One Year Real-World Use of the Control-IQ Advanced Hybrid Closed-Loop Technology

Safety, metabolic and psychological outcomes of Medtronic MiniMed 670G in children, adolescents and young adults: a systematic review

Hybrid closed loop (HCL) systems are the combination of a pump for insulin delivery and a glucose sensor for continuous glucose monitoring. These systems are managed by an algorithm, which delivers insulin on the basis of the interstitial glucose levels. The MiniMed™ 670G system was the first HCL system available for clinical purpose. In this paper, we reviewed the literature about metabolic and psychological outcomes in children, adolescents and young adults with type 1 diabetes treated with MiniMed™ 670G. Only 30 papers responded to the inclusion criteria and thus were considered. All the papers show that the system is safe and effective in managing glucose control. Metabolic outcomes are available up to 12 months of follow-up; longer study period are lacking. This HCL system may improve HbA1c up to 7.1% and time in range up to 73%. The time spent in hypoglycaemia is almost neglectable. Better improvement in blood glucose control is observed in patients with higher HbA1c at HCL system start and larger daily use of auto-mode functionality.     Conclusion: The Medtronic MiniMed™ 670G is safe and well accepted, without any increase in the burden for patients. Some papers report an improvement in the psychological outcomes, but other papers do not confirm this finding. So far, it significantly improves the management of diabetes mellitus in children, adolescents and young adults. Proper training and support by the diabetes team are mandatory. Studies for a period longer than 1 year would be appreciated to better understand the potentiality of this system. What is Known: • The Medtronic MiniMed^TM 670G is a hybrid closed loop system which combines a continuous glucose monitoring sensor with an insulin pump. • It has been the first hybrid closed loop system available for clinical purpose. Adequate training and patients support play a key role in diabetes management. What is New: • The Medtronic MiniMed^TM 670G may improve HbA1c and CGM metrics up to 1-year of follow-up, but the improvement appears lower than advanced hybrid closed loop systems. This system is effective to prevent hypoglycaemia. • The psychosocial effects remain less understood in terms of improvement of psychosocial outcomes. The system has been considered to provide flexibility and independence by the patients and their caregivers. The workload required to use this system is perceived as a burden by the patients who decrease the use of auto-mode functionality over time.

One-year real-world performance of the DBLG1 closed-loop system: Data from 3706 adult users with type 1 diabetes in Germany

AIM

The Diabeloop Generation 1 (DBLG1) system is an interoperable hybrid closed-loop solution that was commercialized in Germany in March 2021. We report the longitudinal glycaemic outcomes among the first 3706 users in a real-world setting.

METHODS

We performed a retrospective data collection of all consenting adult patients with type 1 diabetes who were equipped in Germany with the DBLG1 system before 30 April 2022, and with a minimum 14 days of closed-loop usage.

RESULTS

In total, 3706 users (41% women, age 45.1 ± 14.5 years) met the inclusion criteria, reaching a mean follow-up of 131.0 ± 85.1 days, an overall 485 600 days of continuous glucose monitoring data, and a median time spent in closed-loop of 95.0% (IQR 89.1-97.4). The median percentage time in range (70-180 mg/dl) was 72.1% (IQR 65.0-78.9); the time below 70 mg/dl was 0.9% (0.5-1.7), the time below 54 mg/dl was 0.1% (0.1-0.3), and the median Glucose Management Index was 7.0% (6.8-7.3). Exploratory analysis of a subset of 2460 patients in whom baseline glycated haemoglobin (HbA1c) was available [7.4% (IQR 6.9-8.0)] showed that the achieved mean time in range was influenced by baseline HbA1c, ranging from 65.8 ± 9.9% (A1c ≥8.5%) to 81.3 ± 6.8% (A1c <6.5%).

CONCLUSION

This large real-world analysis confirms the relevance of the DBLG1 automated insulin delivery solution for the achievement of standards of care in adult patients with type 1 diabetes.

Effectiveness and Safety of an Advanced Hybrid Closed-Loop System in Adolescents and Adults with Type 1 Diabetes Previously Treated with Continuous Subcutaneous Insulin Infusion and Flash Glucose Monitoring

This study aimed to evaluate the effectiveness and safety of the MiniMed™ 780G advanced hybrid closed-loop (AHCL) system in people with type 1 diabetes (T1D) previously treated with continuous subcutaneous insulin infusion combined with flash glucose monitoring in a real-life setting. A total of 47 subjects (mean age 41 ± 13.6 years, 60% females, diabetes duration 28 ± 11 years) were included and switched to an AHCL system. Baseline and 6-month data were analyzed. Time in range 70-180 mg/dL increased from 65.3% at baseline to 73.8% at 6 months. Time in hyperglycemia >180 mg/dL decreased from 26.6% to 19.3%. Time in hypoglycemia <70 mg/dL decreased from 4.6% to 2.3%. The coefficient of variation also decreased from 36% to 31.6%. No episodes of severe hypoglycemia, diabetes ketoacidosis, or diabetes-related hospital admissions occurred. In conclusion, the MiniMed 780G AHCL system enables the safe achievement of recommended glycemic targets in people with T1D after 6 months of use.

Automated insulin delivery systems: from early research to routine care of type 1 diabetes

Automated insulin delivery (AID) systems, so-called closed-loop systems or artificial pancreas, are based upon the concept of insulin supply driven by blood glucose levels and their variations according to body glucose needs, glucose intakes and insulin action. They include a continuous glucose monitoring device which provides a signal to a control algorithm tuning insulin delivery from an infusion pump. The control algorithm is the key of the system since it commands insulin administration in order to maintain blood glucose in a predefined target range and close to a near-normal glucose level. The last two decades have shown dramatic advances toward the use in free life of AID systems for routine care of type 1 diabetes through step-by-step demonstrations of feasibility, safety and efficacy in successive hospital, transitional and outpatient trials. Because of the constraints of pharmacokinetics and dynamics of subcutaneous insulin delivery, the currently available AID systems are all 'hybrid' or 'semi-automated' insulin delivery systems with a need of meal and exercise announcements in order to anticipate rapid glucose variations through pre-meal bolus or pre-exercise reduction of infusion rate. Nevertheless, these AID systems significantly improve time spent in a near-normal range with a reduction of the risk of hypoglycemia and the mental load of managing diabetes in everyday life, representing a milestone in insulin therapy. Expected progression toward fully automated, further miniaturized and integrated, possibly implantable on long-term and more physiological closed-loop systems paves the way for a functional cure of type 1 diabetes.

Diabetes Therapy Podcast: Real-World Data for Glucose Sensing Technologies in Type 1 Diabetes

For people living with type 1 diabetes (T1D), home glucose monitoring has evolved from occasional qualitative urine tests to frequently sampled continuous data providing hundreds of data points per day to inform optimal self-management. Continuous glucose monitoring technologies have a robust evidence base derived from randomized controlled trials (RCTs) over the last 20 years, and are now implemented in routine clinical practice, reflecting their clinical and cost effectiveness. However, while randomized studies are the gold standard, they can be slow to set-up, unrepresentative and do not provide data for efficacy in large, unselected populations. Real-world data can be responsive to rapid product cycles in technologies, provide a large, representative population, and have a lower regulatory burden. In this podcast we discuss the advantages and pitfalls of using real-world data to assess the efficacy of continuous glucose sensing technologies in people with T1D, with reference to examples of real-world data for real-time and intermittently scanned continuous glucose monitoring. Large datasets confirm the RCT data for real-time technologies and additionally provide data for work absenteeism and hospital admissions, as well as showing the impact of advanced technology features that can be difficult to assess in randomized studies. Real-world data for intermittently scanned monitoring also confirm the randomized controlled trial data, provide additional insights not shown in controlled study environments and highlight the importance of health equality. A mature real-world dataset for automated insulin delivery systems is now available and the future of glucose sensing is also discussed.

