Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes

Blood Glucose Prediction from Nutrition Analytics in Type 1 Diabetes: A Review

INTRODUCTION

Type 1 Diabetes (T1D) affects over 9 million worldwide and necessitates meticulous self-management for blood glucose (BG) control. Utilizing BG prediction technology allows for increased BG control and a reduction in the diabetes burden caused by self-management requirements. This paper reviews BG prediction models in T1D, which include nutritional components.

METHOD

A systematic search, utilizing the PRISMA guidelines, identified articles focusing on BG prediction algorithms for T1D that incorporate nutritional variables. Eligible studies were screened and analyzed for model type, inclusion of additional aspects in the model, prediction horizon, patient population, inputs, and accuracy.

RESULTS

The study categorizes 138 blood glucose prediction models into data-driven (54%), physiological (14%), and hybrid (33%) types. Prediction horizons of ≤30 min are used in 36% of models, 31-60 min in 34%, 61-90 min in 11%, 91-120 min in 10%, and >120 min in 9%. Neural networks are the most used data-driven technique (47%), and simple carbohydrate intake is commonly included in models (data-driven: 72%, physiological: 52%, hybrid: 67%). Real or free-living data are predominantly used (83%).

CONCLUSION

The primary goal of blood glucose prediction in T1D is to enable informed decisions and maintain safe BG levels, considering the impact of all nutrients for meal planning and clinical relevance.

7. Diabetes Technology: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Real-World User and Clinician Perspective and Experience with MiniMed™ 780G Advanced Hybrid Closed Loop System

INTRODUCTION

The advanced hybrid closed loop (AHCL) MiniMed™ 780G system changes basal insulin delivery every 5 min and auto bolus in response to sensor glucose values. We assessed the performance of the AHCL system in real-world settings for individuals with type 1 diabetes (T1DM) as well as user and clinician perspectives and satisfaction.

METHODS

We held two peer group discussions: one having adults with T1DM/parents of children and adolescents with T1DM to understand their experiences with the AHCL system and another with healthcare providers (HCPs). Responses from the discussions were analyzed and categorized into themes by two independent researchers, with any inconsistencies resolved by consensus. We also analyzed data from the system uploaded to CareLink personal software. Glycemic outcomes, including time in range (TIR), time below range (TBR), time above range (TAR), mean sensor glucose (SG) levels, glucose management indicator (GMI), sensor use, and percentage of time spent in AHCL, were determined.

RESULTS

The peer group discussions revealed numerous key themes and issues for each group, such as the significance of setting reasonable expectations, carbohydrate counting and bolus dosing, technical difficulties, and overall user experience. The users (n = 25; T1DM; 17 female; age 13.8 ± 7.49 years; A1C 6.54 ± 0.45%; duration of diabetes 6 ± 6.78 years) were very satisfied with the system. Most users experienced consistent blood glucose values with very few hypoglycemic episodes. However, there were a few limitations reported, such as hyperglycemic episodes caused by inaccuracies in carb counting, issues with sensor connectivity, and cannula blockages or kinking for those using insulin Fiasp. Users achieved a mean GMI of 6.4 ± 0.26%, TIR of 83.0 ± 8.12%, TBR (54-70 mg/dL) of 2.0 ± 0.81%, TBR* (< 54 mg/dL) of 0%. All of the users achieved a TIR of > 70%.

CONCLUSION

The use of the AHCL system in T1DM resulted in robust glycemic control, minimizing hypoglycemia. Providing training to both users and HCPs can help them use the system effectively.

7. Diabetes Technology: Standards of Care in Diabetes-2023

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A Comparison of Postprandial Glucose Control in the Medtronic Advanced Hybrid Closed-Loop System Versus 670G

