previous recommendations for interpreting trend arrows without losing sight of the need for individual therapy adjustment.

Insulin Infusion Set Use: European Perspectives and Recommendations.

Insulin pump users worldwide depend on insulin infusion sets (IISs) for predictable delivery of insulin to the subcutaneous tissue. Yet emerging data indicates that IISs are associated with many pump-related adverse events and may contribute to potentially life-threatening problem of unexplained hyperglycemia. The relative scarcity of published research on IISs to date, the heterogeneity of regional IIS practices, and the increasing demand for international standards guiding their use prompted convening of a panel of diabetologists and diabetes nurse educators last February, in Milan, Italy, to discuss a framework for optimizing IIS practice in Europe. The multinational panel was tasked, first, with identifying the often-overlooked IIS issues that can affect patients' experience of pump therapy-e.g., partial or complete blockage of the cannula, skin pathologies, unpredictable variations in insulin absorption, dislodgment, and the demands of site rotation and set changes-and, second, with establishing direction for developing cohesive protocols to assure long-term success. As reported in this article, the panel examined IIS-related complications of pump therapy encountered in clinical practice, considered country-wide policies to prevent and mitigate such complications, and updated priorities for improving IIS education on issues of device selection, skin care, and troubleshooting unexplained hyperglycemia. These recommendations may be more relevant with the possibility of closed-loop systems available in the near future.

HypoDE: Research Design and Methods of a Randomized Controlled Study Evaluating the Impact of Real-Time CGM Usage on the Frequency of CGM Glucose Values <55 mg/dl in Patients With Type 1 Diabetes and Problematic Hypoglycemia Treated With Multiple Daily Injections.

Systems for continuous glucose monitoring (CGM) have been available for a number of years, and numerous clinical studies have been performed with them. Interestingly, in many of these studies patients with an increased risk of hypoglycemic events were excluded. In addition, in most studies subjects were using a pump for insulin delivery. Therefore our knowledge about the benefit of CGM in patients employing multiple daily injections (MDI) of insulin is limited, especially when it comes to a reduction in the risk of low glucose events in high-risk individuals. We are planning to run a 26-week randomized controlled study in Germany (HypoDE, Hypoglycemia in Deutschland) that is focused on evaluating if such a reduction can be observed in patients on MDI with an increased risk of low glucose events. In all, 160 patients will participate in the study, randomized into the intervention group and control group. Ideally one would study if the frequency of severe hypoglycemic events is different between both groups. However, this would require such a large sample size and study duration, so for pragmatic reasons we will use low glucose levels <55 mg/dl (measured by CGM) for at least 20 minutes as a risk marker for severe hypoglycemic events. The results from the HypoDE study shall help determine the advantage of using CGM in subjects with type 1 diabetes with an increased risk of low glucose events treated with MDI.

Recessive mutations in the INS gene result in neonatal diabetes through reduced insulin biosynthesis.

Heterozygous coding mutations in the INS gene that encodes preproinsulin were recently shown to be an important cause of permanent neonatal diabetes. These dominantly acting mutations prevent normal folding of proinsulin, which leads to beta-cell death through endoplasmic reticulum stress and apoptosis. We now report 10 different recessive INS mutations in 15 probands with neonatal diabetes. Functional studies showed that recessive mutations resulted in diabetes because of decreased insulin biosynthesis through distinct mechanisms, including gene deletion, lack of the translation initiation signal, and altered mRNA stability because of the disruption of a polyadenylation signal. A subset of recessive mutations caused abnormal INS transcription, including the deletion of the C1 and E1 cis regulatory elements, or three different single base-pair substitutions in a CC dinucleotide sequence located between E1 and A1 elements. In keeping with an earlier and more severe beta-cell defect, patients with recessive INS mutations had a lower birth weight (-3.2 SD score vs. -2.0 SD score) and were diagnosed earlier (median 1 week vs. 10 weeks) compared to those with dominant INS mutations. Mutations in the insulin gene can therefore result in neonatal diabetes as a result of two contrasting pathogenic mechanisms. Moreover, the recessively inherited mutations provide a genetic demonstration of the essential role of multiple sequence elements that regulate the biosynthesis of insulin in man.

Intensive Care Unit Insulin Delivery Algorithms: Why So Many? How to Choose?