Advances in Continuous Glucose Monitoring and Integrated Devices for Management of Diabetes with Insulin-Based Therapy: Improvement in Glycemic Control

Continuous glucose monitoring (CGM) technology has evolved over the past decade with the integration of various devices including insulin pumps, connected insulin pens (CIPs), automated insulin delivery (AID) systems, and virtual platforms. CGM has shown consistent benefits in glycemic outcomes in type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) treated with insulin. Moreover, the combined effect of CGM and education have been shown to improve glycemic outcomes more than CGM alone. Now a CIP is the expected future technology that does not need to be worn all day like insulin pumps and helps to calculate insulin doses with a built-in bolus calculator. Although only a few clinical trials have assessed the effectiveness of CIPs, they consistently show benefits in glycemic outcomes by reducing missed doses of insulin and improving problematic adherence. AID systems and virtual platforms made it possible to achieve target glycosylated hemoglobin in diabetes while minimizing hypoglycemia, which has always been challenging in T1DM. Now fully automatic AID systems and tools for diabetes decisions based on artificial intelligence are in development. These advances in technology could reduce the burden associated with insulin treatment for diabetes.

14. Children and Adolescents: 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.

Efficacy of Control-IQ Technology in a General Endocrine Clinic

OBJECTIVE

Recent advances in technology have allowed for the expanded use of hybrid closed-loop insulin pump therapy and automated insulin delivery systems for the management of diabetes mellitus. We assessed the outcomes of introducing Tandem t:slim X2 with the Control-IQ technology in a general endocrine clinic.

METHODS

Data from 66 adults with type 1 (n = 61) and type 2 (n = 5) diabetes mellitus were aggregated for analysis. Patients were either transitioned from traditional insulin pump therapy or multiple daily injection therapy to Tandem t:slim X2 with the Control-IQ technology from January 2020 to June 2021. The assessed clinical end points included changes in time below range, time above range, and time in target range. Changes in hemoglobin A1C before and after Control-IQ technology implementation were noted. The primary outcome was a change in time in target range with the Control-IQ technology.

RESULTS

There was a significant increase in time in target range when comparing pre- and post-Control-IQ technology (49.5% vs 63.3%, P < .0003) values. There was a reduction in time above range (46.8% vs 34.9%, P < .0013), a decrease in time below range (4.0% vs 1.7%, P = .017), and a decrease in hemoglobin A1C after transitioning to the Control-IQ technology (7.7% [61 mmol/mol] vs 7.1% [54 mmol/mol], P < .017). The patient dropout rate was low (7%).

CONCLUSION

The Control-IQ technology system was effective in reducing hyperglycemia while increasing time in target range and decreasing hypoglycemia. This technology is a useful and effective addition to the growing number of automated insulin delivery systems. The clinical outcomes mirror the results found in the key adult pivotal trials.

One-year follow-up comparison of two hybrid closed-loop systems in Italian children and adults with type 1 diabetes

BACKGROUND AND AIMS

Tandem Control-IQ and MiniMed 780G are the main Advanced Hybrid Closed Loop (AHCL) systems currently available in pediatric and adult patients with Type 1 Diabetes (T1D). The aim of our study was to evaluate glycemic control after 1-year of follow-up extending our previous study of 1-month comparison between the two systems.

METHODS

We retrospectively compared clinical and continuous glucose monitoring (CGM) data from the patients included in the previous study which have completed 1-year observation period. The study population consisted of 74 patients, 42 Minimed 780G users and 32 Tandem Control-IQ users. Linear mixed models with random intercept were performed to study the variations over time and the interaction between time and system; Mann-Whitney or T-test were used to compare systems at 1-year.

RESULTS

Both systems have been shown to be effective in maintaining the glycemic improvement achieved one month after starting AHCL. Significant changes over time were observed for TIR, TAR, TAR>250mg/dl, average glucose levels and SD (p<0.001). At 1-year follow-up Minimed 780G obtained better improvement in TIR (p<0.001), TAR (p=0.002), TAR>250mg/dl (p=0.001), average glucose levels (p<0.001). The comparison of the glycemic parameters at 1-year showed a significant superiority of Minimed 780G in terms of TIR (71% vs 68%; p=0.001), TAR (p=0.001), TAR>250 (p=0.009), average glucose levels(p=0.001) and SD (p=0.031).

CONCLUSIONS

The use of AHCL systems led to a significant improvement of glycemic control at 1-month, which is maintained at 1-year follow-up. MiniMed is more effective than Tandem in reaching the International recommended glycemic targets. Continuous training and education in the use of technology is essential to get the best out of the most advanced technological tools.

Type 1 diabetes - What's new in prevention and therapeutic strategies?

Type 1 diabetes (T1D) is an autoimmune disorder, and insulin deficiency is the result of b-cell dysfunction. Treatment of type 1 diabetes requires constant parenteral insulin administration, which can be very burdensome for the patient. Meticulous use of insulin therapy does not protect the patient against complications. Hence, the search for other methods of treatment as well as ways of preventing the onset of diabetes has been ongoing for a long time. The main obstacle in the implementation of the prevention task is the need to identify people at risk of developing diabetes before the start of autoimmunity. It seems that primary prevention is still unrealistic at the moment, because we do not know all the factors leading to the activation of autoimmunity processes. Research on the use of late secondary prevention in people who develop glucose tolerance disorders or in the early period after the onset of type 1 diabetes are at the most advanced stage. Gene therapy is another attempt at an alternative treatment and prevention of type 1 diabetes and still requires further research. Recent years have brought a lot of information about the nature of type 1 diabetes and the mechanisms leading to its development. However, it has not yet been established what factors decide about the initiation of autoimmunity and what determines the dynamics of these processes.

Biobehavioral Changes Following Transition to Automated Insulin Delivery: A Large Real-life Database Analysis

OBJECTIVE

To document glycemic and user-initiated bolus changes following transition from predictive low glucose suspend (PLGS) system to automated insulin delivery (AID) system during real-life use.

RESEARCH DESIGN AND METHODS

We conducted analysis of 2,329,166 days (6,381 patient-years) of continuous glucose monitoring (CGM) and insulin therapy data for 19,354 individuals with type 1 Diabetes, during 1-month PLGS use (Basal-IQ technology) followed by 3-month AID use (Control-IQ technology). Baseline characteristics are as follows: 55.4% female, age (median/quartiles/range) 39/19-58/1-92 years, mean ± SD glucose management indicator (GMI) 7.5 ± 0.8. Primary outcome was time in target range (TIR) (70-180 mg/dL). Secondary outcomes included CGM-based glycemic control metrics and frequency of user-initiated boluses.

RESULTS

Compared with PLGS, AID increased TIR on average from 58.4 to 70.5%. GMI and percent time above and below target range improved as well: from 7.5 to 7.1, 39.9 to 28.1%, and 1.66 to 1.46%, respectively; all P values <0.0001. Stratification of outcomes by age and baseline GMI revealed clinically significant differences. Glycemic improvements were most pronounced in those <18 years old (TIR improvement 14.0 percentage points) and those with baseline GMI >8.0 (TIR improvement 13.2 percentage points). User-initiated correction boluses decreased from 2.7 to 1.8 per day, while user-initiated meal boluses remained stable at 3.6 to 3.8 per day.

CONCLUSIONS

Observed in real life of >19,000 individuals with type 1 diabetes, transitions from PLGS to AID resulted in improvement of all glycemic parameters, equivalent to improvements observed in randomized clinical trials, and reduced user-initiated boluses. However, glycemic and behavioral changes with AID use may differ greatly across different demographic and clinical groups.