Background: We recently reported that use of an "advanced" hybrid closed-loop system reduced hyperglycemia without increasing hypoglycemia compared to a first-generation system. The aim of this analysis was to evaluate whether this improved performance was specifically related to better mealtime glycemic control. Methods: We conducted a secondary analysis of postprandial glycemic control in an open-label, multinational, randomized crossover trial of 112 participants with type 1 diabetes, aged 14-29, of the Medtronic MiniMed™ 670G hybrid closed-loop system (670G) versus the Medtronic advanced hybrid closed-loop (AHCL) system, for 12 weeks each. We compared glycemic and insulin delivery metrics over a 3 h horizon across all meals to assess system performance and outcomes. Results: Overall meal size and premeal insulin on board were similar during run-in and between 670G and AHCL arms. Compared with 670G arm, premeal, peak, and mean glucose levels were numerically lower in the AHCL arm (167 ± 23, 231 ± 23, and 177 ± 20 mg/dL vs. 175 ± 23, 235 ± 23, and 180 ± 19 mg/dL, respectively), with a trend to lower hyperglycemia level 2 in AHCL arm. Adjusting for premeal glucose level, all postmeal outcomes between 670G and AHCL were statistically similar. Prandial insulin delivery also was similar in both treatment arms (21 ± 9 vs. 23 ± 10 U), with a shift in basal/bolus ratio from 28%/71% in 670G arm to 20%/80% in AHCL arm. Conclusions: Reduced hyperglycemia with AHCL compared to 670G was not related to early postprandial glycemic excursions after adjusting for premeal glucose level (<3 h after meal), but likely to later (>3 h) postprandial or overnight improvements. Further refinements to mealtime bolus algorithms and strategies may more optimally control prandial glycemic excursions.

J. Schreiber L, Wallace EJ, Wylie R, O'Sullivan J, Dolan EB, Duffy GP. Medical devices, smart drug delivery, wearables and technology for the treatment of Diabetes Mellitus

Diabetes mellitus refers to a group of metabolic disorders which affect how the body uses glucose impacting approximately 9% of the population worldwide. This review covers the most recent technological advances envisioned to control and/or reverse Type 1 diabetes mellitus (T1DM), many of which will also prove effective in treating the other forms of diabetes mellitus. Current standard therapy for T1DM involves multiple daily glucose measurements and insulin injections. Advances in glucose monitors, hormone delivery systems, and control algorithms generate more autonomous and personalised treatments through hybrid and fully automated closed-loop systems, which significantly reduce hypo- and hyperglycaemic episodes and their subsequent complications. Bi-hormonal systems that co-deliver glucagon or amylin with insulin aim to reduce hypoglycaemic events or increase time spent in target glycaemic range, respectively. Stimuli responsive materials for the controlled delivery of insulin or glucagon are a promising alternative to glucose monitors and insulin pumps. By their self-regulated mechanism, these "smart" drugs modulate their potency, pharmacokinetics and dosing depending on patients' glucose levels. Islet transplantation is a potential cure for T1DM as it restores endogenous insulin and glucagon production, but its use is not yet widespread due to limited islet sources and risks of chronic immunosuppression. New encapsulation strategies that promote angiogenesis and oxygen delivery while protecting islets from recipients' immune response may overcome current limiting factors.

Clinical Implementation of the Omnipod 5 Automated Insulin Delivery System: Key Considerations for Training and Onboarding People With Diabetes

Automated insulin delivery (AID) systems, which connect an insulin pump, continuous glucose monitoring system, and software algorithm to automate insulin delivery based on real-time glycemic data, hold promise for improving outcomes and reducing therapeutic burden for people with diabetes. This article reviews the features of the Omnipod 5 Automated Insulin Delivery System and how it compares to other AID systems available on or currently under review for the U.S. market. It also provides practical guidance for clinicians on how to effectively train and onboard people with diabetes on the Omnipod 5 System, including how to personalize therapy and optimize glycemia. Many people with diabetes receive their diabetes care in primary care settings rather than in a diabetes specialty clinic. Therefore, it is important that primary care providers have access to resources to support the adoption of AID technologies such as the Omnipod 5 System.

7. Diabetes Technology: Standards of Medical Care in Diabetes-2022

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc22-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc22-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence

Since Banting and Best isolated insulin in the 1920s, dramatic progress has been made in the treatment of type 1 diabetes mellitus (T1DM). However, dose titration and timely injection to maintain optimal glycemic control are often challenging for T1DM patients and their families because they require frequent blood glucose checks. In recent years, technological advances in insulin pumps and continuous glucose monitoring systems have created paradigm shifts in T1DM care that are being extended to develop artificial pancreas systems (APSs). Numerous studies that demonstrate the superiority of glycemic control offered by APSs over those offered by conventional treatment are still being published, and rapid commercialization and use in actual practice have already begun. Given this rapid development, keeping up with the latest knowledge in an organized way is confusing for both patients and medical staff. Herein, we explore the history, clinical evidence, and current state of APSs, focusing on various development groups and the commercialization status. We also discuss APS development in groups outside the usual T1DM patients and the administration of adjunct agents, such as amylin analogues, in APSs.

Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications

INTRODUCTION

Smartphone applications (apps) have been designed that help patients to accurately count their carbohydrate intake in order to optimize prandial insulin dose matching. Our aim was to evaluate the accuracy of two carbohydrate (carb) counting apps.

METHODS

Medical students, in the role of mock patients, evaluated meals using two smartphone apps: Foodvisor^® (which uses automatic food photo recognition technology) and Glucicheck^® (which requires the manual entry of carbohydrates with the help of a photo gallery). The macronutrient quantifications obtained with these two apps were compared to a reference quantification.

RESULTS

The carbohydrate content of the entire meal was underestimated with Foodvisor^® (Foodvisor^® quantification minus gold standard quantification = - 7.2 ± 17.3 g; p < 0.05) but reasonably accurately estimated with Glucicheck^® (Glucicheck^® quantification minus gold standard quantification = 1.4 ± 13.4 g; ns). The percentage of meals with an absolute error in carbohydrate quantification above 20 g was greater for Foodvisor^® compared to Glucicheck^® (30% vs 14%; p < 0.01).

CONCLUSION

The carb counting accuracy was slightly better when using Glucicheck^® compared to Foodvisor^®. However, both apps provided a lower mean absolute carb counting error than that usually made by T1D patients in everyday life, suggesting that such apps may be a useful adjunct for estimating carbohydrate content.

Multicenter Trial of a Tubeless, On-Body Automated Insulin Delivery System With Customizable Glycemic Targets in Pediatric and Adult Participants With Type 1 Diabetes

OBJECTIVE

Advances in diabetes technology have transformed the treatment paradigm for type 1 diabetes, yet the burden of disease is significant. We report on a pivotal safety study of the first tubeless, on-body automated insulin delivery system with customizable glycemic targets.

RESEARCH DESIGN AND METHODS

This single-arm, multicenter, prospective study enrolled 112 children (age 6-13.9 years) and 129 adults (age 14-70 years). A 2-week standard therapy phase (usual insulin regimen) was followed by 3 months of automated insulin delivery. Primary safety outcomes were incidence of severe hypoglycemia and diabetic ketoacidosis. Primary effectiveness outcomes were change in HbA_1c and percent time in sensor glucose range 70-180 mg/dL ("time in range").

RESULTS

A total of 235 participants (98% of enrolled, including 111 children and 124 adults) completed the study. HbA_1c was significantly reduced in children by 0.71% (7.8 mmol/mol) (mean ± SD: 7.67 ± 0.95% to 6.99 ± 0.63% [60 ± 10.4 mmol/mol to 53 ± 6.9 mmol/mol], P < 0.0001) and in adults by 0.38% (4.2 mmol/mol) (7.16 ± 0.86% to 6.78 ± 0.68% [55 ± 9.4 mmol/mol to 51 ± 7.4 mmol/mol], P < 0.0001). Time in range was improved from standard therapy by 15.6 ± 11.5% or 3.7 h/day in children and 9.3 ± 11.8% or 2.2 h/day in adults (both P < 0.0001). This was accomplished with a reduction in time in hypoglycemia <70 mg/dL among adults (median [interquartile range]: 2.00% [0.63, 4.06] to 1.09% [0.46, 1.75], P < 0.0001), while this parameter remained the same in children. There were three severe hypoglycemia events not attributable to automated insulin delivery malfunction and one diabetic ketoacidosis event from an infusion site failure.

CONCLUSIONS

This tubeless automated insulin delivery system was safe and allowed participants to significantly improve HbA_1c levels and time in target glucose range with a very low occurrence of hypoglycemia.

First Outpatient Evaluation of a Tubeless Automated Insulin Delivery System with Customizable Glucose Targets in Children and Adults with Type 1 Diabetes

