Glucose Outcomes with the In-Home Use of a Hybrid Closed-Loop Insulin Delivery System in Adolescents and Adults with Type 1 Diabetes

HbA1c and Hypoglycemia Reductions at 24 and 52 Weeks With Sotagliflozin in Combination With Insulin in Adults With Type 1 Diabetes: The European inTandem2 Study

OBJECTIVE

The objective of this study was to evaluate the efficacy and safety of the dual sodium-glucose cotransporter 1 and 2 inhibitor sotagliflozin compared with placebo when combined with optimized insulin in adults with type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

In a double-blind, 52-week, international phase 3 trial, adults with T1D were randomized to placebo (n = 258) or once-daily oral sotagliflozin 200 mg (n = 261) or 400 mg (n = 263) after 6 weeks of insulin optimization. The primary outcome was change in HbA_1c from baseline to 24 weeks. The first secondary end point was a composite of the proportion of patients with HbA_1c <7.0%, no episode of severe hypoglycemia, and no episode of diabetic ketoacidosis (DKA) at week 24. Fasting glucose, weight, insulin dose, and safety end points were assessed through 52 weeks.

RESULTS

At 24 weeks, placebo-adjusted changes in HbA_1c from baseline (7.8%) were -0.37% and -0.35% with sotagliflozin 200 and 400 mg, respectively (P < 0.001), and differences were maintained at 52 weeks. At 52 weeks, greater proportions of sotagliflozin-treated patients (200 mg: 25.67%; 400 mg: 26.62%) than placebo-treated patients (14.34%; P ≤ 0.001) met the composite end point, and sotagliflozin 400 mg reduced fasting plasma glucose (-0.87 mmol/L; P = 0.008), weight (-2.92 kg; P < 0.001), and total daily insulin dose (-8.2%; P = 0.001). In a 24-week continuous glucose monitoring (CGM) substudy, postprandial glucose decreased (P ≤ 0.009) and CGM demonstrated up to 3 h more time in the target range of 3.9-10.0 mmol/L with sotagliflozin. Treatment satisfaction increased and diabetes distress decreased with sotagliflozin (P < 0.05 vs. placebo). The frequency of documented hypoglycemia was lower with sotagliflozin, and severe hypoglycemia occurred by week 52 in 13 patients (5.0%), 13 patients (5.0%), and 6 patients (2.3%) treated with placebo and sotagliflozin 200 and 400 mg, respectively. DKA occurred in 0 of 258 patients, 6 of 261 patients (2.3%), and 9 of 263 patients (3.4%) in these respective groups.

CONCLUSIONS

In a 1-year study, sotagliflozin was associated with statistically significant HbA_1c reductions. More episodes of DKA and fewer episodes of documented and severe hypoglycemia were observed in patients using sotagliflozin relative to those receiving placebo (ClinicalTrials.gov, NCT02421510).

Advances in Closed-Loop Insulin Delivery Systems in Patients with Type 1 Diabetes

To provide a current review of closed-loop insulin delivery or artificial pancreas (AP) as therapy for people with type 1 diabetes mellitus (T1D) RECENT FINDINGS: The Medtronic Minimed 670G AP system has been in use in clinical practice since March 2017. Currently, Medtronic is conducting a large randomized clinical trial to evaluate its efficacy further in T1D. Simultaneously, the NIH has funded four research consortia to accelerate progress to approval of other AP and decision support systems. Several research groups are currently developing next-generation AP systems, with a number of companies moving toward releasing closed-loop systems in the future. AP systems are also being tested in select populations such as hypoglycemia-unaware T1D and pregnant T1D. AP research is rapidly advancing. The clinical range of AP will be expanded in the next decade.

Prevention and Management of Severe Hypoglycemia and Hypoglycemia Unawareness: Incorporating Sensor Technology

PURPOSE OF REVIEW

In addition to assisting in achieving improved glucose control, continuous glucose monitoring (CGM) sensor technology may also aid in detection and prevention of hypoglycemia. In this paper, we report on the current scientific evidence on the effectiveness of this technology in the prevention of severe hypoglycemia and hypoglycemia unawareness.

RECENT FINDINGS

Recent studies have found that the integration of CGM with continuous subcutaneous insulin infusion (CSII) therapy, a system known as sensor-augmented pump (SAP) therapy, very significantly reduces the occurrence of these conditions by providing real-time glucose readings/trends and automatically suspending insulin infusion when glucose is low (LGS) or, even, before glucose is low but is predicted to soon be low (PLGS). Initial data indicate that even for patients with type 1 diabetes treated with multiple daily injections, real-time CGM alone has been found to reduce both severe hypoglycemia and hypoglycemia unawareness. Closed loop systems (artificial pancreas) comprised of CGM and CSII without patient intervention to adjust basal insulin, which automatically reduce, increase, and suspend insulin delivery, represent a potential new option that is moving toward becoming a reality in the near future. Sensor technology promises to continue to improve patients' lives not only by attaining glycemic control but also by reducing hypoglycemia, a goal best achieved in conjunction with structured individualized patient education.

Effect of 6 months hybrid closed-loop insulin delivery in young people with type 1 diabetes: a randomised controlled trial protocol

INTRODUCTION

Automated insulin delivery (also known as closed loop, or artificial pancreas) has shown potential to improve glycaemic control and quality of life in people with type 1 diabetes (T1D). Automated insulin delivery devices incorporate an insulin pump with continuous glucose monitoring(CGM) and an algorithm, and adjust insulin in real time. This study aims to establish the safety and efficacy of a hybrid closed-loop (HCL) system in a long-term outpatient trial in people with T1D aged 12 -<25 years of age, and compare outcomes with standard therapy for T1D as used in the contemporary community.

