Insulin Delivery System Research Articles

Precision medicine in type 1 diabetes: comparing metabolic outcomes of Control-IQ and MiniMed 780G according to patient characteristics.

This study aimed to compare 12-month metabolic outcomes in patients with type 1 diabetes (T1D) treated with either MiniMed 780G (Guardian 4) or Control-IQ (Dexcom G6) automated insulin delivery (AID) systems and identify interaction with patient characteristics. We conducted a single-centre, retrospective study including all patients (aged ≥16) with T1D who were started on either MiniMed 780G or Control-IQ between January 2021 and October 2022 and continued for ≥12 months. We used propensity score matching to compare the average marginal effects between MiniMed 780G and Control-IQ regarding the primary outcome (time in range [TIR]) and secondary outcomes (time below range [TBR], glucose monitoring indicator [GMI] and coefficient of variation [CV]) after 12 months. We tested for interaction effects between baseline characteristics (age, sex, socio-professional background, body mass index, insulin daily dose, carbohydrate counting practice) and treatment effect. We included 245 patients (58% women): 178 treated with Control-IQ and 67 with MiniMed 780G. The mean ± SD age and haemoglobin A1c were 39 ± 15 years and 8.7 ± 1.8% (72 ± 20 mmol/mol) respectively. In the propensity score-matched sample (n = 221), we observed significant differences in 12-month TIR (MiniMed 780G minus Control-IQ [95% CI]: 6.4 [3.4;9.5]), GMI (-0.42 [-0.59; -0.25]) and CV (-2.12 [-3.68; -0.55]), while TBR showed no significant difference (-0.04 [-0.47; +0.40]). The 12-month TIR difference was consistent across subgroups, including baseline carbohydrate counting characteristics. MiniMed 780G is associated with moderate metabolic superiority compared to Control-IQ, without interaction with patient characteristics. These results suggest that neither model is more appropriate for certain populations, particularly patients without carbohydrate counting practice.

Biotechnology Revolution Shaping the Future of Diabetes Management

Introduction: Diabetes mellitus (DM) has a millennia-long history, with early references dating back to ancient Egypt and India. However, it was not until the 20th century that the connection between diabetes and insulin was fully understood. The sequencing of insulin in the 1950s initiated the convergence of biotechnology and diabetes management, leading to the development of recombinant human insulin in 1982. This marked the start of peptide-based therapies in DM. Recombinant peptides for DM treatment: Numerous recombinant peptides have been developed since, starting with modified insulin molecules, with the aim of bettering DM management through fine-tuning the glycemic response to insulin. Peptide-based therapies in DM have expanded substantially beyond insulin to include agonists of Glucagon-like peptide-1 receptor and Glucose-dependent insulinotropic polypeptide receptor, glucagon receptor antagonists, and even peptides exerting multiple receptor agonist effects, for better metabolic control. Insulin pumps, continuous glucose monitoring, and automated insulin delivery systems: The development of modern delivery systems combined with real-time glucose monitoring has significantly advanced diabetes care. Insulin pumps evolved from early large devices to modern sensor-augmented pumps with automated shutoff features and hybrid closed-loop systems, requiring minimal user input. The second-generation systems have demonstrated superior outcomes, proving highly effective in diabetes management. Islet cell transplantation, organoids, and biological pancreas augmentation represent innovative approaches to diabetes management. Islet cell transplantation aims to restore insulin production by transplanting donor beta cells, though challenges persist regarding graft survival and the need for immunosuppression. Organoids are a promising platform for generating insulin-producing cells, although far from clinical use. Biological pancreas augmentation relies on therapies that promote beta-cell (re)generation, reduce stress, and induce immune tolerance. Further biotechnology-driven perspectives in DM will include metabolic control via biotechnology-enabled tools such as custom-designed insulin hybrid molecules, machine-learning algorithms to control peptide release, and engineering cells for optimal peptide production and secretion.