OBJECTIVE: Studies showing improved outcomes with tight glycemic control in the intensive care unit (ICU) have resulted in a substantial number of new insulin delivery algorithms being proposed. The present study highlights mechanisms used in the better-known approaches, examines what might be critical differences among them, and uses systems theory to characterize the conditions under which each can be expected to perform best. METHODS: Algorithm dose (DeltaI/DeltaG) and step (response to a persistent elevation in glucose) response curves were calculated for written instruction algorithms, developed at the Providence Heart and Vascular Institute (Portland [P] protocol), the University of Washington (UW), and Yale University (Y), together with similar curves for the Glucommander (GM) and proportional integral derivative (PID) computer algorithms. From the simulated curves, different mechanisms used to adjust insulin delivery were identified. RESULTS: All algorithms increased insulin delivery in response to persistent hyperglycemia, but the mechanism used altered the algorithm's sensitivity to glucose, or gain, in the GM, UW, and Y protocols, while leaving it unchanged for the P protocol and PID algorithm. CONCLUSIONS: The increase in insulin delivery in response to persistent hyperglycemia observed with all the algorithms can be expected to bring subjects who respond to insulin to targeted glucose ranges. However, because the PID and P protocols did not alter the insulin delivery response curves, these algorithms can be expected to take longer to achieve target glucose levels in individuals who are insulin resistant and/or are exposed to increased carbohydrate loads (e.g., glucose infusions). By contrast, the GM, UW, and Y algorithms can be expected to adapt to the insulin resistance such that the time to achieve target levels is unchanged if the time for insulin to act does not change. If the insulin resistance is accompanied by a longer time for insulin to act, the UW, Y, and GM algorithms may increase the risk of hypoglycemia. Under these conditions, the longer time required for the PID and P protocols to achieve a target glucose level may be a reasonable trade-off for no increase in the risk of hypoglycemia.

Expanded clinical spectrum in hepatocyte nuclear factor 1b-maturity-onset diabetes of the young.

AIMS: HNF1B-maturity-onset diabetes of the young is caused by abnormalities in the HNF1B gene encoding the transcription factor HNF-1beta. We aimed to investigate detailed clinical features and the type of HNF1B gene anomaly in five pediatric cases with HNF1B-MODY. METHODS: From a cohort of 995 children and adolescents with diabetes, we analyzed the most frequent maturity-onset diabetes of the young genes (GCK, HNF1A, HNF4A) including HNF1B sequencing and deletion analysis by quantitative Multiplex-PCR of Short Fluorescent Fragments (QMPSF) if patients were islet autoantibody-negative and had one parent with diabetes or associated extrapancreatic features or detectable C-peptide outside honeymoon phase. Presence and size of disease-causing chromosomal rearrangements detected by QMPSF were further analyzed by array comparative genomic hybridization. RESULTS: Overall, five patients had a heterozygous HNF1B deletion, presenting renal disease, elevated liver enzymes, and diabetes. Diabetes was characterized by insulin resistance and adolescent onset of hyperglycemia. Additionally, clinical features in some patients were pancreas dysplasia and exocrine insufficiency (two of five patients), genital defects (three of five), mental retardation (two of five), and eye abnormalities (coloboma, cataract in two of five). One case also had severe growth deficit combined with congenital cholestasis, and another case had common variable immune deficiency. All patients reported here had monoallelic loss of the entire HNF1B gene. Whole genome array comparative genomic hybridization confirmed a precurrent genomic deletion of approximately 1.3-1.7 Mb in size. CONCLUSION: The clinical data of our cases enlarge the wide spectrum of patients with HNF1B anomaly. The underlying molecular defect in all cases was a 1.3- to 1.7-Mb deletion, and paired, segmental duplications along with breakpoints were most likely involved in this recurrent chromosomal microdeletion.

Clinical heterogeneity in patients with FOXP3 mutations presenting with permanent neonatal diabetes.

OBJECTIVE: Immune dysregulation, polyendocrinopathy, enteropathy, X-linked (IPEX) syndrome is caused by FOXP3 mutations. We aimed to determine the prevalence, genetics, and clinical phenotype of FOXP3 mutations in a large cohort with permanent neonatal diabetes (PNDM). RESEARCH DESIGN AND METHODS: The 11 coding exons and the polyadenylation region of FOXP3 were sequenced in 26 male subjects with diabetes diagnosed before 6 months of age in whom common genetic causes of PNDM had been excluded. Ten subjects had at least one additional immune-related disorder, and the remaining 16 had isolated diabetes. RESULTS: We identified four hemizygous FOXP3 mutations in 6 of 10 patients with associated immune-related disorders and in 0 of 16 patients with isolated diabetes (P = 0.002). Three patients with two novel mutations (R337Q and P339A) and the previously reported L76QfsX53 developed classic IPEX syndrome and died within the first 13 months. The novel mutation V408M was found in three patients from two unrelated families and had a mild phenotype with hypothyroidism and autoimmune enteropathy (n = 2) or nephrotic syndrome (n = 1) and survival to 12-15 years. CONCLUSIONS: FOXP3 mutations result in approximately 4% of cases of male patients with permanent diabetes diagnosed before 6 months. Patients not only have classic IPEX syndrome but, unexpectedly, may have a more benign phenotype. FOXP3 sequencing should be performed in any male patient with the diagnosis of diabetes in the first 6 months who develops other possible autoimmune-associated conditions, even in the absence of full IPEX syndrome.

Glucose control in pediatric intensive care unit patients using an insulin-glucose algorithm.