Essential Continuous Glucose Monitoring Metrics: The Principal Dimensions of Glycemic Control in Diabetes

Background: With the proliferation of continuous glucose monitoring (CGM), a number of metrics were developed to assess quality of glycemic control. Many of them are highly correlated. Thus, we aim to identify the principal dimensions of glycemic control-a minimal set of metrics, necessary and sufficient for comprehensive assessment of diabetes management. Methods: Seventy-five thousand five hundred sixty-three 2-week CGM profiles recorded in six studies by 790 individuals with type 1 or type 2 diabetes were used to compute mean glucose (MG), percentage time >180 mg/dL (TAR), >250 mg/dL (TAR2), <70 mg/dL (TBR), <54 mg/dL (TBR2), and coefficient of variation (CV). The true dimensionality of the glycemic-metric space was identified in a training set (53,380 profiles) and validated in an independent test set (22,183 profiles). Results: Correlation analysis identified two blocks of metrics-(MG, TAR, TAR2) and (TBR, TBR2, CV)-each with high internal correlation, but insignificant between-block correlation, suggesting that the true dimensionality of the glycemic-metric space is 2. Principal component analysis confirmed two essential metrics quantifying exposure to hyperglycemia (i.e., treatment efficacy) and risk for hypoglycemia (i.e., treatment safety), and explaining ∼90% of the variance in the training and test data. Conclusion: Two essential metrics, treatment efficacy and treatment safety, are necessary and sufficient to characterize glycemic control in diabetes. Thus, quantitatively, diabetes treatment optimization is reduced to a two-dimensional problem, meaning that minimizing both exposure to hyperglycemia and risk for hypoglycemia will lead to improvement in any other metric of glycemic control.

Real-World Evidence Supporting Tandem Control-IQ Hybrid Closed-Loop Success in the Medicare and Medicaid Type 1 and Type 2 Diabetes Populations

Background: The Tandem Control-IQ (CIQ) system has demonstrated significant glycemic improvements in large randomized controlled and real-world trials. Use of this system is lower in people with type 1 diabetes (T1D) government-sponsored insurance and those with type 2 diabetes (T2D). This analysis aimed to evaluate the performance of CIQ in these groups. Methods and Materials: A retrospective analysis of CIQ users was performed. Users age ≥6 years with a t:slim X2 Pump and >30 days of continuous glucose monitoring (CGM) data pre-CIQ and >30 days post-CIQ technology initiation were included. Results: A total of 4243 Medicare and 1332 Medicaid CIQ users were analyzed among whom 5075 had T1D and 500 had T2D. After starting CIQ, the Medicare beneficiaries group saw significant improvement in time in target range 70-180 mg/dL (TIR; 64% vs. 74%; P < 0.0001), glucose management index (GMI; 7.3% vs. 7.0%; P < 0.0001), and the percentage of users meeting American Diabetes Association (ADA) CGM Glucometrics Guidelines (12.8% vs. 26.3%; P < 0.0001). The Medicaid group also saw significant improvement in TIR (46% vs. 60%; P < 0.0001), GMI (7.9% vs. 7.5%; P < 0.0001), and percentage meeting ADA guidelines (5.7% vs. 13.4%; P < 0.0001). Patients with T2D and either insurance saw significant glycemic improvements. Conclusions: The CIQ system was effective in the Medicare and Medicaid groups in improving glycemic control. The T2D subgroup also demonstrated improved glycemic control with CIQ use. Glucometrics achieved in this analysis are comparable with those seen in previous randomized controlled clinical trials with the CIQ system.

Closed-loop insulin delivery: update on the state of the field and emerging technologies

INTRODUCTION

Over the last five years, closed-loop insulin delivery systems have transitioned from research-only to real-life use. A number of systems have been commercialized and are increasingly used in clinical practice. Given the rapidity of new developments in the field, understanding the capabilities and key similarities and differences of current systems can be challenging. This review aims to provide an update on the state of the field of closed-loop insulin delivery systems, including emerging technologies.

AREAS COVERED

We summarize key clinical safety and efficacy evidence of commercial and emerging insulin-only hybrid closed-loop systems for type 1 diabetes. A literature search was conducted and clinical trials using closed-loop systems during free-living conditions were identified to report on safety and efficacy data. We comment on emerging technologies and adjuncts for closed-loop systems, as well as non-technological priorities in closed-loop insulin delivery.

EXPERT OPINION

Commercial hybrid closed-loop insulin delivery systems are efficacious, consistently improving glycemic control when compared to standard therapy. Challenges remain in widespread adoption due to clinical inertia and the lack of resources to embrace technological developments by health care professionals.

Outpatient Randomized Crossover Comparison of Zone Model Predictive Control Automated Insulin Delivery with Weekly Data Driven Adaptation Versus Sensor-Augmented Pump: Results from the International Diabetes Closed-Loop Trial 4

Background: Automated insulin delivery (AID) systems have proven effective in increasing time-in-range during both clinical trials and real-world use. Further improvements in outcomes for single-hormone (insulin only) AID may be limited by suboptimal insulin delivery settings. Methods: Adults (≥18 years of age) with type 1 diabetes were randomized to either sensor-augmented pump (SAP) (inclusive of predictive low-glucose suspend) or adaptive zone model predictive control AID for 13 weeks, then crossed over to the other arm. Each week, the AID insulin delivery settings were sequentially and automatically updated by an adaptation system running on the study phone. Primary outcome was sensor glucose time-in-range 70-180 mg/dL, with noninferiority in percent time below 54 mg/dL as a hierarchical outcome. Results: Thirty-five participants completed the trial (mean age 39 ± 16 years, HbA1c at enrollment 6.9% ± 1.0%). Mean time-in-range 70-180 mg/dL was 66% with SAP versus 69% with AID (mean adjusted difference +2% [95% confidence interval: -1% to +6%], P = 0.22). Median time <70 mg/dL improved from 3.0% with SAP to 1.6% with AID (-1.5% [-2.4% to -0.5%], P = 0.002). The adaptation system decreased initial basal rates by a median of 4% (-8%, 16%) and increased initial carbohydrate ratios by a median of 45% (32%, 59%) after 13 weeks. Conclusions: Automated adaptation of insulin delivery settings with AID use did not significantly improve time-in-range in this very well-controlled population. Additional study and further refinement of the adaptation system are needed, especially in populations with differing degrees of baseline glycemic control, who may show larger benefits from adaptation.

Long-term outcomes of an advanced hybrid closed-loop system: A focus on different subpopulations

BACKGROUND

The long-term benefit provided by advanced hybrid closed-loop (AHCL) systems needs to be assessed in general populations and specific subpopulations.

METHODS

A prospective evaluation of subjects initiating the AHCL system 780G was performed. Time in range (70-180 mg/dl) (TIR), <70 mg/dl, <54 mg/dl, >180 mg/dl and >250 mg/dl were compared, at baseline and after one year, in different subpopulations, according to previous treatment (pump vs MDI), age (> or ≤25 years old) and hypoglycaemia risk at baseline.

RESULTS

135 subjects were included (age: 35 ± 15 years, 64 % females, diabetes duration: 21 ± 12 years). An increase in TIR was found, from 67.26 ± 11.80 % at baseline to 77.41 ± 8.85 % after one year (p < 0.001). All the subgroups showed a significant improvement in TIR, time > 180 mg/dl and >250 mg/dl. At the 1-year evaluation, no significant differences were found, between previous pump users and MDI subjects. Children and young adults had a lower time < 70 mg/dl than adults. Subjects with a high risk of hypoglycaemia at baseline had a higher time spent at <70 mg/dl and <54 mg/dl than low-risk individuals.

CONCLUSION

The initial benefit provided by the AHCL system is sustained in the long term. MDI subjects obtain the same outcomes as subjects with pump experience.

One-Year Real-World Study on Comparison among Different Continuous Subcutaneous Insulin Infusion Devices for the Management of Pediatric Patients with Type 1 Diabetes: The Supremacy of Hybrid Closed-Loop Systems

Since their advent in daily clinical practice, continuous subcutaneous insulin infusion (CSII) systems have been increasingly improved, leading to a high percentage of both adult and pediatric patients with diabetes now using insulin pumps. Different types of CSII systems are currently available, which are characterized by different settings and technical features. This longitudinal observational study aims to evaluate real-word glycemic outcomes in children and adolescents with type 1 diabetes using three different CSII devices: hybrid closed-loop (HCL) systems, predictive low glucose (PLGS) systems, and non-automated insulin pumps. The secondary objective was to identify clinical variables that may significantly influence the achievement of therapeutic goals in our study cohort. One-hundred-and-one patients on CSII therapy attending our pediatric diabetes center were enrolled. When compared with the non-automated group, patients using HCL systems showed higher levels of time in target glucose range (p = 0.003) and lower glucose variability (p = 0.008). Similarly, we found significantly better glucose metrics in HCL users in comparison to PLGS patients (time in range p = 0.008; coefficient of variation p = 0.009; time above 250 mg/dL p = 0.007). Multiple linear regression models showed that HCL systems (time in range p < 0.001) and high daily percentage of glycemic sensor use (time in range p = 0.031) are predictors for good glycemic control. The introduction and increasing availability of novel technologies for diabetes represent a promising strategy to improve glycemic control and quality of life in pediatric patients with type 1 diabetes. Our real-world data confirm the superiority of HCL systems in terms of improvement of time spent in the target glucose range, prevention of hypoglycemia, and reduction of glycemic variability.