METHODS AND ANALYSIS

This is an open-label, multicentre, 6-month, randomised controlled home trial to test the MiniMed Medtronic 670G system (HCL) in people with T1D aged 12 -<25 years, and compare it to standard care (multiple daily injections or continuous subcutaneous insulin infusion (CSII), with or without CGM). Following a run-in period including diabetes and carbohydrate counting education, dosage optimisation and baseline glucose control data collection, participants are randomised to either HCL or to continue on their current treatment regimen. The primary aim of the study is to compare the proportion of time spent in target sensor glucose range (3.9-10.0 mmol/L) on HCL versus standard therapy. Secondary aims include a range of glucose control parameters, psychosocial measures, health economic measures, biomarker status, user/technology interactions and healthcare professional expectations. Analysis will be intention to treat. A study in adults with an aligned design is being conducted in parallel to this trial.

ETHICS AND DISSEMINATION

Ethics committee permissions were gained from respective institutional review boards. The findings of the study will provide high-quality evidence on the role of HCL in clinical practice.

Technology in the management of type 1 diabetes mellitus - current status and future prospects

Type 1 diabetes mellitus (T1DM) represents 5-10% of diabetes cases worldwide. The incidence of T1DM is increasing, and there is no immediate prospect of a cure. As such, lifelong management is required, the burden of which is being eased by novel treatment modalities, particularly from the field of diabetes technologies. Continuous glucose monitoring has become the standard of care and includes factory-calibrated subcutaneous glucose monitoring and long-term implantable glucose sensing. In addition, considerable progress has been made in technology-enabled glucose-responsive insulin delivery. The first hybrid insulin-only closed-loop system has been commercialized, and other closed-loop systems are under development, including dual-hormone glucose control systems. This Review focuses on well-established diabetes technologies, including glucose sensing, pen-based insulin delivery, data management and data analytics. We also cover insulin pump therapy, threshold-based suspend, predictive low-glucose suspend and single-hormone and dual-hormone closed-loop systems. Clinical practice recommendations for insulin pump therapy and continuous glucose monitoring are presented, and ongoing research and future prospects are highlighted. We conclude that the management of T1DM is improved by diabetes technology for the benefit of the majority of people with T1DM, their caregivers and guardians and health-care professionals treating patients with T1DM.

Closing the Loop on Managing Youth With Type 1 Diabetes: Children Are Not Just Small Adults

As hybrid closed-loop (HCL) insulin delivery systems permeate clinical practice, it is critical to ensure all with diabetes are afforded the opportunity to benefit from this technology. Indeed, due to the suboptimal control achieved by the vast majority of youth with type 1 diabetes (T1D), pediatric patients are positioned to see the greatest benefit from automated insulin delivery systems. To ensure these systems are well poised to deliver the promise of more targeted control, it is essential to understand the unique characteristics and factors of childhood. Herein, the developmental and physiological needs of youth with T1D are reviewed and consideration is given to how HCL could address these issues. Studies of HCL technologies in youth are briefly reviewed. As future-generation closed-loop systems are being devised, features that could make this technology more attractive to youth and to their families are discussed. Integration of HCL has the potential to minimize the burden of this chronic medical condition while improving glycemic control and ultimately allowing our pediatric patients to fulfill the primary goal of childhood, to be a kid.

Closed-loop insulin delivery: current status of diabetes technologies and future prospects

INTRODUCTION

Type 1 diabetes is characterised by destruction of pancreatic beta cells, leading to insulin deficiency and hyperglycaemia. The mainstay of treatment remains lifelong insulin therapy as a sustainable cure has as yet proven elusive. The burden of daily management of type 1 diabetes has contributed to suboptimal outcomes for people living with the condition. Innovative technological approaches have been shown to improve glycaemic and patient-related outcomes.

AREAS COVERED

We discuss recent advances in technologies in type 1 diabetes including closed-loop systems, also known as the 'artificial pancreas. Its various components, technical aspects and limitations are reviewed. We also discuss its advent into clinical practice, and other systems in development. Evidence from clinical studies are summarised.

EXPERT COMMENTARY

The recent approval of a hybrid closed-loop system for clinical use highlights the significant progress made in this field. Results from clinical studies have shown safety and glycaemic benefit, however challenges remain around improving performance and acceptability. More data is required to establish long-term clinical efficacy and cost-effectiveness, to fulfil the expectations of people with type 1 diabetes.

Evaluation of an Artificial Pancreas with Enhanced Model Predictive Control and a Glucose Prediction Trust Index with Unannounced Exercise

BACKGROUND

We investigated the safety and efficacy of the addition of a trust index to enhanced Model Predictive Control (eMPC) Artificial Pancreas (AP) that works by adjusting the responsiveness of the controller's insulin delivery based on the confidence intervals around predictions of glucose trends. This constitutes a dynamic adaptation of the controller's parameters in contrast with the widespread AP implementation of individualized fixed controller tuning.

MATERIALS AND METHODS

After 1 week of sensor-augmented pump (SAP) use, subjects completed a 48-h AP admission that included three meals/day (carbohydrate range 29-57 g/meal), a 1-h unannounced brisk walk, and two overnight periods. Endpoints included sensor glucose percentage time 70-180, <70, >180 mg/dL, number of hypoglycemic events, and assessment of the trust index versus standard eMPC glucose predictions.