A Randomized Trial Comparing Inhaled Insulin Plus Basal Insulin Versus Usual Care in Adults With Type 1 Diabetes.

To evaluate a regimen of inhaled Technosphere insulin (TI) plus insulin degludec in adults with type 1 diabetes, who prestudy were predominately using either an automated insulin delivery (AID) system or multiple daily insulin injections (MDI) with continuous glucose monitoring. At 19 sites, adults with type 1 diabetes were randomly assigned to TI plus insulin degludec (N = 62) or usual care (UC) with continuation of prestudy insulin delivery method (N = 61) for 17 weeks. Prestudy, AID was used by 48% and MDI by 45%. Mean ± SD HbA1c was 7.57% ± 0.97% at baseline and 7.62% ± 1.06% at 17 weeks in the TI group and 7.59% ± 0.80% and 7.54% ± 0.77%, respectively, in the UC group (adjusted difference 0.11%, 95% CI -0.10 to 0.33, P value for noninferiority = 0.01). HbA1c improved from baseline to 17 weeks by >0.5% (5.5 mmol/mol) in 12 (21%) in the TI group and in 3 (5%) in the UC group and worsened by >0.5% (5.5 mmol/mol) in 15 (26%) in the TI group and in 2 (3%) in the UC group. The most common TI side effect was a brief cough; eight participants discontinued TI due to side effects. In adults with type 1 diabetes, HbA1c after 17 weeks with a regimen of TI and degludec was noninferior to UC, which consisted predominately of either AID or MDI. TI should be considered an option for people with type 1 diabetes, particularly those who are motivated to further reduce postprandial hyperglycemia.

The DERMIS Study: Methodologies, Results, and Implications for the Future.

Ongoing innovation in diabetes technologies has led to the development of advanced tools such as automated insulin delivery (AID) systems that adjust insulin delivery in response to current and predicted glucose levels, residual insulin action, and other inputs (eg, meal and exercise announcements). However, infusion sets continue to be the "Achilles heel" of accurate and precise insulin delivery and continued device use. A recent study by Kalus et al (DERMIS Study) revealed higher vessel density and signals of inflammation by optical coherence tomography (OCT), in addition to increased inflammation, fat necrosis, fibrosis, and eosinophilic infiltration by histopathology. Although the study provided a comprehensive description of what was happening, the results raise important questions that require additional research. On February 29, 2024, the Leona M. and Harry B. Helmsley Charitable Trust sponsored a conference to begin addressing these issues. This article summarizes the DERMIS study findings and testing methodologies discussed at the conference and proposes the next steps for developing insulin infusion sets that reduce the variability in insulin delivery and extend wear.

Toward Automation: The Road Traveled and Road Ahead for Integrating Automated Insulin Delivery into Inpatient Care.

The introduction of automated insulin delivery (AID) systems represents a significant advancement in diabetes care, offering substantial benefits in outpatient settings. Although clinical studies suggest that these systems can also help improve glycemic control in acutely ill patients, several barriers remain for the actual implementation and use of these technologies in clinical practice. Three main contexts for inpatient use are addressed, including: (a) continuation of personal AID systems, (b) initiation of AID during hospitalization, and (c) initiation of AID systems at discharge. A research road map with immediate to long-term actions is presented. Initially, it calls for clinical studies assessing in-hospital efficacy, safety, and utility, addressing specific patient needs and health care operational impacts. Midterm, it focuses on practical integration, simplifying AID use, ensuring electronic health record compatibility, clarifying regulatory uncertainties, and supporting health care professionals and patients. Long-term goals include system optimizations and policy advocacy for in-hospital AID use.