Machine Learning Approach for Care Improvement of Children and Youth with Type 1 Diabetes Treated with Hybrid Closed-Loop System

Type 1 diabetes is a disease affecting beta cells of the pancreas and it’s responsible for a decreased insulin secretion, leading to an increased blood glucose level. The traditional method for glucose treatment is based on finger-stick measurement of the blood glucose concentration and consequent manual insulin injection. Nowadays insulin pumps and continuous glucose monitoring systems are replacing them, being simpler and automatized. This paper focuses on analyzing and improving the knowledge about which Machine Learning algorithms can work best with glycaemic data and tries to find out the relation between insulin pump settings and glycaemic control. The dataset is composed of 90 days of recordings taken from 16 children and adolescents. Three Machine Learning approaches, two for classification, Logistic Regression (LR) and Random Forest (RL), and one for regression, Multivariate Linear Regression (MLR), have been used for the purpose. Specifically, the pump settings analysis was performed based on the Time In Range (TIR) computation and comparison consequent to pump setting changes. RF and MLR have shown the best results, while, for the settings’ analysis, the data show a discrete correlation between changes and TIRs. This study provides an interesting closer look at the data recorded by the insulin pump and a suitable starting point for a thorough and complete analysis of them.

Barriers and Facilitators to Diabetes Device Adoption for People with Type 1 Diabetes

PURPOSE OF REVIEW

Diabetes technology (insulin pumps, continuous glucose monitoring, automated insulin delivery systems) has advanced significantly and provides benefits to the user. This article reviews the current barriers to diabetes device adoption and sustained use, and outlines the known and potential facilitators for increasing and sustaining device adoption.

RECENT FINDINGS

Barriers to diabetes device adoption continue to exist at the system-, provider-, and individual-level. Known facilitators to promote sustained adoption include consistent insurance coverage, support for providers and clinics, structured education and support for technology users, and device user access to support as needed (e.g., through online resources). Systemic barriers to diabetes device adoption persist while growing evidence demonstrates the increasing benefits of newest devices and systems. There are ongoing efforts to develop evidence-based structured education programs to support device adoption and sustained use.

Comparison of MiniMed 780G system performance in users aged younger and older than 15 years: Evidence from 12 870 real-world users

AIM

To investigate real-world glycaemic outcomes and goals achieved by users of the MiniMed 780G advanced hybrid closed loop (AHCL) system aged younger and older than 15 years with type 1 diabetes (T1D).

MATERIALS AND METHODS

Data uploaded by MiniMed 780G system users from 27 August 2020 to 22 July 2021 were aggregated and retrospectively analysed based on self-reported age (≤15 years and >15 years) for three cohorts: (a) post-AHCL initiation, (b) 6-month longitudinal post-AHCL initiation and (c) pre- versus post-AHCL initiation. Analyses included mean percentage of time spent in AHCL and at sensor glucose ranges, insulin delivered and the proportion of users achieving recommended glucose management indicator (GMI < 7.0%) and time in target range (TIR 70-180 mg/dl > 70%) goals.

RESULTS

Users aged 15 years or younger (N = 3211) achieved a GMI of 6.8% ± 0.3% and TIR of 73.9% ± 8.7%, while spending 92.7% of time in AHCL. Users aged older than 15 years (N = 8874) achieved a GMI of 6.8% ± 0.4% and TIR of 76.5% ± 9.4% with 92.3% of time in AHCL. Time spent at less than 70 mg/dl was within the recommended target of less than 4% (3.2% and 2.3%, respectively). Similar outcomes were observed for each group (N = 790 and N = 1642, respectively) in the first month following AHCL initiation, and were sustained over the 6-month observation period.

CONCLUSIONS

This real-world analysis shows that more than 75% of users with T1D aged 15 years or younger using the MiniMed 780G system achieved international consensus-recommended glycaemic control, mirroring the achievements of the population aged older than 15 years.

A Reinforcement Learning Based System for Blood Glucose Control without Carbohydrate Estimation in Type 1 Diabetes: In Silico Validation

Type 1 Diabetes (T1D) is a chronic autoimmune disease, which requires the use of exogenous insulin for glucose regulation. In current hybrid closed-loop systems, meal entry is manual which adds cognitive burden to the persons living with T1D. In this study, we proposed a control system based on Proximal Policy Optimisation (PPO) that controls both basal and bolus insulin infusion and only requires meal announcement, thus eliminating the need for carbohydrate estimation. We evaluated the system on a challenging meal scenario, using an open-source simulator based on the UVA/Padova 2008 model and achieved a mean Time in Range value of 65% for the adult subject cohort, while maintaining a moderate hypoglycemic and hyperglycemic risk profile. The approach shows promise and welcomes further research towards the translation to a real-life artificial pancreas. Clinical relevance- This was an in-silico analysis towards the development of an autonomous artificial pancreas system for glucose control. The proposed system show promise in eliminating the need for estimating the carbohydrate content in meals.

Automated Insulin Delivery with SGLT2i Combination Therapy in Type 1 Diabetes

Background: Use of sodium-glucose cotransporter 2 inhibitors (SGLT2i) as adjunct therapy to insulin in type 1 diabetes (T1D) has been previously studied. In this study, we present data from the first free-living trial combining low-dose SGLT2i with commercial automated insulin delivery (AID) or predictive low glucose suspend (PLGS) systems. Methods: In an 8-week, randomized, controlled crossover trial, adults with T1D received 5 mg/day empagliflozin (EMPA) or no drug (NOEMPA) as adjunct to insulin therapy. Participants were also randomized to sequential orders of AID (Control-IQ) and PLGS (Basal-IQ) systems for 4 and 2 weeks, respectively. The primary endpoint was percent time-in-range (TIR) 70-180 mg/dL during daytime (7:00-23:00 h) while on AID (NCT04201496). Findings: A total of 39 subjects were enrolled, 35 were randomized, 34 (EMPA; n = 18 and NOEMPA n = 16) were analyzed according to the intention-to-treat principle, and 32 (EMPA; n = 16 and NOEMPA n = 16) completed the trial. On AID, EMPA versus NOEMPA had higher daytime TIR 81% versus 71% with a mean estimated difference of +9.9% (confidence interval [95% CI] 0.6-19.1); p = 0.04. On PLGS, the EMPA versus NOEMPA daytime TIR was 80% versus 63%, mean estimated difference of +16.5% (95% CI 7.3-25.7); p < 0.001. One subject on SGLT2i and AID had one episode of diabetic ketoacidosis with nonfunctioning insulin pump infusion site occlusion contributory. Interpretation: In an 8-week outpatient study, addition of 5 mg daily empagliflozin to commercially available AID or PLGS systems significantly improved daytime glucose control in individuals with T1D, without increased hypoglycemia risk. However, the risk of ketosis and ketoacidosis remains. Therefore, future studies with SGLT2i will need modifications to closed-loop control algorithms to enhance safety.