RESULTS

Baseline characteristics for the 15 subjects who completed the study (mean ± SD) were age 46.1 ± 17.8 years, HbA1c 7.2% ± 1.0%, diabetes duration 26.8 ± 17.6 years, and total daily dose (TDD) 35.5 ± 16.4 U/day. Mean sensor glucose percent time 70-180 mg/dL (88.0% ± 8.0% vs. 74.6% ± 9.4%), <70 mg/dL (1.5% ± 1.9% vs. 7.8% ± 6.0%), and number of hypoglycemic events (0.6 ± 0.6 vs. 6.3 ± 3.4), all showed statistically significant improvement during AP use compared with the SAP run-in (P < 0.001). On average, the trust index enhanced controller responsiveness to predicted hyper- and hypoglycemia by 26% (P < 0.005).

CONCLUSIONS

In this population of well-controlled patients, we conclude that eMPC with trust index AP achieved nearly 90% time in the target glucose range. Additional studies will further validate these results.

Type 1 diabetes

Type 1 diabetes is a chronic autoimmune disease characterised by insulin deficiency and resultant hyperglycaemia. Knowledge of type 1 diabetes has rapidly increased over the past 25 years, resulting in a broad understanding about many aspects of the disease, including its genetics, epidemiology, immune and β-cell phenotypes, and disease burden. Interventions to preserve β cells have been tested, and several methods to improve clinical disease management have been assessed. However, wide gaps still exist in our understanding of type 1 diabetes and our ability to standardise clinical care and decrease disease-associated complications and burden. This Seminar gives an overview of the current understanding of the disease and potential future directions for research and care.

Effect of 6 months of hybrid closed-loop insulin delivery in adults with type 1 diabetes: a randomised controlled trial protocol

INTRODUCTION

Manual determination of insulin dosing largely fails to optimise glucose control in type 1 diabetes. Automated insulin delivery via closed-loop systems has improved glucose control in short-term studies. The objective of the present study is to determine the effectiveness of 6 months' closed-loop compared with manually determined insulin dosing on time-in-target glucose range in adults with type 1 diabetes.

METHODS AND ANALYSIS

This open-label, seven-centre, randomised controlled parallel group clinical trial will compare home-based hybrid closed-loop versus standard diabetes therapy in Australia. Adults aged ≥25 years with type 1 diabetes using intensive insulin therapy (via multiple daily injections or insulin pump, total enrolment target n=120) will undertake a run-in period including diabetes and carbohydrate-counting education, clinical optimisation and baseline data collection. Participants will then be randomised 1:1 either to 26 weeks of MiniMed 670G hybrid closed-loop system therapy (Medtronic, Northridge, CA, USA) or continuation of their current diabetes therapy. The hybrid closed-loop system delivers insulin automatically to address basal requirements and correct to target glucose level, while bolus doses for meals require user initiation and carbohydrate estimation. Analysis will be intention to treat, with the primary outcome time in continuous glucose monitoring (CGM) target range (3.9-10.0 mmol/L) during the final 3 weeks of intervention. Secondary outcomes include: other CGM parameters, HbA_1c, severe hypoglycaemia, psychosocial well-being, sleep, cognition, electrocardiography, costs, quality of life, biomarkers of vascular health and hybrid closed-loop system performance. Semistructured interviews will assess the expectations and experiences of a subgroup of hybrid closed-loop users.

ETHICS AND DISSEMINATION

The study has Human Research Ethics Committee approval. The study will be conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. Results will be disseminated at scientific conferences and via peer-reviewed publications.

TRIAL REGISTRATION NUMBER

ACTRN12617000520336; Pre-results.

Customization of home closed-loop insulin delivery in adult patients with type 1 diabetes, assisted with structured remote monitoring: the pilot WP7 Diabeloop study

AIMS

Improvement in closed-loop insulin delivery systems could result from customization of settings to individual needs and remote monitoring. This pilot home study evaluated the efficacy and relevance of this approach.

METHODS

A bicentric clinical trial was conducted for 3 weeks, using an MPC-based algorithm (Diabeloop Artificial Pancreas system) featuring five settings designed to modulate the reactivity of regulation. Remote monitoring was ensured by expert nurses with a web platform generating automatic Secured Information Messages (SIMs) and with a structured procedure. Endpoints were glucose metrics and description of impact of monitoring on regulation parameters.

RESULTS

Eight patients with type 1 diabetes (six men, age 41.8 ± 11.4 years, HbA1c 7.7 ± 1.0%) were included. Time spent in the 70-180 mg/dl range was 70.2% [67.5; 76.9]. Time in hypoglycemia < 70 mg/dl was 2.9% [2.1; 3.4]. Eleven SIMs led to phone intervention. Original default settings were modified in all patients by the intervention of the nurses.

CONCLUSION

This pilot trial suggests that the Diabeloop closed-loop system could be efficient regarding metabolic outcomes, whereas its telemedical monitoring feature could contribute to enhanced efficacy and safety. This study is registered at ClinicalTrials.gov with trial registration number NCT02987556.

The Hybrid Closed-Loop System: Evolution and Practical Applications

Achievement of well-controlled blood glucose is essential for preventing complications in patients with type 1 diabetes. Since the inception of continuous subcutaneous insulin infusion, the aim has been to develop an artificial pancreas, with the ability to use an automated algorithm to deliver one or more hormones in response to blood glucose with the intent to keep blood sugar as close to a prespecified target as possible. Development and rapid improvement of continuous glucose sensor technology has recently allowed swift progress toward a fully closed-loop insulin delivery system. In 2017, Medtronic began marketing the 670G insulin pump with Guardian 3 sensor. When in auto mode, this is a hybrid closed-loop insulin delivery system that automatically adjusts basal insulin delivery every 5 min based on sensor glucose to maintain blood glucose levels as close to a specific target as possible. Patients receive prandial insulin by entering carbohydrate amount into the bolus calculator. Early studies show improvement in HbA1c in both adults and adolescents with this technology. Initial safety trials showed no occurrence of diabetic ketoacidosis or hypoglycemia. The utility of this device is limited by blood glucose targets of 120 and 150 mg/dL that are unacceptably high for some patients. Notwithstanding recent advances, we are far from a system that is able to replicate islet function in the form of a fully automated, multihormonal blood glucose control device.