Changes in glucose variability and diabetes control in children and young adults with type 1 diabetes on routine continuous glucose monitoring and continuous subcutaneous insulin therapy following a switch to hybrid closed-loop therapy (MiniMed 780G) – retrospective study

IntroductionAdvanced hybrid closed loop (AHCL) insulin delivery systems offer considerable benefits to individuals with type 1 diabetes (T1D) in terms of glucose control and quality of life. With increasing numbers of regular users, real-life long-term data on long-term AHCL effectiveness become available.Material and methodsThis was a single-centre retrospective study. We included children and young adults (age 5–25 years ) with established T1D (≥ 3 m) who started MiniMed780G therapy between January 2021 and April 2022. We excluded those naïve to continuous glucose monitoring (CGM) or insulin pumps, as well as those without good-quality baseline CGM data. Included patients were followed for 12 months, with CGM and pump data retrieved from 14-day periods before transition and 3, 6, 9, and 12 months following the start of automode. Clinical data (body weight, height, glycated haemoglobin concentration) were recorded from the most recent outpatient visits.ResultsAmong 81 patients who started AHCL therapy, 46 met the criteria for analysis (mean age 11.5 ±4.4 years, diabetes duration 4.4 ±3.6 years, mean glycated haemoglobin 7.0 ±1.0%). Over the year following transition, we noted a significant improvement in time in target range 70–180 mg/dl (TIR, baseline: 69.1 ±12.0% to 12 m: 76.9 ±8.5%, <i>p</i> < 0.0001) and time in tight range 70–140 mg/dl (baseline: 45.3 ±14.2% to 12 m: 53.3 ±10.4%, <i>p</i> < 0.0001). Time below target range 70 mg/dl (TBR70 mg/dl) decreased significantly for 24-hour records (<i>p</i> = 0.0020). Importantly, those improvements were not accompanied by an increase in daily dose of insulin or body mass index.ConclusionsA prolonged 12-month-long observation in a routine care setting demonstrates that for young CGM- and pump users with T1D, switch AHCL offers sustained benefits in glucose variability.

The SMHP™ position statement on therapeutic carbohydrate reduction for type 1 diabetes

This article presents the position of the Society of Metabolic Health Practitioners (SMHP) regarding therapeutic carbohydrate reduction (TCR) nutrition interventions for type 1 diabetes mellitus (T1DM). A modified Delphi methodology was used to arrive at a consensus consisting of several focus groups, multiple rounds, and an anonymous survey. The field of endocrinology has seen many new advances for the treatment of T1DM including hybrid closed-loop insulin delivery systems and continuous glucose monitors for better glycaemic control, monoclonal antibodies to delay the onset of disease and increased access to paediatric endocrinologists, among many other noteworthy achievements. Despite these advancements, standard of care approaches to T1DM result in higher than acceptable morbidity and mortality, with a high prevalence of microvascular and macrovascular complications. Insulin resistance in type 1 diabetes is an independent risk factor for adverse outcomes even in well controlled type 1 diabetes. In 2021, only 21% of adults with T1DM in the United States achieved the American Diabetes Association’s (ADA’s) target haemoglobin A1C goal of 7.0%, while data in the paediatric and adolescent population have demonstrated worse glycaemic control. Supported by observational and interventional evidence, the SMHP advocates for the reevaluation of the prevailing nutritional therapy for T1DM with more broad consideration for TCR. The SMHP recommends open access and clinical support for TCR nutrition interventions for individuals with T1DM of all ages and calls upon the medical community to help foster more attention and research on TCR for T1DM.

Automated insulin delivery systems for the management of insulin therapy in post-transplant diabetes mellitus: a case series from a single center population.

Automated insulin delivery systems for the management of insulin therapy in post-transplant diabetes mellitus: a case series from a single center population.

Is low-dose glucagon needed and effective in preventing fasted exercise-induced hypoglycaemia in type 1 diabetes treated with the MiniMed 780G, an automated insulin delivery system?