Background: The objective of this study was to assess the safety and effectiveness of the first commercial configuration of a tubeless automated insulin delivery system, Omnipod^® 5, in children (6-13.9 years) and adults (14-70 years) with type 1 diabetes (T1D) in an outpatient setting. Materials and Methods: This was a single-arm, multicenter, prospective clinical study. Data were collected over a 14-day standard therapy (ST) phase followed by a 14-day hybrid closed-loop (HCL) phase, where participants (n = 36) spent 72 h at each of three prespecified glucose targets (130, 140, and 150 mg/dL, 9 days total) then 5 days with free choice of glucose targets (110-150 mg/dL) using the Omnipod 5. Remote safety monitoring alerts were enabled during the HCL phase. Primary endpoints were difference in time in range (TIR) (70-180 mg/dL) between ST and HCL phases and proportion of participants reporting serious device-related adverse events. Results: Mean TIR was significantly higher among children in the free-choice period overall (64.9% ± 12.2%, P < 0.01) and when using a 110 mg/dL target (71.2% ± 10.2%, P < 0.01), a 130 mg/dL target (61.5% ± 7.7%, P < 0.01), and a 140 mg/dL target (64.8% ± 11.6%, P < 0.01), and among adults using a 130 mg/dL target (75.1% ± 11.6%, P < 0.05), compared to the ST phase (children: 51.0% ± 13.3% and adults: 65.6% ± 15.7%). There were no serious device-related adverse events reported during the HCL phase, nor were there episodes of severe hypoglycemia or diabetic ketoacidosis. Conclusion: The Omnipod 5 System was safe and effective when used at glucose targets from 110 to 150 mg/dL for 14 days at home in children and adults with T1D.

Current treatment options and challenges in patients with Type 1 diabetes: Pharmacological, technical advances and future perspectives

Type 1 diabetes mellitus imposes a significant burden of complications and mortality, despite important advances in treatment: subjects affected by this disease have also a worse quality of life-related to disease management. To overcome these challenges, different new approaches have been proposed, such as new insulin formulations or innovative devices. The introduction of insulin pumps allows a more physiological insulin administration with a reduction of HbA1c level and hypoglycemic risk. New continuous glucose monitoring systems with better accuracy have allowed, not only better glucose control, but also the improvement of the quality of life. Integration of these devices with control algorithms brought to the creation of the first artificial pancreas, able to independently gain metabolic control without the risk of hypo- and hyperglycemic crisis. This approach has revolutionized the management of diabetes both in terms of quality of life and glucose control. However, complete independence from exogenous insulin will be obtained only by biological approaches that foresee the replacement of functional beta cells obtained from stem cells: this will be a major challenge but the biggest hope for the subjects with type 1 diabetes. In this review, we will outline the current scenario of innovative diabetes management both from a technological and biological point of view, and we will also forecast some cutting-edge approaches to reduce the challenges that hamper the definitive cure of diabetes.

Feasibility Study of a Hybrid Closed-Loop System with Automated Insulin Correction Boluses

Background: The Medtronic MiniMed™ 670G system adjusts basal insulin delivery in response to continuous glucose monitoring levels and is already in use in clinical practice. We tested the home-based feasibility of the new MiniMed advanced hybrid closed-loop (AHCL) system, which includes several algorithm enhancements and an optional autocorrection bolus mode. Methods: Twelve adolescents and young adults (eight females) with type 1 diabetes [median (interquartile range)] aged 16.6 (15.9, 18.2) years and diabetes duration of 7.1 (4.7, 8.8) years] participated in this single-arm study. The first stage was a 6-day open-loop run-in period, with the predictive low-glucose suspend feature on. This was followed by 6 days/5 nights in a supervised hotel setting, using the AHCL system, including closed-loop challenges (missed meal bolus, late meal bolus, and physical activity); and finally, 3 weeks with unrestricted home use. Glycemic parameters were compared between the open-loop and closed-loop periods. Results: Participants spent 93.3% (4.7) of the time in SmartGuard™ Auto Mode. Hemoglobin A1C levels decreased from median (interquartile range) 7.1% (6.7, 7.9) at baseline to 6.8% (6.6, 7.4) at study end, after 4 weeks (P = 0.0027). Time in range (TIR) (70-180 mg/dL) was 68.4% (10.6) and time below 70 mg/dL was 4% (3.5) during open-loop; and 74% (6.1) and 2.6% (1.9), respectively, during the closed-loop at home phase (P = 0.06, P = 0.27). TIR increased during the nighttime, from 64.6% (17.4) to 80.7% (7.8), P = 0.007, without change in time below 70 mg/dL (P = 0.15). No serious adverse events occurred. Conclusions: The new AHCL system demonstrated safety and effectiveness in controlling day and night glucose levels.

Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies

Background: Automated insulin delivery (AID) systems have demonstrated improvements in time-in-range (TIR, blood glucose 70-180 mg/dL) without increasing hypoglycemia. Testing a closed-loop system in an inpatient environment with supervised challenges allows for initial evaluation of performance and safety of the system. Methods: Adults with type 1 diabetes (T1D) were enrolled into two similar studies (n = 10 per study), with 3-day inpatient analysis periods. Participants tested a Lilly hybrid closed-loop (HCL) system comprising an investigational insulin pump, insulin lispro, a pump-embedded model predictive control algorithm, a continuous glucose monitor (CGM), and an external dedicated controller. Each protocol included meal-related and exercise challenges to simulate real-world diabetes self-management errors. Only study staff interacted with the HCL system. Performance was assessed using standard CGM metrics overall and within prespecified periods. Results: Participants (25% male) had mean ± standard deviation (SD) age 44.7 ± 14.2 years, T1D duration 30.2 ± 11.1 years, A1C 7.2% ± 0.8%, and insulin usage 0.53 ± 0.21 U/(kg·day). Percentage TIR 70-180 mg/dL (mean ± SD) was 81.2 ± 8.4 overall, 85.2 ± 8.1 outside of challenge periods, 97.3 ± 5.3 during the nocturnal periods, and 74.5 ± 16.2 for the postprandial periods. During challenge periods, percentage TIR for the overbolus challenge was 65.4 ± 29.2 and that for the delayed bolus challenge was 57.1 ± 25.1. No adverse events (AEs), serious AEs, or unanticipated adverse device events occurred while participants were using the HCL system. Conclusions: In participants with T1D, Lilly AID system demonstrated expected algorithm performance and safety with satisfactory glycemic outcomes overall and in response to simulated diabetes management challenges. Additional studies in less supervised conditions and with broader patient populations are warranted. ClinicalTrials.gov Registration number NCT03743285, NCT03849612.

7. Diabetes Technology: Standards of Medical Care in Diabetes-2021

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A clinical review of the t:slim X2 insulin pump

Insulin pumps are commonly used for intensive insulin therapy to treat type 1 diabetes in adults and youth. Insulin pump technologies have advanced dramatically in the last several years to integrate with continuous glucose monitors (CGM) and incorporate control algorithms. These control algorithms automate some insulin delivery in response to the glucose information received from the CGM to reduce the occurrence of hypoglycemia and hyperglycemia and improve overall glycemic control. The t:slim X2 insulin pump system became commercially available in 2016. It is an innovative insulin pump technology that can be updated remotely by the user to install new software onto the pump device as new technologies become available. Currently, the t:slim X2 pairs with the Dexcom G6 CGM and there are two advanced software options available: Basal-IQ, which is a predictive low glucose suspend (PLGS) technology, and Control-IQ, which is a Hybrid Closed Loop (HCL) technology. This paper will describe the different types of advanced insulin pump technologies, review how the t:slim X2 insulin pump works, and summarize the clinical studies leading to FDA approval and commercialization of the Basal-IQ and Control-IQ technologies.

Review of the Omnipod® 5 Automated Glucose Control System Powered by Horizon™ for the treatment of Type 1 diabetes

Type 1 diabetes (T1D) is a medical condition that requires constant management, including monitoring of blood glucose levels and administration of insulin. Advancements in diabetes technology have offered methods to reduce the burden on people with T1D. Several hybrid closed-loop systems are commercially available or in clinical trials, each with unique features to improve care for patients with T1D. This article reviews the Omnipod® 5 Automated Glucose Control System Powered by Horizon™ and the safety and efficacy data to support its use in the management of T1D.

A Randomized, Placebo-Controlled Double-Blind Trial of a Closed-Loop Glucagon System for Postbariatric Hypoglycemia

BACKGROUND

Postbariatric hypoglycemia (PBH) can threaten safety and reduce quality of life. Current therapies are incompletely effective.

METHODS

Patients with PBH were enrolled in a double-blind, placebo-controlled, crossover trial to evaluate a closed-loop glucose-responsive automated glucagon delivery system designed to reduce severe hypoglycemia. A hypoglycemia detection and mitigation algorithm was embedded in the artificial pancreas system connected to a continuous glucose monitor (CGM, Dexcom) driving a patch infusion pump (Insulet) filled with liquid investigational glucagon (Xeris) or placebo (vehicle). Sensor/plasma glucose responses to mixed meal were assessed during 2 study visits. The system delivered up to 2 doses of study drug (300/150 μg glucagon or equal-volume vehicle) if triggered by the algorithm. Rescue dextrose was given for plasma glucose <55 mg/dL or neuroglycopenia.