Predictive hyperglycemia and hypoglycemia minimization: In-home double-blind randomized controlled evaluation in children and young adolescents

OBJECTIVE

The primary objective of this trial was to evaluate the feasibility, safety, and efficacy of a predictive hyperglycemia and hypoglycemia minimization (PHHM) system vs predictive low glucose suspension (PLGS) alone in optimizing overnight glucose control in children 6 to 14 years old.

RESEARCH DESIGN AND METHODS

Twenty-eight participants 6 to 14 years old with T1D duration ≥1 year with daily insulin therapy ≥12 months and on insulin pump therapy for ≥6 months were randomized per night into PHHM mode or PLGS-only mode for 42 nights. The primary outcome was percentage of time in sensor-measured range 70 to 180 mg/dL in the overnight period.

RESULTS

The addition of automated insulin delivery with PHHM increased time in target range (70-180 mg/dL) from 66 ± 11% during PLGS nights to 76 ± 9% during PHHM nights (P<.001), without increasing hypoglycemia as measured by time below various thresholds. Average morning blood glucose improved from 176 ± 28 mg/dL following PLGS nights to 154 ± 19 mg/dL following PHHM nights (P<.001).

CONCLUSIONS

The PHHM system was effective in optimizing overnight glycemic control, significantly increasing time in range, lowering mean glucose, and decreasing glycemic variability compared to PLGS alone in children 6 to 14 years old.

Fully Closed-Loop Multiple Model Probabilistic Predictive Controller Artificial Pancreas Performance in Adolescents and Adults in a Supervised Hotel Setting

BACKGROUND

Initial Food and Drug Administration-approved artificial pancreas (AP) systems will be hybrid closed-loop systems that require prandial meal announcements and will not eliminate the burden of premeal insulin dosing. Multiple model probabilistic predictive control (MMPPC) is a fully closed-loop system that uses probabilistic estimation of meals to allow for automated meal detection. In this study, we describe the safety and performance of the MMPPC system with announced and unannounced meals in a supervised hotel setting.

RESEARCH DESIGN AND METHODS

The Android phone-based AP system with remote monitoring was tested for 72 h in six adults and four adolescents across three clinical sites with daily exercise and meal challenges involving both three announced (manual bolus by patient) and six unannounced (no bolus by patient) meals. Safety criteria were predefined. Controller aggressiveness was adapted daily based on prior hypoglycemic events.

RESULTS

Mean 24-h continuous glucose monitor (CGM) was 157.4 ± 14.4 mg/dL, with 63.6 ± 9.2% of readings between 70 and 180 mg/dL, 2.9 ± 2.3% of readings <70 mg/dL, and 9.0 ± 3.9% of readings >250 mg/dL. Moderate hyperglycemia was relatively common with 24.6 ± 6.2% of readings between 180 and 250 mg/dL, primarily within 3 h after a meal. Overnight mean CGM was 139.6 ± 27.6 mg/dL, with 77.9 ± 16.4% between 70 and 180 mg/dL, 3.0 ± 4.5% <70 mg/dL, 17.1 ± 14.9% between 180 and 250 mg/dL, and 2.0 ± 4.5%> 250 mg/dL. Postprandial hyperglycemia was more common for unannounced meals compared with announced meals (4-h postmeal CGM 197.8 ± 44.1 vs. 140.6 ± 35.0 mg/dL; P < 0.001). No participants met safety stopping criteria.

CONCLUSIONS

MMPPC was safe in a supervised setting despite meal and exercise challenges. Further studies are needed in a less supervised environment.

Real-Time Detection of Infusion Site Failures in a Closed-Loop Artificial Pancreas

BACKGROUND

As evidence emerges that artificial pancreas systems improve clinical outcomes for patients with type 1 diabetes, the burden of this disease will hopefully begin to be alleviated for many patients and caregivers. However, reliance on automated insulin delivery potentially means patients will be slower to act when devices stop functioning appropriately. One such scenario involves an insulin infusion site failure, where the insulin that is recorded as delivered fails to affect the patient's glucose as expected. Alerting patients to these events in real time would potentially reduce hyperglycemia and ketosis associated with infusion site failures.

METHODS

An infusion site failure detection algorithm was deployed in a randomized crossover study with artificial pancreas and sensor-augmented pump arms in an outpatient setting. Each arm lasted two weeks. Nineteen participants wore infusion sets for up to 7 days. Clinicians contacted patients to confirm infusion site failures detected by the algorithm and instructed on set replacement if failure was confirmed.

RESULTS

In real time and under zone model predictive control, the infusion site failure detection algorithm achieved a sensitivity of 88.0% (n = 25) while issuing only 0.22 false positives per day, compared with a sensitivity of 73.3% (n = 15) and 0.27 false positives per day in the SAP arm (as indicated by retrospective analysis). No association between intervention strategy and duration of infusion sets was observed ( P = .58).

CONCLUSIONS

As patient burden is reduced by each generation of advanced diabetes technology, fault detection algorithms will help ensure that patients are alerted when they need to manually intervene. Clinical Trial Identifier: www.clinicaltrials.gov,NCT02773875.