To evaluate and compare the plasma glucose (PG) response during spontaneous fasted morning moderate-intensity exercise with and without injection of subcutaneous glucagon in adults with type 1 diabetes (T1D) treated with an automated insulin delivery (AID) system. Ten adults (four female) with T1D (age 50 [42-67] years, diabetes duration: 22 [14-44] years, HbA1c: 55 [47-69] mmol/mol) treated with the MiniMed™ 780G AID system participated in a proof-of-concept two-period, crossover trial. Fasting participants undertook a 45 min bout of continuous moderate-intensity (~60% V̇O2peak) exercise on a cycle ergometer followed by 1 h of rest. Before exercise, 150-μg glucagon was administered subcutaneously on visit 1 (GLUC) but not on visit 2 (NO-GLUC). Temporary target on the AID was activated 15 min before until 15 min after exercise cessation. Blood samples were taken at 5- and 15-min intervals for measuring PG and biomarkers. Data were analysed using paired t tests or repeated measures ANOVA. Time in range (3.9-10.0 mmol/L) was 100% on both study visits. No hypoglycaemia (<3.9 mmol/L) occurred in either arm. The GLUC arm had significantly higher mean PG (p = 0.01), area under the PG curve (p = 0.01), coefficient of variation (p < 0.01), peak PG (p = 0.01) and PG at the end of exercise (p < 0.01). No differences in endogenous glucoregulatory hormones were observed between visits. Adults with T1D treated with the MiniMed™ 780G can perform spontaneous fasted moderate-intensity exercise without hypoglycaemia. Therefore, glucagon was not needed for prevention of hypoglycaemia in such situations.

Results of an Australian trial of an automated insulin delivery (AID) system and other studies support likely benefit of AID use for many Australian adults with type 1 diabetes.

Less than 20% of Australians with type 1 diabetes (T1D) meet recommended glucose targets. Technology use is associated with better glycaemia, with the most advanced being automated insulin delivery (AID) systems, which are now recommended as gold-standard T1D care. Our Australian AID trial shows a wide spectrum of adults with T1D can achieve recommended targets. Other studies, including lived experience data, are supportive. Insulin pumps are not subsidised for most Australian adults with T1D. We advocate change.

Disparities in Diabetes Technology Uptake in Youth and Young Adults With Type 1 Diabetes: A Global Perspective

Abstract Globally, nearly 9 million people are living with type 1 diabetes (T1D). Although the incidence of T1D is not affected by socioeconomic status, the development of complications and limited access to modern therapy is overrepresented in vulnerable populations. Diabetes technology, specifically continuous glucose monitoring and automated insulin delivery systems, are considered the gold standard for management of T1D, yet access to these technologies varies widely across countries and regions, and varies widely even within high-income countries. This review focuses on disparities in diabetes technology use among adolescents and young adults with T1D, barriers to access and use, and summarizes common themes emerging across countries and regions. We conducted a survey among medical technology manufacturers and physicians in various countries across diverse geographical regions and performed extensive literature searches. Across all countries and regions, economic barriers stand out as the largest and most common barriers, either preventing market penetrance of technology into a country or limiting its access to the individual with diabetes due to high out of pocket costs. Other common barriers include structural or accessibility barriers, such as stringent eligibility requirements by insurance providers, regardless of whether the insurance was private or government-based, and provider/individual level barriers. Based on the evidence presented, we suggest the need for a joint effort involving governments, private health insurers, technology manufacturers, and healthcare providers to address the global disparities of diabetic technology utilization and ensure equitable access for all individuals living with T1D worldwide.

Prevent hypoglycaemia when using automated insulin delivery systems in type 1 diabetes requires near normal glycaemic variability