RESULTS

Twelve participants (11 females/1 male, age 52 ± 2, 8 ± 1 years postsurgery, mean ± SEM) completed all visits. Predictive hypoglycemia alerts prompted automated drug delivery postmeal, when sensor glucose was 114 ± 7 vs 121 ± 5 mg/dL (P = .39). Seven participants required rescue glucose after vehicle but not glucagon (P = .008). Five participants had severe hypoglycemia (<55 mg/dL) after vehicle but not glucagon (P = .03). Nadir plasma glucose was higher with glucagon vs vehicle (67 ± 3 vs 59 ± 2 mg/dL, P = .004). Plasma glucagon rose after glucagon delivery (1231 ± 187 vs 16 ± 1 pg/mL at 30 minutes, P = .001). No rebound hyperglycemia occurred. Transient infusion site discomfort was reported with both glucagon (n = 11/12) and vehicle (n = 10/12). No other adverse events were observed.

CONCLUSION

A CGM-guided closed-loop rescue system can detect imminent hypoglycemia and deliver glucagon, reducing severe hypoglycemia in PBH.

CLINICAL TRIALS REGISTRATION

NCT03255629.

Automated Insulin Delivery in Adults

Hybrid closed-loop (artificial pancreas) systems have recently been introduced into clinical practice for adults with type 1 diabetes. This reflects successful translation from research studies in highly supervised settings to evaluation of the technology in free-living home settings. We review the different closed-loop approaches and the key clinical evidence supporting adoption of hybrid closed-loop systems for adults with type 1 diabetes. We also discuss the growing evidence for automated insulin delivery in pregnant women and in hospitalized patients with hyperglycemia. We consider the psychosocial impact of closed-loop systems and the challenges and potential future advancements for automated insulin delivery.

Safety and Performance of the Omnipod Hybrid Closed-Loop System in Adults, Adolescents, and Children with Type 1 Diabetes Over 5 Days Under Free-Living Conditions

Background: The objective of this study was to assess the safety and performance of the Omnipod^® personalized model predictive control (MPC) algorithm in adults, adolescents, and children aged ≥6 years with type 1 diabetes (T1D) under free-living conditions using an investigational device. Materials and Methods: A 96-h hybrid closed-loop (HCL) study was conducted in a supervised hotel/rental home setting following a 7-day outpatient standard therapy (ST) phase. Eligible participants were aged 6-65 years with A1C <10.0% using insulin pump therapy or multiple daily injections. Meals during HCL were unrestricted, with boluses administered per usual routine. There was daily physical activity. The primary endpoints were percentage of time with sensor glucose <70 and ≥250 mg/dL. Results: Participants were 11 adults, 10 adolescents, and 15 children aged (mean ± standard deviation) 28.8 ± 7.9, 14.3 ± 1.3, and 9.9 ± 1.0 years, respectively. Percentage time ≥250 mg/dL during HCL was 4.5% ± 4.2%, 3.5% ± 5.0%, and 8.6% ± 8.8% per respective age group, a 1.6-, 3.4-, and 2.0-fold reduction compared to ST (P = 0.1, P = 0.02, and P = 0.03). Percentage time <70 mg/dL during HCL was 1.9% ± 1.3%, 2.5% ± 2.0%, and 2.2% ± 1.9%, a statistically significant decrease in adults when compared to ST (P = 0.005, P = 0.3, and P = 0.3). Percentage time 70-180 mg/dL increased during HCL compared to ST, reaching significance for adolescents and children: HCL 73.7% ± 7.5% vs. ST 68.0% ± 15.6% for adults (P = 0.08), HCL 79.0% ± 12.6% vs. ST 60.6% ± 13.4% for adolescents (P = 0.01), and HCL 69.2% ± 13.5% vs. ST 54.9% ± 12.9% for children (P = 0.003). Conclusions: The Omnipod personalized MPC algorithm was safe and performed well over 5 days and 4 nights of use by a cohort of participants ranging from youth aged ≥6 years to adults with T1D under supervised free-living conditions with challenges, including daily physical activity and unrestricted meals.

7. Diabetes Technology: Standards of Medical Care in Diabetes-2020

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc20-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc20-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

MiniMed 670G hybrid closed loop artificial pancreas system for the treatment of type 1 diabetes mellitus: overview of its safety and efficacy

Introduction: Automated insulin delivery for people with type 1 diabetes has been a major goal in the diabetes technology field for many years. While a fully automated system has not yet been accomplished, the MiniMed™ 670G artificial pancreas (AP) system is the first commercially available insulin pump that automates basal insulin delivery, while still requiring user input for insulin boluses. Determining the safety and efficacy of this system is essential to the development of future devices striving for more automation. Areas Covered: This review will provide an overview of how the MiniMed 670G system works including its safety and efficacy, how it compares to similar devices, and anticipated future advances in diabetes technology currently under development. Expert Opinion: The ultimate goal of advanced diabetes technologies is to reduce the burden and amount of management required of patients with diabetes. In addition to reducing patient workload, achieving better glucose control and improving hemoglobin A1c (HbA1c) values are essential for reducing the threat of diabetes-related complications further down the road. Current devices come close to reaching these goals, but understanding the unmet needs of patients with diabetes will allow future technologies to achieve these goals more quickly.