BACKGROUND: Control of hyperglycemia in adult medical and surgical intensive care units (ICUs) has been shown to dramatically decrease morbidity and mortality. Algorithms to achieve glycemic control in the ICU setting are evolving. We have evaluated the use of a discrete proportional-integral-derivative (PID) algorithm to control hyperglycemia in pediatric ICU (PICU) patients both with and without diabetes. METHODS: Six PICU patients [four with diabetic ketoacidosis (DKA) and two with glucocorticoid-induced hyperglycemia] with glucose values >150 mg/dL were enrolled. Their hyperglycemia was managed with a PID algorithm that provided recommendations for both changes in the intravenous insulin infusion rate and the time to obtain the next discrete glucose value. Glucose targets were adjusted based on clinical circumstances. RESULTS: Patients (mean age 9.2 years; range 1.8-14 years) utilized the algorithm for a total of 454.4 h. Mean time to the initial glucose target was 8.7 h (range 1.3-15.1 h) in five patients. One subject with hyperosmolar DKA did not achieve target before discharge from the PICU, and another was at target when the algorithm was initiated. After the glucose target was achieved, the mean SD was 23.5 mg/dL, and glucose values were >40 mg/dL above target 13% of the time and <40 mg/dL below target 1% of the time. There were no glucose values <55 mg/dL. CONCLUSION: The PID algorithm safely and effectively controlled hyperglycemia in a PICU, despite multiple changes in intravenous fluids, steroid doses (including high-dose pulses), and hemodialysis.

Treatment with insulin glargine reduces asymptomatic hypoglycemia detected by continuous subcutaneous glucose monitoring in children and adolescents with type 1 diabetes.

OBJECTIVE: Unsatisfactory basal insulin substitution may lead to asymptomatic hypoglycemia in children and adolescents with type 1 diabetes (T1D). To investigate the effects of multiple daily injections before and after changing to insulin glargine (IG), continuous glucose monitoring system (CGMS) data were used to analyze glycemic control and hypoglycemic episodes during the two different therapy regimens. METHODS: Basal insulin therapy was changed to one daily injection of IG in 30 pediatric patients with T1D (14 boys and 16 girls; age 4.5-18.3 yr, median 14.2 yr; diabetes duration 0.5-15.6 yr, median 4.6 yr) having elevated fasting glucose or recurrent hypoglycemia despite treatment with multiple injection therapy (basal insulin: two to four injections of neutral protamine Hagedorn (NPH) and/or zinc lente insulin). Ambulatory CGMS was applied before and 6-8 wk after treatment change. Frequency of hypoglycemic and hyperglycemic episodes, glucose area under the curve (AUC), and time below 60 mg/dL and above 180 mg/dL, respectively, were calculated from CGMS data during the day (8:00-22:00 hours) and at night (22:00-8:00 hours). RESULTS: Nocturnal hypoglycemia was detected by CGMS in 20 patients before and in 12 patients after the change to IG (p = .039), whereas both, the number of nocturnal and diurnal hypoglycemic episodes, decreased not significantly from 41 to 36 (p = .758) and 48 to 28 (p = .055), respectively. AUC and time below 60 mg/dL as well as hemoglobin A1c (HbA1c) were not significantly different before and after the change to IG. CONCLUSION: Under treatment with IG, asymptomatic hypoglycemia was reduced without increase of HbA1c.

Assessment of glycemic control by continuous glucose monitoring system in 50 children with type 1 diabetes starting on insulin pump therapy.

OBJECTIVE: To report experience with a continuous glucose monitoring system (CGMS) and to identify factors influencing glycemic control in a large cohort of children and adolescents with type 1 diabetes and change to insulin pump therapy via continuous subcutaneous insulin infusion (CSII). RESEARCH DESIGN AND METHODS: In 50 patients [21 boys, 29 girls; median age 12.6 yr (range: 1.3-16.4 yr); diabetes duration 5.0 yr (0.2-13.3)], hemoglobin A1c (HbA1c) and ambulatory CGMS were performed before and 6 wk after starting CSII. Average glucose concentration per 24 h, during day and night time as well as number of excursions, duration, and area under the curve (AUC) of glucose values above 180 mg/dL and below 60 mg/dL were calculated from CGMS data. Simultaneously, metabolic control was documented by standardized self-monitoring of blood glucose (SMBG). RESULTS: In the total cohort, HbA1c improved from 8.1 +/- 1.2% at baseline to 7.7 +/- 0.9% after 6 wk of CSII (p <0.001). This effect was more distinct in boys (8.0 +/- 1.4 vs. 7.5 +/- 1.1%, p=0.007) than in girls (8.1 +/- 1.1 vs. 7.8 +/- 0.7%, p=0.039) as well as in patients with poor glycemic control (HbA1c >8.0%) at baseline (8.9 +/- 0.6 vs. 8.1 +/- 0.8%, p <0.001) and in those older than 12 yr (8.2 +/- 1.2 vs. 7.7 +/- 1.0%, p <0.001). At 6 wk of CSII, the values of glucose average per 24 h, AUC and time above 180 mg/dL, particularly during the day, improved. HbA1c was correlated with AUC above 180 mg/dL (r=0.742, p <0.001) and CGMS average glucose per 24 h (r=0.628, p=0.002), but to a lesser extent with SMBG values (r=0.418, p=0.054). CONCLUSION: With the change to CSII, HbA1c improved significantly after 6 wk of therapy. CGMS usage provided additional information about glycemic control in these patients.