AimAlthough newer technologies of insulin delivery in type 1 diabetes have facilitated an improvement in glycaemic control the risk of hypoglycaemia remains a threat. Therefore, it is important to define the thresholds of glycaemic variability below which the risk of hypoglycaemia can be eliminated or at least minimized. MethodsRandomized controlled trials conducted from 2017 to 2023 comparing Sensor-Augmented-Pumps and Augmented Insulin Delivery Systems (n = 16 and 22 studies, respectively) were selected. A weighted linear model of regression was used to compute the relationship between glycaemic variability and times spent below glucose range. The intercepts of regression lines with the abscissa axis (time below range = 0 %) defined the glycaemic variability thresholds. ResultsPositive relationships were observed between the 2 metrics. The scatter plots indicated that the times spent below range never reached the value of 0 % and that the glycaemic variability never fell below 28 %. By extrapolating the regression lines, the glycaemic variability at intercepts with time below range < 70 mg/dL of 0 % was 30.1 % with sensor augmented pumps and 18.9 % with automated insulin delivery. For a time below range < 54 mg/dL of 0 % the respective glycaemic variability values were 32.7 % and 19.9 % (with sensor augmented pumps and automated insulin delivery, respectively). ConclusionsImportantly, glycaemic variability targets and ambient hyperglycaemia are interdependent. Users of automated insulin delivery need to reach a glycaemic variability of 18 % to 20 % to minimize or eradicate the risk of hypoglycaemia. Such values are those observed in healthy non-diabetic people.

Is Automated Insulin Delivery System Therapy Safe and Effectıve in Children Under 7 Years Old?

This study aims to evaluate the off-label use of the MiniMed™ 780G system in children under seven years old, as clinical outcomes in this age group are less established despite the improvements in glycemic control seen with MiniMed™ 780G therapy. Children under seven years old with type 1 diabetes (T1D) using MiniMed™ 780G pump therapy were retrospectively compared with children of similar age and gender using MiniMed™ 640G insulin pump therapy and multiple-dose insulin (MDI) therapy with continuous glucose monitoring systems (CGMs). CGM metrics, total daily insulin dose (TDI), and HbA1c levels were evaluated retrospectively at baseline and at the 3rd, 6th, and 12th months. At the initiation of MiniMed™ 780G therapy, the mean age was 5,25±1,22 years (range: 2,8-6,8 years), and the mean TDI was 10,12±4,34 U/day (range: 4,5-17 U/day). The glucose management indicator (GMI) and HbA1c remained lower in the MiniMed™ 780G group at the 3rd, 6th, and 12th months compared to baseline (p=0,009 and p<0,001, respectively). In the MiniMed™ 780G group, Time Above Range (TAR) was significantly lower at the 3rd, 6th, and 12th months (p=0,018, 0,017, and 0,04, respectively), and Time in Range (TIR) was higher at the 3rd and 12th months (p=0,026 and 0,019, respectively). The coefficient of variation (CV) and HbA1c were lower at the 12th month (p=0,008 and 0,015, respectively) compared to the other groups. No instances of ketoacidosis or severe hypoglycemic events were observed in any of the children during the follow-up period. The absence of significantly higher levels of hypoglycemia compared to other groups at any time point, along with a significant decrease in TAR across all time points, a significant increase in TIR at the 3rd and 12th months, and a significant decrease in HbA1c and CV, indicates that the MiniMed™ 780G system is both safe and effective for children under seven years old.

Cardiac autonomic neuropathy: impact on severe hypoglycemic unawareness and orthostatic hypotension in diabetic dysautonomia, a case series and review.

Diabetic autonomic neuropathy (DAN) and its associated cardiovascular autonomic neuropathy (CAN) can lead to potentially fatal complications. We analyzed two distinct cases of DAN/CAN based on comprehensive cardiovascular autonomic reflex tests (CARTs). Case 1 involves a 27-year-old patient with T1DM suffering from recurrent severe hypoglycemic unawareness due to DAN. After implementing an automated insulin delivery system, the glucose management improved significantly. Case 2 describes a 60-year-old patient with type 2 diabetes experiencing debilitating orthostatic hypotension. The initiation of Midodrine and Fludrocortisone markedly improved symptoms and capacity of daily activities. This observational study highlights the critical yet frequently overlooked severe manifestations of DAN/CAN, specifically hypoglycemic unawareness and orthostatic hypotension. CARTs play a pivotal role in confirming the diagnosis and guiding therapeutic decisions. Tailored interventions, including advanced technologies like automated insulin delivery systems for T1DM and pharmacotherapy targeting neurogenic orthostasis, can significantly improve patient outcomes and quality of life.