A Clinical Overview of Insulin Pump Therapy for the Management of Diabetes: Past, Present, and Future of Intensive Therapy

IN BRIEF Insulin pump therapy is advancing rapidly. This article summarizes the variety of insulin pump technologies available to date and discusses important clinical considerations for each type of technology.

Information and communication technology enabling partnership in person-centred diabetes management: building a theoretical framework from an inductive case study in The Netherlands

OBJECTIVES

The aim of this paper is to construct a theoretical framework for information and communication technology (ICT)-enabled partnership towards diabetes management.

DESIGN

We conducted an inductive case study and held interviews on the development and use of an artificial pancreas (AP) system for diabetes management.

SETTING

The study was carried out in the Netherlands with users of an AP system.

PARTICIPANTS

We interviewed six patients with type 1 diabetes, five healthcare professionals (two medical specialists and three diabetes nurses), and one policy advisor from the Ministry of Health, Welfare and Sport.

RESULTS

We built a new theoretical framework for ICT-enabled person-centred diabetes management, covering the central themes of self-managing the disease, shared analysing of (medical) data and experiencing the partnership. We found that ICT yielded new activities of data sharing and a new role for data professionals in the provision of care as well as contributed to carefree living thanks to the semiautomated management enabled by the device. Our data suggested that to enable the partnership through ICT, organisational adjustments need to be made such as the development of new ICT services and a viable financial model to support these services.

CONCLUSION

The management of diabetes through ICT requires an adjustment of the partnership between persons with the chronic condition and the healthcare professional(s) in such a way that the potential for self-managing the condition by analysing the newly available (medical) data (from the AP system) together leads to an experience of partnership between patients and healthcare professionals.

Performance of Omnipod Personalized Model Predictive Control Algorithm with Moderate Intensity Exercise in Adults with Type 1 Diabetes

Background: The objective of this study was to assess the safety and performance of the Omnipod^® personalized model predictive control (MPC) algorithm with variable glucose setpoints and moderate intensity exercise using an investigational device in adults with type 1 diabetes (T1D). Materials and Methods: A supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient standard treatment phase. Adults aged 18-65 years with T1D and HbA1c between 6.0% and 10.0% were eligible. Subjects completed two moderate intensity exercise sessions of >30 min duration on consecutive days: the first with the glucose set point increased from 130 to 150 mg/dL and the second with a temporary basal rate of 50%, both started 90 min pre-exercise. Primary endpoints were percentage time in hypoglycemia <70 mg/dL and hyperglycemia ≥250 mg/dL. Results: Twelve subjects participated in the study, with (mean ± standard deviation) age 36.5 ± 14.4 years, diabetes duration 21.7 ± 15.7 years, HbA1c 7.6% ± 1.1%, and total daily dose 0.60 ± 0.22 U/kg. Outcomes for the 54-h HCL period were mean glucose: 136 ± 14 mg/dL, percentage time <70 mg/dL: 1.4% ± 1.3%, 70-180 mg/dL: 85.1% ± 9.3%, and ≥250 mg/dL: 1.8% ± 2.4%. In the 12-h period after exercise start, percentage time <70 mg/dL was 1.4% ± 2.7% with the raised glucose set point and 1.6% ± 3.0% with reduced basal rate. The percentage time <70 mg/dL overnight was 0% ± 0% on both study nights. Conclusions: The Omnipod personalized MPC algorithm performed well and was safe during day and night use in response to variable glucose set points and with temporarily raised glucose set point or reduced basal rate 90 min in advance of moderate intensity exercise in adults with T1D.

Technological advances shaping diabetes care

PURPOSE OF REVIEW

To emphasize the current unmet needs for patients with diabetes and evaluate the recent technological advances in the diabetes field and summarize upcoming technologies in diabetes care. This review highlights emerging diabetes technologies and patient-centered diabetes management.