Artificial pancreas treatment for outpatients with type 1 diabetes: systematic review and meta-analysis

OBJECTIVE

To evaluate the efficacy and safety of artificial pancreas treatment in non-pregnant outpatients with type 1 diabetes.

DESIGN

Systematic review and meta-analysis of randomised controlled trials.

DATA SOURCES

Medline, Embase, Cochrane Library, and grey literature up to 2 February 2018.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Randomised controlled trials in non-pregnant outpatients with type 1 diabetes that compared the use of any artificial pancreas system with any type of insulin based treatment. Primary outcome was proportion (%) of time that sensor glucose level was within the near normoglycaemic range (3.9-10 mmol/L). Secondary outcomes included proportion (%) of time that sensor glucose level was above 10 mmol/L or below 3.9 mmol/L, low blood glucose index overnight, mean sensor glucose level, total daily insulin needs, and glycated haemoglobin. The Cochrane Collaboration risk of bias tool was used to assess study quality.

RESULTS

40 studies (1027 participants with data for 44 comparisons) were included in the meta-analysis. 35 comparisons assessed a single hormone artificial pancreas system, whereas nine comparisons assessed a dual hormone system. Only nine studies were at low risk of bias. Proportion of time in the near normoglycaemic range (3.9-10.0 mmol/L) was significantly higher with artificial pancreas use, both overnight (weighted mean difference 15.15%, 95% confidence interval 12.21% to 18.09%) and over a 24 hour period (9.62%, 7.54% to 11.7%). Artificial pancreas systems had a favourable effect on the proportion of time with sensor glucose level above 10 mmol/L (-8.52%, -11.14% to -5.9%) or below 3.9 mmol/L (-1.49%, -1.86% to -1.11%) over 24 hours, compared with control treatment. Robustness of findings for the primary outcome was verified in sensitivity analyses, by including only trials at low risk of bias (11.64%, 9.1% to 14.18%) or trials under unsupervised, normal living conditions (10.42%, 8.63% to 12.2%). Results were consistent in a subgroup analysis both for single hormone and dual hormone artificial pancreas systems.

CONCLUSIONS

Artificial pancreas systems are an efficacious and safe approach for treating outpatients with type 1 diabetes. The main limitations of current research evidence on artificial pancreas systems are related to inconsistency in outcome reporting, small sample size, and short follow-up duration of individual trials.

Optimizing Hybrid Closed-Loop Therapy in Adolescents and Emerging Adults Using the MiniMed 670G System

OBJECTIVE

The MiniMed 670G System is the first commercial hybrid closed-loop (HCL) system for management of type 1 diabetes. Using data from adolescent and young adult participants, we compared insulin delivery patterns and time-in-range metrics in HCL (Auto Mode) and open loop (OL). System alerts, usage profiles, and operational parameters were examined to provide suggestions for optimal clinical use of the system.

RESEARCH DESIGN AND METHODS

Data from 31 adolescent and young adult participants (14-26 years old) at three clinical sites in the 670G pivotal trial were analyzed. Participants had a 2-week run-in period in OL, followed by a 3-month in-home study phase with HCL functionality enabled. Data were compared between baseline OL and HCL use after 1 week, 1 month, 2 months, and 3 months.

RESULTS

Carbohydrate-to-insulin (C-to-I) ratios were more aggressive for all meals with HCL compared with baseline OL. Total daily insulin dose and basal-to-bolus ratio did not change during the trial. Time in range increased 14% with use of Auto Mode after 3 months (P < 0.001), and HbA_1c decreased 0.75%. Auto Mode exits were primarily due to sensor/insulin delivery alerts and hyperglycemia. The percentage of time in Auto Mode gradually declined from 87%, with a final use rate of 72% (-15%).

CONCLUSIONS

In transitioning young patients to the 670G system, providers should anticipate immediate C-to-I ratio adjustments while also assessing active insulin time. Users should anticipate occasional Auto Mode exits, which can be reduced by following system instructions and reliably bolusing for meals. Unique 670G system functionality requires ongoing clinical guidance and education from providers.

Safety and Feasibility of the OmniPod Hybrid Closed-Loop System in Adult, Adolescent, and Pediatric Patients with Type 1 Diabetes Using a Personalized Model Predictive Control Algorithm

BACKGROUND

The safety and feasibility of the OmniPod personalized model predictive control (MPC) algorithm in adult, adolescent, and pediatric patients with type 1 diabetes were investigated.

METHODS

This multicenter, observational trial included a 1-week outpatient sensor-augmented pump open-loop phase and a 36-h inpatient hybrid closed-loop (HCL) phase with announced meals ranging from 30 to 90 g of carbohydrates and limited physical activity. Patients aged 6-65 years with HbA1c between 6.0% and 10.0% were eligible. The investigational system included a modified version of OmniPod, the Dexcom G4 505 Share^® AP System, and the personalized MPC algorithm running on a tablet computer. Primary endpoints included sensor glucose percentage of time in hypoglycemia <70 mg/dL and hyperglycemia >250 mg/dL. Additional glycemic targets were assessed.

RESULTS

The percentage of time <70 mg/dL during the 36-h HCL phase was mean (standard deviation): 0.7 (1.7) in adults receiving 80% meal bolus (n = 24), and 0.7 (1.2) in adults (n = 10), 2.0 (2.4) in adolescents (n = 12), and 2.0 (2.6) in pediatrics (n = 12) receiving 100% meal bolus. The overall hypoglycemia rate was 0.49 events/24 h. The percentage of time >250 mg/dL was 8.0 (7.5), 3.6 (3.7), 4.9 (6.3), and 6.7 (5.6) in the study groups, respectively. Percentage of time in the target range of 70-180 mg/dL was 69.5 (14.4), 73.0 (15.0), 72.6 (15.5), and 70.1 (12.3), respectively.