Development of a Diabetes Navigator Toolkit to Support Diabetes Technology Uptake: The IMPACT Toolkit

Advanced diabetes technologies (ADTs), including continuous glucose monitoring devices, insulin pumps, and automated insulin delivery systems, improve glycemic control in type 1 diabetes but are underutilized, particularly in minority and underserved populations. This article reports on a qualitative study to develop a diabetes toolkit. Participants identified barriers to the use of ADTs and proposed solutions to these barriers, which were then incorporated into a diabetes toolkit designed for use by a diabetes navigator or other diabetes care team members seeking to improve the uptake and sustained use of ADTs.

Efficacy and Safety of Automated Insulin Delivery Systems in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM). We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently. Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (??.80% vs. ??.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (??.93% vs. ??.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (??9.64% vs. ??0.87%). Notably, glycemia risk index (GRI) (??.74; 95% CI, ??.34 to ??.14; P<0.01) was also improved with AID therapy. AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.

Time in tight range: A key metric for optimal glucose control in the era of advanced diabetes technologies and therapeutics.

Compared to glycated haemoglobin A1c (HbA1c), the rapidly developing continuous glucose monitoring (CGM) technology provides more detailed information about glycemic control. Amongst the new glucose metrics derived from CGM, time in target range of 3.9-10.0 mmol/L (time in range, TIR) has been widely used for the assessment of glucose control. In recent years, the rise of new technologies and therapies including advanced hybrid closed-loop automated insulin delivery systems and new hypoglycemic drugs has made it possible to achieve better glycemic control. In this context, the concept of time in tight range (TITR), defined as the percentage of time spent in target glucose range of 3.9-7.8 mmol/L, has gained increasing attention. Whilst TITR is highly correlated with TIR, there are still differences between the two metrics. These differences make TITR a more appropriate indicator in certain situations, such as when glucose levels are close to normal or when tighter glycemic control is required. This review summarizes recent studies related to TITR.

Consensus Report on Glucagon-Like Peptide-1 Receptor Agonists as Adjunctive Treatment for Individuals With Type 1 Diabetes Using an Automated Insulin Delivery System.

With increasing prevalence of obesity and cardiovascular diseases, there is a growing interest in the use of glucagon-like peptide-1 receptor agonists (GLP-1RAs) as an adjunct therapy in type 1 diabetes (T1D). The GLP-1RAs are currently not approved by the US Food and Drug Administration for the treatment of T1D in the absence of randomized controlled trials documenting efficacy and safety of these agents in this population. The Diabetes Technology Society convened a series of three consensus meetings of clinicians and researchers with expertise in diabetes technology, GLP-1RA therapy, and T1D management. The project was aimed at synthesizing current literature and providing conclusions on the use of GLP-1RA therapy as an adjunct to automated insulin delivery (AID) systems in adults with T1D. The expert panel members met virtually three times on January 17, 2024, and April 24, 2024, and August 14, 2024, to discuss topics ranging from physiology and outcomes of GLP-1RAs in T1D to limitations of current sensors, algorithms, and insulin for AID systems. The panelists also identified research gaps and future directions for research. The panelists voted to in favor of 31 recommendations. This report presents the consensus opinions of the participants that, in adults with T1D using AID systems, GLP-1RAs have the potential to (1) provide effective adjunct therapy and (2) improve glycemic and metabolic outcomes without increasing the risk of severe hypoglycemia or diabetic ketoacidosis.

Comparison of Computational Statistical Packages for the Analysis of Continuous Glucose Monitoring Data with a Reference Software, "Ambulatory Glucose Profile," in Type 1 Diabetes.