RECENT FINDINGS

A review of the literature showed that there is a clear benefit of using diabetes technologies in diabetes care. Recently, the US Food and Drug Administration (FDA) created a new category of Class II integrated continuous glucose monitoring (iCGM) devices and announced new guidelines to accelerate the approval of future products. With the first-generation hybrid-closed loop, a new era opened in automated insulin delivery systems. Diabetes coaching, apps, and remote monitoring technologies eased access to the providers and increased patient's self-confidence for diabetes management.

SUMMARY

Improvements in diabetes technologies will hopefully overcome unmet needs for patients with diabetes and improve health outcomes. Patients will benefit from the upcoming technologies in their day-to-day diabetes management while providers may monitor patients remotely with ease and efficiently. These developments will decrease diabetes burden, improve quality of life, and open a new era of personalized diabetes care.

Improving patient self-care using diabetes technologies

Diabetes technologies are an unstoppable phenomenon. They offer opportunities to improve patient self-care through empowerment. However, they can be a challenge for both patients and clinicians. Thus, the use of technology may empower or burden. To understand and benefit from the use of diabetes technologies, one must understand the currently unmet needs in diabetes management. These unmet needs call for perspectives beyond glycated hemoglobin and an evaluation of technology solutions. Optimal use of these technologies is necessary to obtain benefits and achieve cost-effectiveness; this process depends on diabetes education and training. This review evaluates clinician and patient perspectives regarding diabetes technologies, followed by an evaluation of technology solutions. Diabetes technology solutions are evaluated according to available results about their effectiveness and their potential to empower people living with diabetes.

Design and Clinical Evaluation of the Interoperable Artificial Pancreas System (iAPS) Smartphone App: Interoperable Components with Modular Design for Progressive Artificial Pancreas Research and Development

BACKGROUND

There is an unmet need for a modular artificial pancreas (AP) system for clinical trials within the existing regulatory framework to further AP research projects from both academia and industry. We designed, developed, and tested the interoperable artificial pancreas system (iAPS) smartphone app that can interface wirelessly with leading continuous glucose monitors (CGM), insulin pump devices, and decision-making algorithms while running on an unlocked smartphone.

METHODS

After algorithm verification, hazard and mitigation analysis, and complete system verification of iAPS, six adults with type 1 diabetes completed 1 week of sensor-augmented pump (SAP) use followed by 48 h of AP use with the iAPS, a Dexcom G5 CGM, and either a Tandem or Insulet insulin pump in an investigational device exemption study. The AP system was challenged by participants performing extensive walking without exercise announcement to the controller, multiple large meals eaten out at restaurants, two overnight periods, and multiple intentional connectivity interruptions.

RESULTS

Even with these intentional challenges, comparison of the SAP phase with the AP study showed a trend toward improved time in target glucose range 70-180 mg/dL (78.8% vs. 83.1%; P = 0.31), and a statistically significant reduction in time below 70 mg/dL (6.1% vs. 2.2%; P = 0.03). The iAPS system performed reliably and showed robust connectivity with the peripheral devices (99.8% time connected to CGM and 94.3% time in closed loop) while requiring limited user intervention.

CONCLUSIONS

The iAPS system was safe and effective in regulating glucose levels under challenging conditions and is suitable for use in unconstrained environments.

Novel Bluetooth-Enabled Tubeless Insulin Pump: Innovating Pump Therapy for Patients in the Digital Age

The Omnipod DASH™ Insulin Management System (Insulet Corp, Billerica, MA) is a discreet, tubeless, wearable insulin pump that holds up to 200 units of U-100 insulin and delivers therapy through customizable basal rates and bolus amounts. This recently FDA-cleared system consists of the insulin pump ("Pod"), which is worn on body and delivers insulin, and the Personal Diabetes Manager (PDM), which is a handheld device used to wirelessly control and monitor the Pod functionality. The PDM can also be paired with the CONTOUR^® NEXT ONE blood glucose (BG) meter (Ascensia Diabetes Care, Basel, Switzerland) to wirelessly receive BG readings. This review provides a detailed description of the Pod and PDM. Key features of the Pod are described, including the novel pump delivery mechanism, waterproof (IP28) housing design, and automated cannula insertion. The technology introduced in the new system, such as touchscreen PDM interface, Bluetooth^® wireless technology, and wireless internet connectivity, is also presented. Last, Omnipod^® Insulin Management System clinical data are reviewed, including early feasibility results for the Omnipod Horizon™ Automated Glucose Control hybrid closed-loop system.