CONCLUSIONS

The OmniPod personalized MPC algorithm performed well and was safe during day and night use in adult, adolescent, and pediatric patients with type 1 diabetes. Longer term studies will assess the safety and performance of the algorithm under free living conditions with extended use.

Diabetes technology: improving care, improving patient-reported outcomes and preventing complications in young people with Type 1 diabetes

With the evolution of diabetes technology, those living with Type 1 diabetes are given a wider arsenal of tools with which to achieve glycaemic control and improve patient-reported outcomes. Furthermore, the use of these technologies may help reduce the risk of acute complications, such as severe hypoglycaemia and diabetic ketoacidosis, as well as long-term macro- and microvascular complications. In addition, diabetes technology can have a beneficial impact on psychosocial health by reducing the burden of diabetes. Unfortunately, diabetes goals are often unmet and people with Type 1 diabetes too frequently experience acute and long-term complications of this condition, in addition to often having less than ideal psychosocial outcomes. Increasing realization of the importance of patient-reported outcomes is leading to diabetes care delivery becoming more patient-centred. Diabetes technology in the form of medical devices, digital health and big data analytics have the potential to improve clinical care and psychosocial support, resulting in lower rates of acute and chronic complications, decreased burden of diabetes care, and improved quality of life.

Accuracy of Continuous Glucose Monitoring before, during, and after Aerobic and Anaerobic Exercise in Patients with Type 1 Diabetes Mellitus

Continuous glucose monitoring (CGM) plays an important role in treatment decisions for patients with type 1 diabetes under conventional or closed-loop therapy. Physical activity represents a great challenge for diabetes management as well as for CGM systems. In this work, the accuracy of CGM in the context of exercise is addressed. Six adults performed aerobic and anaerobic exercise sessions and used two Medtronic Paradigm Enlite-2 sensors under closed-loop therapy. CGM readings were compared with plasma glucose during different periods: one hour before exercise, during exercise, and four hours after the end of exercise. In aerobic sessions, the median absolute relative difference (MARD) increased from 9.5% before the beginning of exercise to 16.5% during exercise (p < 0.001), and then decreased to 9.3% in the first hour after the end of exercise (p < 0.001). For the anaerobic sessions, the MARD before exercise was 15.5% and increased without statistical significance to 16.8% during exercise realisation (p = 0.993), and then decreased to 12.7% in the first hour after the cessation of anaerobic activities (p = 0.095). Results indicate that CGM might present lower accuracy during aerobic exercise, but return to regular operation a few hours after exercise cessation. No significant impact for anaerobic exercise was found.

Hope vs hype: where are we in type 1 diabetes?

Much progress has been made in type 1 diabetes research. Biological replacement of islet function has been achieved with pancreas transplantation and with islet transplantation. In the future, human embryonic stem cells and/or induced pluripotent stem cells may offer a potentially unlimited source of cells for islet replacement. Another potential strategy is to induce robust beta cell replication so that regeneration of islets can be achieved. Immune interventions are being studied with the hope of arresting the type 1 diabetes disease process to either prevent the disease or help preserve beta cell function. Mechanical replacement of islet cell function involves the use of glucose sensor-controlled insulin infusion systems. As all of these avenues are pursued, headlines often overstate the case, thus hyping any given advance, which provides enormous hope for patients and families seeking a cure for type 1 diabetes. Often, however, it is an animal study or a pilot trial that is being described. The reality is that translation to successful trials in human beings may not be readily achievable. This article discusses both the hype and the hopes in type 1 diabetes research.

Sensor-Augmented Pump-Based Customized Mathematical Model for Type 1 Diabetes

BACKGROUND

Simulations using mathematical models are important for studying, developing, and improving therapies for people with type 1 diabetes.

METHODS

The Medtronic CareLink^® database was used to create virtual patients with a variety of inter-insulin sensitivities, meal absorption rates, pharmacokinetics, age, and gender. In addition, intra-insulin sensitivities of the virtual patients change over a 24-h cycle.

RESULTS

A total of 2087 virtual patients were developed. The time percentage between 70 and 180 mg/dL of the CareLink uploads and the simulated virtual patients was 72.4% (18.6) and 74.1% (16.9), respectively. The time percentage <70 mg/dL of the real continuous glucose monitoring from CareLink uploads and the simulated virtual patients was 1% (2.4) and 1.7% (4.1), respectively. A simulation study with the virtual patients predicted the glycemic distribution after 2 h of insulin suspension as reported in the ASPIRE (Automation to Simulate Pancreatic Insulin Response) clinical trial. The 3 months outcomes of Medtronic's hybrid closed-loop 670G system pivotal trial were also predicted in a simulation study. The time percentage <70 mg/dL was 3.4% and 3.1%, and the time percentage between 71 and 180 mg/dL was 73.8% and 77.7% for 93 pivotal study adults (>18 years) and 90 adult (>28 years) virtual patients, respectively.

CONCLUSION

The Medtronic CareLink database was utilized to generate a large number of virtual patients with a variety of insulin sensitivities, pharmacokinetics, and meal absorption rates. This new simulation model can be potentially used to evaluate and prognosticate the outcomes of studies of artificial pancreas algorithms and systems.

Novel blood glucose lowering therapies for managing type 1 diabetes in paediatric patients

INTRODUCTION

Therapy for type 1 diabetes (T1D) is mainly restricted to insulin treatment. The management of paediatric patients with T1D should tackle not only glucose control, but also insulin resistance, beta-cell preservation, quality of life and cardiovascular disease risk factors, which are increasingly recognized to occur in adolescents with T1D.