The Effect of Control IQ Hybrid Closed Loop Technology on Glycemic Control in Adolescents and Adults with Cystic Fibrosis-Related Diabetes

Background: Cystic fibrosis-related diabetes (CFRD) is associated with pulmonary decline, compromised nutritional status, and earlier mortality. Although diabetes technology is increasingly being used in individuals with CFRD, there is a paucity of data investigating the impact of hybrid closed loop (HCL) technology on glycemia in this patient population. Materials and Methods: In this multicenter retrospective study of 13 adults and adolescents with CFRD, 14 days of continuous glucose monitor data were analyzed at baseline, 1 and 3 months after transition to the Tandem t:slim X2 pump with Control IQ™ technology, a HCL system. Results: Control IQ initiation was associated with a significant increase in % time in target range (70-180 mg/dL), as well as decreases in average glucose, % time in hyperglycemic ranges (% time >180 mg/dL, % time >250 mg/dL), and glycemic variability (standard deviation, coefficient of variation). There was no significant change in % time in hypoglycemia ranges (% time <54 mg/dL, % time <70 mg/dL). Conclusions: To our knowledge, this is the first study to report a beneficial effect of Food and Drug Administration (FDA)-approved HCL technology on glycemia in adults and adolescents with CFRD to date. Future studies are needed to understand the potential long-term glycemic benefits of HCL devices and to explore the impact of this technology on heath-related quality of life, pulmonary function, nutritional status, and mortality.

Feasibility study of a prototype extended-wear insulin infusion set in adults with type 1 diabetes

AIM

To assess the feasibility of a prototype insulin infusion set (IIS) for extended wear in adults with type 1 diabetes.

MATERIALS AND METHODS

The prototype Capillary Biomedical investigational extended-wear IIS (CBX IIS) incorporates a soft, flexible, reinforced kink-resistant angled nylon-derivative cannula with one distal and three proximal ports to optimize insulin delivery. Twenty adult participants with type 1 diabetes established on insulin pump therapy used the CBX IIS for two 7-day test periods while wearing a Dexcom G5 continuous glucose monitor.

RESULTS

Participants were able to wear the CBX IIS for an average of 6.6 ± 1.4 days. Eighty-eight percent (36 of 41) of sets were worn for 7 days. No serious adverse events were reported. Five infusion sets failed prematurely because of: unresolvable hyperglycaemia (three); hyperglycaemia with elevated ketones (one); or infection (one). Median time in range (3.9-10.0 mmol/L) was 62% (54-76). Average glucose levels per day of infusion set wear showed a statistically significant increase over time (p < .001).

CONCLUSIONS

Our preliminary observations confirm the tolerability of the prototype CBX IIS for extended wear, albeit with a deterioration in glucose control after the third day.

Review of Automated Insulin Delivery Systems for Type 1 Diabetes and Associated Time in Range Outcomes

Automated insulin delivery (AID) systems play an important role in the management of type 1 diabetes mellitus (T1DM). These systems include three components: a continuous glucose monitor (CGM), an insulin pump and an algorithm that adjusts the pump based on the CGM sensor glucose readings. They are not fully automated and still require the user to administer bolus insulin doses for food. Some AID systems have automatic correction boluses, while others only have automatic basal or background insulin adjustments. As CGM has become more accurate and the technology has evolved, AID systems have demonstrated improved glycaemic outcomes. The clinical evaluation of AID systems in randomized controlled trials and real-world studies have shown their utility in helping glycaemic management. In this review, we compare AID systems that are commercially available in the US and summarize the literature, with a special focus on time in range in T1DM. The review also discusses new AID systems on the horizon and explores considerations for personalized care.

The Psychological Implications of Automated Insulin Delivery Systems in Type 1 Diabetes Care

Automated insulin delivery (AID) systems have brought important glycemic benefits to type 1 diabetes management. The present paper provides an overview of their psychological implications. Trials and real-world observational studies report improvements in diabetes-specific quality of life, with qualitative work describing reduced management burden, increased flexibility and improved relationships. Not all experiences are positive, however, evidenced by dropping algorithm use soon after device initiation. Apart from finance and logistics, reasons for discontinuation include technology frustrations, wear-related issues and unmet glycemic and work load expectations. New challenges include distrust in proper AID functioning, overreliance and deskilling, compensatory behaviors to override or trick the system and optimize time in range, and concerns related to wearing multiple devices on the body. Research efforts may focus on incorporating a diversity perspective, updating existing person-reported outcome measures according to new technology developments, addressing implicit or explicit health professional bias in technology access, examining the merits of incorporating stress reactivity in the AID algorithm, and developing concrete approaches for psychological counseling and support related to technology use. An open dialogue with health professionals and peers about expectations, preferences and needs may foster the collaboration between the person with diabetes and the AID system.

Current Status and Emerging Options for Automated Insulin Delivery Systems

Combining technologies including rapid insulin analogs, insulin pumps, continuous glucose monitors, and control algorithms has allowed for the creation of automated insulin delivery (AID) systems. These systems have proven to be the most effective technology for optimizing metabolic control and could hold the key to broadly achieving goal-level glycemic control for people with type 1 diabetes. The use of AID has exploded in the past several years with several options available in the United States and even more in Europe. In this article, we review the largest studies involving these AID systems, and then examine future directions for AID with an emphasis on usability.

Real-world evidence on clinical outcomes of people with type 1 diabetes using open-source and commercial automated insulin dosing systems: A systematic review

AIMS

Several commercial and open-source automated insulin dosing (AID) systems have recently been developed and are now used by an increasing number of people with diabetes (PwD). This systematic review explored the current status of real-world evidence on the latest available AID systems in helping to understand their safety and effectiveness.

METHODS

A systematic review of real-world studies on the effect of commercial and open-source AID system use on clinical outcomes was conducted employing a devised protocol (PROSPERO ID 257354).

RESULTS

Of 441 initially identified studies, 21 published 2018-2021 were included: 12 for Medtronic 670G; one for Tandem Control-IQ; one for Diabeloop DBLG1; two for AndroidAPS; one for OpenAPS; one for Loop; three comparing various types of AID systems. These studies found that several types of AID systems improve Time-in-Range and haemoglobin A_1c (HbA_1c ) with minimal concerns around severe hypoglycaemia. These improvements were observed in open-source and commercially developed AID systems alike.

CONCLUSIONS

Commercially developed and open-source AID systems represent effective and safe treatment options for PwD of several age groups and genders. Alongside evidence from randomized clinical trials, real-world studies on AID systems and their effects on glycaemic outcomes are a helpful method for evaluating their safety and effectiveness.

Analysis of "Glycemic Outcomes During Real-World Hybrid Closed-Loop System Use by Individuals With Type 1 Diabetes in the United States"

In an article in the Journal of Diabetes Science and Technology, Arunachalum et al retrospectively analyzed glycemic outcomes, regarding the use of hybrid closed-loop (HCL) systems in individuals with type-1 diabetes (T1D) in the United States in a real-world evidence (RWE) setting. In clinical trials, diabetes technology has shown to improve time in range (TIR) as well as other glucose metrics. In the light of increasing the use of diabetes technology in the T1D population, why do we not see improvement in clinical outcomes? Is it cost-effective to increase the use diabetes technology? Does access to diabetes technology vary in the United States? There is a need for additional clinical studies evaluating the effectiveness of diabetes technology in T1D including health economic aspects.

Glycemic Outcomes During Real-World Hybrid Closed-Loop System Use by Individuals With Type 1 Diabetes in the United States

BACKGROUND

Glycemic outcomes during real-world hybrid closed-loop (HCL) system use by individuals with type 1 diabetes, in the United States, were retrospectively analyzed.

METHODS

Hybrid closed-loop system data voluntarily uploaded to Carelink™ personal software from March 2017 to November 2020 by individuals (aged ≥7 years) using the MiniMed™ 670G system and having ≥10 days of continuous glucose monitoring data after initiating Auto Mode were assessed. Glycemic outcomes including the mean glucose management indicator (GMI), sensor glucose (SG), percentage of time spent in (TIR), below (TBR), and above (TAR) target range (70-180 mg/dL) were analyzed. Outcomes were also analyzed in a subgroup of users per baseline GMI of <7% versus >8%.