Objective: To compare the accuracy of commonly used continuous glucose monitoring (CGM) analysis programs with ambulatory glucose profile (AGP) and Dexcom Clarity (DC) in analyzing CGM metrics in patients with type 1 diabetes (T1D). Research Methods: CGM data up to 90 days from 152 adults using the same CGM and automated insulin delivery system with T1D were collected. Six of the 19 CGM analysis programs (CDGA, cgmanalysis, Glyculator, iglu, EasyGV, and GLU) were selected to compare with AGP and DC. Metrics were compared etween all tools with two one-sided t-tests equivalence testing. For the equivalence test, the acceptable range of deviation was set as ±2 mg/dL for mean glucose, ±2% for time in range (TIR), ±1% for time above range (TAR), time above range level 1 (TAR1), time above range level 2 (TAR2), and coefficient of variation (CV). Results: All packages were compared with each other for all CGM metrics, and most of them had statistically significant differences for at least some metrics. All tools were equivalent to AGP for mean glucose, TIR, TAR, TAR1, and TAR2 within ±2 mg/dL, ±2%, ±1%, ±1% and 1%, respectively. CDGA, Glyculator, cgmanalysis, and iglu were not equivalent to AGP for CV within ±1%. All tools were equivalent to DC for mean glucose, TIR, and TAR2 within ±2 mg/dL, ±2%, and ±1%, respectively. Glyculator was not equivalent for TAR1, TAR, and CV. CGDA, cgmanalysis, and iglu were not equivalent to DC for TAR1 and TAR. EasyGV and GLU were not equivalent for TAR within ±1%. Conclusions: CGM analysis programs reported CGM metrics statistically differently, but these differences may not be applicable in clinical practice. The equivalence test also confirmed that the differences are negligible for TIR and mean glucose, while they can be important for hyperglycemic ranges and CV. A standardization for CGM data handling and analysis is necessary for clinical studies reporting CGM-generated outcomes.

Automated insulin delivery systems in elderly patients with brittle type 2 diabetes

PurposeGeriatric diabetes is complicated by the frailty of this population, and hypoglycemia with insulin is not uncommon in these patients. Automated Insulin Delivery (AID) systems may provide better glycemic control in elderly patients with brittle type 2 diabetes. MethodsThirty-four patients (≥ 60 years) including cancer patients with brittle diabetes were switched to an AID system from multiple-dose insulin (MDI) treatment. HbA1c level, weight, total daily insulin requirement, and C-peptide, creatinine, and lipids were followed for at least six months. ResultsThere were 34 patients (14 male, 41.2 %) with a median age of 67 (IQR 63.0–75.5). Six patients (17.6 %) were on chemotherapy and/or steroids (Ch/S). The patients’ initial median HbA1c % was 9.3 (IQR 7.6–11.0), c-peptide level was 0.9 (IQR 0.5–2.2) ng/mL, and median total daily insulin dose was 41 IU (IQR 32–53).Six months after the patients were switched to an AID system their HbA1c % decreased to 7.1 (IQR 6.5–8.1), p < 0.001 and c-peptide increased to 1.21 (IQR 0.2–1.7) ng/mL, p = 0.878. Total insulin dose decreased with AID systems [32 IU (IQR 23.9–37.8)), p < 0.001].There was a decrease in median HbA1c % in patients on Ch/S [8.7 (IQR 7.0–11.5) to 6.9 (IQR 6.3–9.2)] however it didn’t reach statistical significance p = 0.225. Total insulin dose also decreased without statistical significance [33 IU (IQR 41–28) to 28 (IQR 23–35), p = 0.173].The mean time in range (TIR) percent of the patients with AID systems were as follows; <54 mg/dL was 0.5 %, 56–70 mg/dL was 1.3 %, 70–180 mg/dL was 64.8 %, >180 mg/dL was 26.7 % and > 250 mg/dL was 6.7 %. ConclusionAlthough AID systems are tested mostly in young type 1 patients our results show that elderly patients with brittle type 2 diabetes also benefit from an AID system. Even in very frail patients such as cancer patients, improvement can be seen.