AREAS COVERED

This review examines the recently published literature from PubMed on non-insulin agents for the management of T1D in paediatric patients.

EXPERT OPINION

Few paediatric patients with T1D are achieving their metabolic targets. Current data support the need for new strategies and the consideration of additional therapies that not only may help patients, their families and their physicians to meet HbA1c targets, but also may preserve residual islet mass and good quality of life and prevent microvascular and macrovascular complications, thereby, reducing hypoglycaemic episodes. Non-insulin adjunctive therapies may improve not only glucose control, but also insulin sensitivity, in addition to preserving beta-cell function in T1D patients. Thus, more studies are required to define the potential role of these therapies in the management of paediatric patients.

Model-Fusion-Based Online Glucose Concentration Predictions in People with Type 1 Diabetes

Accurate predictions of glucose concentrations are necessary to develop an artificial pancreas (AP) system for people with type 1 diabetes (T1D). In this work, a novel glucose forecasting paradigm based on a model fusion strategy is developed to accurately characterize the variability and transient dynamics of glycemic measurements. To this end, four different adaptive filters and a fusion mechanism are proposed for use in the online prediction of future glucose trajectories. The filter fusion mechanism is developed based on various prediction performance indexes to guide the overall output of the forecasting paradigm. The efficiency of the proposed model fusion based forecasting method is evaluated using simulated and clinical datasets, and the results demonstrate the capability and prediction accuracy of the data-based fusion filters, especially in the case of limited data availability. The model fusion framework may be used in the development of an AP system for glucose regulation in patients with T1D.

The challenges of achieving postprandial glucose control using closed-loop systems in patients with type 1 diabetes

For patients with type 1 diabetes, closed-loop delivery systems (CLS) combining an insulin pump, a glucose sensor and a dosing algorithm allowing a dynamic hormonal infusion have been shown to improve glucose control when compared with conventional therapy. Yet, reducing glucose excursion and simplification of prandial insulin doses remain a challenge. The objective of this literature review is to examine current meal-time strategies in the context of automated delivery systems in adults and children with type 1 diabetes. Current challenges and considerations for post-meal glucose control will also be discussed. Despite promising results with meal detection, the fully automated CLS has yet failed to provide comparable glucose control to CLS with carbohydrate-matched bolus in the post-meal period. The latter strategy has been efficient in controlling post-meal glucose using different algorithms and in various settings, but at the cost of a meal carbohydrate counting burden for patients. Further improvements in meal detection algorithms or simplified meal-priming boluses may represent interesting avenues. The greatest challenges remain in regards to the pharmacokinetic and dynamic profiles of available rapid insulins as well as sensor accuracy and lag-time. New and upcoming faster acting insulins could provide important benefits. Multi-hormone CLS (eg, dual-hormone combining insulin with glucagon or pramlintide) and adjunctive therapy (eg, GLP-1 and SGLT2 inhibitors) also represent promising options. Meal glucose control with the artificial pancreas remains an important challenge for which the optimal strategy is still to be determined.

8. Pharmacologic Approaches to Glycemic Treatment: Standards of Medical Care in Diabetes-2018

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes 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, please refer to the Standards of Care Introduction Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Variables to Be Monitored via Biomedical Sensors for Complete Type 1 Diabetes Mellitus Management: An Extension of the "On-Board" Concept

Type 1 diabetes mellitus (DM1) is a growing disease, and a deep understanding of the patient is required to prescribe the most appropriate treatment, adjusted to the patient's habits and characteristics. Before now, knowledge regarding each patient has been incomplete, discontinuous, and partial. However, the recent development of continuous glucose monitoring (CGM) and new biomedical sensors/gadgets, based on automatic continuous monitoring, offers a new perspective on DM1 management, since these innovative devices allow the collection of 24-hour biomedical data in addition to blood glucose levels. With this, it is possible to deeply characterize a diabetic person, offering a better understanding of his or her illness evolution, and, going further, develop new strategies to manage DM1. This new and global monitoring makes it possible to extend the "on-board" concept to other features. This well-known approach to the processing of variable "insulin" describes some inertias and aggregated/remaining effects. In this work, such analysis is carried out along with a thorough study of the significant variables to be taken into account/monitored-and how to arrange them-for a deep characterization of diabetic patients. Lastly, we present a case study evaluating the experience of the continuous and comprehensive monitoring of a diabetic patient, concluding that the huge potential of this new perspective could provide an acute insight into the patient's status and extract the maximum amount of knowledge, thus improving the DM1 management system in order to be fully functional.

10th Annual Symposium on Self-Monitoring of Blood Glucose, April 27-29, 2017, Warsaw, Poland

International experts in the field of diabetes and diabetes technology met in Warsaw, Poland, for the 10th Annual Symposium on Self-Monitoring of Blood Glucose. The goal of these meetings is to establish a global network of experts to facilitate new collaborations and research projects that can improve the lives of people with diabetes. The 2017 meeting comprised a comprehensive scientific program, parallel interactive workshops, and four keynote lectures.

Effects of Sotagliflozin Added to Insulin in Patients with Type 1 Diabetes

BACKGROUND

In most patients with type 1 diabetes, adequate glycemic control is not achieved with insulin therapy alone. We evaluated the safety and efficacy of sotagliflozin, an oral inhibitor of sodium-glucose cotransporters 1 and 2, in combination with insulin treatment in patients with type 1 diabetes.