RESULTS

The overall cohort (N = 123 355 users, with a mean of 87.9% of time in Auto Mode) had a GMI of 7.0% ± 0.4%, TIR of 70.4% ± 11.2%, TBR <70 mg/dL of 2.2% ± 2.1% and TAR>180 mg/dL of 27.5% ± 11.6%, post-Auto Mode initiation. Compared with pre-Auto Mode initiation, users (N = 52 941, 88.6% of time in Auto Mode) had a GMI that decreased from 7.3% ± 0.6% to 7.1% ± 0.5% (P < .001), TIR that increased from 61.5% ± 15.1% to 68.1% ± 11.9% (P < .001), TAR>180 mg/dL that decreased from 36.3% ± 15.7% to 29.8% ± 12.2% (P < .001) and TBR<70 mg/dL that decreased from 2.11 ± 2.4 to 2.07% ± 2.25% (P = .002). While all metrics statistically improved for the baseline GMI >8.0% group, the baseline GMI <7.0% group had unchanged TIR (77.4% ± 7.4% to 77.5% ± 8.0%, P = .456) and TAR>180 mg/dL that increased (19.2 ± 6.7 to 19.6 ± 7.9%, p < 0.001).

CONCLUSION

Real-world HCL system use in the U.S. demonstrated overall glycemic control that trended similarly with the system pivotal trial outcomes and previous real-world system use analyses.

External validation of a classifier of daily continuous glucose monitoring (CGM) profiles

As continuous glucose monitoring (CGM) sensors generate ever increasing amounts of CGM data, the need for methods to simplify the storage and analysis of this data becomes increasingly important. Lobo et al. developed a classifier of daily CGM profiles as an initial step in addressing this need. The classifier has several important applications including, but not limited to, data compression, data encryption, and indexing of databases. While the classifier has already successfully classified 99.0% of the 42,595 daily CGM profiles in a Test Set, this work presents an external validation using an external validation set (EVal Set) derived from 8 publicly available data sets. The Test Set and the EVal Set differ in terms of (but not limited to) demographics, data collection time periods, and data collection geographies. The classifier successfully classified 98.2% of the 137,030 daily CGM profiles in the EVal Set. Furthermore, each of the 483 distinct groups of classified daily CGM profiles from the EVal Set retains the same clinical characteristics as the corresponding group from the Test Set, as desired. Finally, the set of unclassified daily CGM profiles from the EVal Set retains the same statistical characteristics as the set of unclassified daily CGM profiles from the Test Set, as desired. These results establish the robustness and generalizability of the classifier: the performance of the classifier is unchanged despite the marked differences between the Test Set and the EVal Set.

Cambridge hybrid closed-loop algorithm in children and adolescents with type 1 diabetes: a multicentre 6-month randomised controlled trial

BACKGROUND

Closed-loop insulin delivery systems have the potential to address suboptimal glucose control in children and adolescents with type 1 diabetes. We compared safety and efficacy of the Cambridge hybrid closed-loop algorithm with usual care over 6 months in this population.

METHODS

In a multicentre, multinational, parallel randomised controlled trial, participants aged 6-18 years using insulin pump therapy were recruited at seven UK and five US paediatric diabetes centres. Key inclusion criteria were diagnosis of type 1 diabetes for at least 12 months, insulin pump therapy for at least 3 months, and screening HbA1c levels between 53 and 86 mmol/mol (7·0-10·0%). Using block randomisation and central randomisation software, we randomly assigned participants to either closed-loop insulin delivery (closed-loop group) or to usual care with insulin pump therapy (control group) for 6 months. Randomisation was stratified at each centre by local baseline HbA1c. The Cambridge closed-loop algorithm running on a smartphone was used with either (1) a modified Medtronic 640G pump, Medtronic Guardian 3 sensor, and Medtronic prototype phone enclosure (FlorenceM configuration), or (2) a Sooil Dana RS pump and Dexcom G6 sensor (CamAPS FX configuration). The primary endpoint was change in HbA1c at 6 months combining data from both configurations. The primary analysis was done in all randomised patients (intention to treat). Trial registration ClinicalTrials.gov, NCT02925299.

FINDINGS

Of 147 people initially screened, 133 participants (mean age 13·0 years [SD 2·8]; 57% female, 43% male) were randomly assigned to either the closed-loop group (n=65) or the control group (n=68). Mean baseline HbA1c was 8·2% (SD 0·7) in the closed-loop group and 8·3% (0·7) in the control group. At 6 months, HbA1c was lower in the closed-loop group than in the control group (between-group difference -3·5 mmol/mol (95% CI -6·5 to -0·5 [-0·32 percentage points, -0·59 to -0·04]; p=0·023). Closed-loop usage was low with FlorenceM due to failing phone enclosures (median 40% [IQR 26-53]), but consistently high with CamAPS FX (93% [88-96]), impacting efficacy. A total of 155 adverse events occurred after randomisation (67 in the closed-loop group, 88 in the control group), including seven severe hypoglycaemia events (four in the closed-loop group, three in the control group), two diabetic ketoacidosis events (both in the closed-loop group), and two non-treatment-related serious adverse events. There were 23 reportable hyperglycaemia events (11 in the closed-loop group, 12 in the control group), which did not meet criteria for diabetic ketoacidosis.

INTERPRETATION

The Cambridge hybrid closed-loop algorithm had an acceptable safety profile, and improved glycaemic control in children and adolescents with type 1 diabetes. To ensure optimal efficacy of the closed-loop system, usage needs to be consistently high, as demonstrated with CamAPS FX.

FUNDING

National Institute of Diabetes and Digestive and Kidney Diseases.

Glycemic outcomes of Advanced Hybrid Closed Loop system in children and adolescents with Type 1 Diabetes, previously treated with Multiple Daily Injections (MiniMed 780G system in T1D individuals, previously treated with MDI)

BACKGROUND

The objective of this study was to evaluate the glycemic outcomes in children and adolescents with Type 1 Diabetes (T1D) previously treated with Multiple Daily Injections (MDI) using a structured initiation protocol for the Advanced Hybrid Closed Loop (AHCL) Minimed 780G insulin pump system.

METHODS

In this prospective open label single-arm, single-center, clinical investigation, we recruited children and adolescents (aged 7-17 years) with T1D on MDI therapy and HbA1c below 12.5%. All participants followed a 10-day structured initiation protocol which included 4 steps: step 1: AHCL system assessment; step 2: AHCL system training; step 3: Sensor augmented pump therapy (SAP) for 3 days; step 4: AHCL system use for 12 weeks, successfully completing the training from MDI to AHCL in 10 days. The primary outcome of the study was the change in the time spent in the target in range (TIR) of 70-180 mg/dl and HbA1c from baseline (MDI + CGM, 1 week) to study phase (AHCL, 12 weeks). The paired student t-test was used for statistical analysis and a value < 0.05 was considered statistically significant.

RESULTS

Thirty-four participants were recruited and all completed the 12 weeks study. TIR increased from 42.1 ± 18.7% at baseline to 78.8 ± 6.1% in the study phase (p < 0.001). HbA1c decreased from 8.6 ± 1.7% (70 ± 18.6 mmol/mol) at baseline, to 6.5 ± 0.7% (48 ± 7.7 mmol/mol) at the end of the study (p = 0.001). No episodes of severe hypoglycemia or DKA were reported.

CONCLUSION

Children and adolescents with T1D on MDI therapy who initiated the AHCL system following a 10-days structured protocol achieved the internationally recommended goals of glycemic control with TIR > 70% and a HbA1c of < 7%.

Predicting Success with a First-Generation Hybrid Closed-Loop Artificial Pancreas System Among Children, Adolescents, and Young Adults with Type 1 Diabetes: A Model Development and Validation Study

Background: Hybrid Closed-Loop (HCL) systems aid individuals with type 1 diabetes in improving glycemic control; however, sustained use over time has not been consistent for all users. This study developed and validated prognostic models for successful 12-month use of the first commercial HCL system based on baseline and 1- or 3-month data. Methods and Materials: Data from participants at the Barbara Davis Center (N = 85) who began use of the MiniMed 670G HCL were used to develop prognostic models using logistic regression and Lasso model selection. Candidate factors included sex, age, duration of diabetes, baseline hemoglobin A1c (HbA1c), race, ethnicity, insurance status, history of insulin pump and continuous glucose monitor use, 1- or 3-month Auto Mode use, boluses per day, and time in range (TIR; 70-180 mg/dL), and scores on behavioral questionnaires. Successful use of HCL was predefined as Auto Mode use ≥60%. The 3-month model was then externally validated against a sample from Stanford University (N = 55). Results: Factors in the final model included baseline HbA1c, sex, ethnicity, 1- or 3-month Auto Mode use, Boluses per Day, and TIR. The 1- and 3-month prognostic models had very good predictive ability with area under the curve values of 0.894 and 0.900, respectively. External validity was acceptable with an area under the curve of 0.717. Conclusions: Our prognostic models use clinically accessible baseline and early device-use factors to identify risk for failure to succeed with 670G HCL technology. These models may be useful to develop targeted interventions to promote success with new technologies.

Switching from predictive low glucose suspend to advanced hybrid closed loop control: Effects on glucose control and patient reported outcomes

AIMS

Automated insulin delivery improves glucose control. Aim of this study was to compare in real life the effects on glucose control and patient reported outcomes of an advanced hybrid closed loop system (Control-IQ), versus a simpler system with predictive low glucose suspend function (Basal-IQ).

METHODS

Thirty-one type 1 diabetic subjects were studied during Basal-IQ and after switching to Control-IQ. Variables analyzed were time spent in range (70-180 mg/dL), in tight range (70-140 mg/dL), above range (>180 mg/dL), below range (<70 mg/dL), mean glucose, coefficient of variation and glycated hemoglobin. Questionnaires were administered regarding therapy satisfaction (Diabetes Treatment Satisfaction Questionnaire in status/change form), fear of hypoglycemia (Hypoglycemia Fear Survey), quality of sleep (Pittsburgh Sleep Quality Index).

RESULTS

After 12 weeks of Control-IQ, time in range increased from 62.7 to 74.0%, p < 0.0001, time in tight range increased from 37.1 to 44.6 %, p < 0.001, time above range decreased from 35.6 to 24.4% p < 0.0001. Improvements were observed in mean glucose and glucose variability. Glycated hemoglobin decreased from 7.0% (53 mmol/mol) to 6.6% (49 mmol/mol), p < 0.0001. Subjects using Control-IQ manifested greater satisfaction and less fear of hypoglycemia.

CONCLUSION

Compared to Basal-IQ, Control-IQ improves glucose control and therapy satisfaction.

Outcomes of hybrid closed-loop insulin delivery activated 24/7 versus evening and night in free-living prepubertal children with type 1 diabetes: A multicentre, randomized clinical trial

AIM

To assess the safety and efficacy of hybrid closed-loop (HCL) insulin delivery 24/7 versus only evening and night (E/N), and on extended 24/7 use, in free-living children with type 1 diabetes.

MATERIALS AND METHODS

Prepubertal children (n = 122; 49 females/73 males; age, 8.6 ± 1.6 years; diabetes duration, 5.2 ± 2.3 years; insulin pump use, 4.6 ± 2.5 years; HbA1c 7.7% ± 0.7%/61 ± 5 mmol/mol) from four centres were randomized for 24/7 versus E/N activation of the Tandem Control-IQ system for 18 weeks. Afterwards, all children used the activated system 24/7 for 18 more weeks. The primary outcome was the percentage of time spent in the 70-180 mg/dL glucose range (TIR).

RESULTS

HCL was active 94.1% and 51.1% of the time in the 24/7 and E/N modes, respectively. TIR from baseline increased more in the 24/7 versus the E/N mode (52.9% ± 9.5% to 67.3% ± 5.6% [+14.4%, 95% CI 12.4%-16.7%] vs. 55.1% ± 10.8% to 64.7% ± 7.0% [+9.6%, 95% CI 7.4%-11.6%]; P = .001). Mean percentage time below range was similarly reduced, from 4.2% and 4.6% to 2.7%, and the mean percentage time above range decreased more in the 24/7 mode (41.9% to 30.0% [-11.9%, 95% CI 9.7%-14.6%] vs. 39.8% to 32.6% [-7.2%, 95% CI 5.0%-9.9%]; P = .007). TIR increased through the whole range of baseline levels and always more with 24/7 use. The results were maintained during the extension phase in those initially on 24/7 use and improved in those with initial E/N use up to those with 24/7 use. Neither ketoacidosis nor severe hypoglycaemia occurred.

CONCLUSIONS

The current study shows the safety and efficacy of the Tandem Control-IQ system in free-living children with type 1 diabetes for both E/N and 24/7 use; 24/7 use shows better outcomes, sustained for up to 36 weeks with no safety issues.

Real-World Performance of the MiniMed™ 780G System: First Report of Outcomes from 4120 Users

Background: The MiniMed™ 780G system includes an advanced hybrid closed loop (AHCL) algorithm that provides both automated basal and correction bolus insulin delivery. The preliminary performance of the system in real-world settings was evaluated. Methods: Data uploaded from August 2020 to March 2021 by individuals living in Belgium, Finland, Italy, the Netherlands, Qatar, South Africa, Sweden, Switzerland, and the United Kingdom were aggregated and retrospectively analyzed to determine the mean glucose management indicator (GMI), percentage of time spent within (TIR), below (TBR), and above (TAR) glycemic ranges, system use, and insulin consumption in users having ≥10 days of sensor glucose (SG) data after initiating AHCL. The impact of initiating AHCL was evaluated in a subgroup of users also having ≥10 days of SG data, before AHCL initiation. Results: Users (N = 4120) were observed for a mean of 54 ± 32 days. During this time, they spent a mean of 94.1% ± 11.4% of the time in AHCL and achieved a mean GMI of 6.8% ± 0.3%, TIR of 76.2% ± 9.1%, TBR <70 of 2.5% ± 2.1%, and TAR >180 of 21.3% ± 9.4%, after initiating AHCL. There were 77.3% and 79.0% of users who achieved a TIR >70% and a GMI of <7.0%, respectively. Users for whom comparison with pre-AHCL was possible (N = 812) reduced their GMI by 0.4% ± 0.4% (P = 0.005) and increased their TIR by 12.1% ± 10.5% (P < 0.0001), post-AHCL initiation. More users achieved the glycemic treatment goals of GMI <7.0% (37.6% vs. 75.2%, P < 0.0001) and TIR >70% (34.6% vs. 74.9%, P < 0.0001) when compared with pre-AHCL initiation. Conclusion: Most MiniMed 780G system users achieved TIR >70% and GMI <7%, while minimizing hypoglycemia, in a real-world condition.

Recent advances in closed-loop insulin delivery

Since the discovery of insulin 100 years ago, we have seen considerable advances across diabetes therapies. The more recent advent of glucose-responsive automated insulin delivery has started to revolutionise the management of type 1 diabetes in children and adults. Evolution of closed-loop insulin delivery from research to clinical practice has been rapid, and multiple systems are now commercially available. In this review, we summarise key evidence on currently available closed-loop systems and those in development. We comment on dual-hormone and do-it-yourself systems, as well as reviewing clinical evidence in special populations such as very young children, older adults and in pregnancy. We identify future directions for research and barriers to closed-loop adoption, including how these might be addressed to ensure equitable access to this novel therapy.

Accessibility and Openness to Diabetes Management Support via Mobile Phones: A Survey of People with Type 1 Diabetes Using Advanced Diabetes Technologies (Preprint)

Background

Little is known about the feasibility of mobile health (mHealth) support among people with type 1 diabetes (T1D) using advanced diabetes technologies including continuous glucose monitoring (CGM) systems and hybrid closed-loop insulin pumps (HCLs).

Objective

This study aims to evaluate patient access and openness to receiving mHealth diabetes support in people with T1D using CGM systems or HCLs.

Methods

We conducted a cross-sectional survey among patients with T1D using CGM systems or HCLs managed in an academic medical center. Participants reported information regarding their mobile device use; cellular call, SMS text message, or internet connectivity; and openness to various channels of mHealth communication (smartphone apps, SMS text messages, and interactive voice response [IVR] calls). Participants’ demographic characteristics and CGM data were collected from medical records. The analyses focused on differences in openness to mHealth and mHealth communication channels across groups defined by demographic variables and measures of glycemic control.

Results

Among all participants (N=310; female: n=198, 63.9%; mean age 45, SD 16 years), 98.1% (n=304) reported active cellphone use and 80% (n=248) were receptive to receiving mHealth support to improve glucose control. Among participants receptive to mHealth support, 98% (243/248) were willing to share CGM glucose data for mHealth diabetes self-care assistance. Most (176/248, 71%) were open to receiving messages via apps, 56% (139/248) were open to SMS text messages, and 12.1% (30/248) were open to IVR calls. Older participants were more likely to prefer SMS text messages (P=.009) and IVR calls (P=.03) than younger participants.

Conclusions

Most people with T1D who use advanced diabetes technologies have access to cell phones and are receptive to receiving mHealth support to improve diabetes control.

The automated pancreas: A review of technologies and clinical practice

Insulin pumps and glucose sensors are effective in improving diabetes therapy and reducing acute complications. The combination of both devices using an algorithm-driven interoperable controller makes automated insulin delivery (AID) systems possible. Many AID systems have been tested in clinical trials and have proven safety and effectiveness. However, currently, none of these systems are available for routine use in children younger than 6 years in Europe. For continued use, both users and prescribers must have sound knowledge of the features of the individual AID systems. Presently, all systems require various user interactions (e.g. meal announcements) because fully automated systems are not yet developed. Open-source systems are non-regulated variants to circumvent existing regulatory conditions. There are risks here for both users and prescribers. To evaluate AID therapy, the metric data of the glucose sensors, 'time in target range' and 'glucose management index', are novel recognized and suitable parameters allowing a consultation based on real glucose and insulin pump download data from the daily life of people with diabetes. Read out via cloud-based software or automatic download of such individual treatment data provides the ideal technical basis for shared decision-making through telemedicine, which must be further evaluated for general use.

Rapid-acting insulin analogues: Theory and best clinical practice in type 1 and type 2 diabetes

Since the discovery of insulin 100 years ago, insulin preparations have improved significantly. Starting from purified animal insulins, evolving to human insulins produced by genetically modified organisms, and ultimately to insulin analogues, all in an attempt to mimic physiological insulin action profiles seen in individuals without diabetes. Achieving strict glucose control without hypoglycaemia and preventing chronic complications of diabetes while preserving quality of life remains a challenging goal, but the advent of newer ultra-rapid-acting insulin analogues may enable intensive insulin therapy without being too disruptive to daily life. Ultra-rapid-acting insulin analogues can be administered shortly before meals and give better coverage of mealtime-induced glucose excursions than conventional insulin preparations. They also increase convenience with timing of bolus dosing. In this review, we focus on the progress that has been made in rapid-acting insulins. We summarize pharmacokinetic and pharmacodynamic data, clinical trial data supporting the use of these new formulations as part of a basal-bolus regimen and continuous subcutaneous insulin infusion, and provide a clinical perspective to help guide healthcare professionals when and for whom to use ultra-fast-acting insulins.

To sleep or not to sleep: An Italian Control-IQ-uestion

OBJECTIVE

Tandem Control-IQ is an advanced hybrid closed loop (AHCL) system with a Sleep Activity Mode to intensify glycemic control overnight. The aim of the study is to evaluate the effectiveness of using Sleep Mode or not among Tandem Control-IQ users.

RESEARCH DESIGN AND METHODS

We performed a retrospective Tandem Control-IQ data download for patients followed at IRCCS G. Gaslini Pediatric Diabetes Centre. We divided the patients into group 1 (Sleep Mode users) and group 2 (non-users) and compared their overall glycemic data, particularly during nighttime.

RESULTS

Group 1 (n = 49) does not show better nocturnal glycemic control as expected when compared with group 2 (n = 34). Group 2 shows a nighttime TIR% of 69.50 versus 66.25 (p = 0.20). Only the patients who do not use Sleep Mode and with sensor and automatic mode use ≥90% reached TIR >70% during nighttime, as well as lower nocturnal TAR% (18.80 versus 21.78, p = 0.05).

CONCLUSIONS

This is the first study that evaluates the real-life effectiveness of the use of Sleep Mode in young patients with T1D. Control-IQ Sleep Activity Mode may not be as effective in Italian patients as in American patients due to the different habits.

Real-World, Patient-Reported and Clinic Data from Individuals with Type 1 Diabetes Using the MiniMed 670G Hybrid Closed-Loop System

Background: The purpose of this study was to collect 1 year of real-world data from individuals with type 1 diabetes (T1D) initiating the Medtronic 670G hybrid closed-loop insulin delivery system as part of usual care. We sought to expand current knowledge to understand how use of the system impacts patient-reported outcomes, in addition to clinical outcomes, for children and adults with T1D. Methods: Questionnaires were completed by the participant (and/or parent) before initiation of the 670G system (baseline) and at 6 weeks, 6 months, and 12 months from enrollment. Clinical data were obtained at routine clinical visits. Results: Of 132 participants who initiated Auto Mode, 80 completed the 12-month questionnaires while persisting with the system. Nearly all reported receiving adequate training on the 670G. Participant and parent-reported fear of hypoglycemia decreased by 6 and 11 points, respectively, from baseline to 12 months. More than half reported issues with sleep interruption at night due to alarms and 40% did not like frequent exits from Auto Mode. For the subset who had complete continuous glucose monitor data (n = 27), mean percent time in target range (70-180 mg/dL) was 66% at baseline, and 74% and 68% at 6 and 12 months, respectively. Conclusions: With this study, we have captured real-time feedback from patients with T1D who initiated the 670G system and continued to use it over 12 months regarding their experience with the system. This has helped to illuminate both benefits and burdens associated with the first commercially available hybrid closed-loop system.

Efficacy of advanced hybrid closed loop systems for the management of type 1 diabetes in children

Over the last years significant advances have been achieved in the development of technologies for diabetes management. Continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), predictive low glucose management (PLGM), hybrid closed loop (HCL) and advanced hybrid closed loop (AHCL) systems allow better diabetes management, thus reducing the burden of the disease and the risk of chronic complications. This review summarizes the main characteristics of the currently available HCL and AHCL systems and their primary effects in children and adolescents with type 1 diabetes (T1D). The findings of trials assessing the glucose control (time in range, HbA1c values, hypoglycemic events), the health-related quality of life and the existing limits of the use of these technologies are reported. The most recent data clearly confirm the ability of the HCL and AHCL insulin delivery systems to safely achieve a significant improvement of glucose control and quality of life in the pediatric population with T1D. Further studies are underway to overcame current barriers and future improvements in the usability of these technologies are awaited to facilitate their use in the routine clinical practice. The HCL and AHCL algorithms are the key features of today's insulin delivery systems that mark a crucial step towards fully automated closed loop systems.

Barriers to Uptake of Insulin Technologies and Novel Solutions

Diabetes-related technology has undergone great advancement in recent years. These technological devices are more commonly utilized in the type 1 diabetes population, which requires insulin as the primary treatment modality. Available devices include insulin pumps, continuous glucose monitors, and hybrid systems referred to as automated insulin delivery systems or hybrid closed-loop systems, which combine those two devices along with software algorithms to achieve advanced therapeutic capabilities, including automatic modulation of insulin delivery based on sensor-derived glucose levels to minimize abnormal glucose trends. Use of diabetes technology is associated with significant positive health and psychosocial outcomes, yet utilization rates are generally lacking across both adult and pediatric type 1 diabetes populations in the United States and other countries. There are consistent themes in existing barriers to technology uptake reported by individuals with type 1 diabetes or parents of children with type 1 diabetes, including physical burdens associated with wearing the devices, concerns in navigating the technology and the devices' abilities to meet user expectations, high cost, inadequate resources within the healthcare team to support device use, disparities in technology access, and psychosocial barriers. It is important to understand the common barriers to uptake of not only the automated insulin delivery systems but also their component devices (insulin pumps and continuous glucose monitors) to fully support individuals in utilizing these devices and optimizing health benefits. The purpose of this article is to summarize the current automated insulin delivery devices that are available for use in management of type 1 diabetes, review common barriers to uptake of those systems and their component devices, and provide expert opinion on existing and future solutions to identified barriers.