METHODS

In this phase 3, double-blind trial, which was conducted at 133 centers worldwide, we randomly assigned 1402 patients with type 1 diabetes who were receiving treatment with any insulin therapy (pump or injections) to receive sotagliflozin (400 mg per day) or placebo for 24 weeks. The primary end point was a glycated hemoglobin level lower than 7.0% at week 24, with no episodes of severe hypoglycemia or diabetic ketoacidosis after randomization. Secondary end points included the change from baseline in glycated hemoglobin level, weight, systolic blood pressure, and mean daily bolus dose of insulin.

RESULTS

A significantly larger proportion of patients in the sotagliflozin group than in the placebo group achieved the primary end point (200 of 699 patients [28.6%] vs. 107 of 703 [15.2%], P<0.001). The least-squares mean change from baseline was significantly greater in the sotagliflozin group than in the placebo group for glycated hemoglobin (difference, -0.46 percentage points), weight (-2.98 kg), systolic blood pressure (-3.5 mm Hg), and mean daily bolus dose of insulin (-2.8 units per day) (P≤0.002 for all comparisons). The rate of severe hypoglycemia was similar in the sotagliflozin group and the placebo group (3.0% [21 patients] and 2.4% [17], respectively). The rate of documented hypoglycemia with a blood glucose level of 55 mg per deciliter (3.1 mmol per liter) or below was significantly lower in the sotagliflozin group than in the placebo group. The rate of diabetic ketoacidosis was higher in the sotagliflozin group than in the placebo group (3.0% [21 patients] and 0.6% [4], respectively).

CONCLUSIONS

Among patients with type 1 diabetes who were receiving insulin, the proportion of patients who achieved a glycated hemoglobin level lower than 7.0% with no severe hypoglycemia or diabetic ketoacidosis was larger in the group that received sotagliflozin than in the placebo group. However, the rate of diabetic ketoacidosis was higher in the sotagliflozin group. (Funded by Lexicon Pharmaceuticals; inTandem3 ClinicalTrials.gov number, NCT02531035 .).

Practical Approaches to Diagnosing, Treating and Preventing Hypoglycemia in Diabetes

Hypoglycemia in individuals with diabetes can increase the risk of morbidity and all-cause mortality in this patient group, particularly in the context of cardiovascular impairment, and can significantly decrease the quality of life. Hypoglycemia can present one of the most difficult aspects of diabetes management from both a patient and healthcare provider perspective. Strategies used to reduce the risk of hypoglycemia include individualizing glucose targets, selecting the appropriate medication, modifying diet and lifestyle and applying diabetes technology. Using a patient-centered care approach, the provider should work in partnership with the patient and family to prevent hypoglycemia through evidence-based management of the disease and appropriate education.

Twelve-Week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin A1c and Hypoglycemia

OBJECTIVE

Artificial pancreas (AP) systems are best positioned for optimal treatment of type 1 diabetes (T1D) and are currently being tested in outpatient clinical trials. Our consortium developed and tested a novel adaptive AP in an outpatient, single-arm, uncontrolled multicenter clinical trial lasting 12 weeks.

RESEARCH DESIGN AND METHODS

Thirty adults with T1D completed a continuous glucose monitor (CGM)-augmented 1-week sensor-augmented pump (SAP) period. After the AP was started, basal insulin delivery settings used by the AP for initialization were adapted weekly, and carbohydrate ratios were adapted every 4 weeks by an algorithm running on a cloud-based server, with automatic data upload from devices. Adaptations were reviewed by expert study clinicians and patients. The primary end point was change in hemoglobin A_1c (HbA_1c). Outcomes are reported adhering to consensus recommendations on reporting of AP trials.

RESULTS

Twenty-nine patients completed the trial. HbA_1c, 7.0 ± 0.8% at the start of AP use, improved to 6.7 ± 0.6% after 12 weeks (-0.3, 95% CI -0.5 to -0.2, P < 0.001). Compared with the SAP run-in, CGM time spent in the hypoglycemic range improved during the day from 5.0 to 1.9% (-3.1, 95% CI -4.1 to -2.1, P < 0.001) and overnight from 4.1 to 1.1% (-3.1, 95% CI -4.2 to -1.9, P < 0.001). Whereas carbohydrate ratios were adapted to a larger extent initially with minimal changes thereafter, basal insulin was adapted throughout. Approximately 10% of adaptation recommendations were manually overridden. There were no protocol-related serious adverse events.

CONCLUSIONS

Use of our novel adaptive AP yielded significant reductions in HbA_1c and hypoglycemia.

The Effect of Prior Continuous Glucose Monitoring Use on Glycemic Outcomes in the Pivotal Trial of the MiniMed™ 670G Hybrid Closed-Loop System

A 3-month pivotal trial using the MiniMed™ 670G hybrid closed-loop (HCL) system in adolescent and adult patients with type 1 diabetes (T1D), relative to a 2-week baseline run-in period, resulted in increased sensor glucose (SG) values in target range (71-180 mg/dL), reduced HbA1c levels, and no events of diabetic ketoacidosis or severe hypoglycemia ( Clinicaltrials.gov : NCT02463097). This brief report evaluated how prior continuous glucose monitoring (CGM) experience influenced glycemic outcomes, in the same pivotal trial. HbA1c levels and the percentage of SG values in low, high, and in-target ranges were analyzed from participants (n = 124) completing the Hybrid Closed-Loop Pivotal Trial in T1D. There were 78 individuals comprising the prior CGM group and 46 comprising the no prior CGM group. Compared to baseline, HbA1c was reduced from 7.4% ± 0.9% to 6.9% ± 0.7% for the prior CGM group and from 7.5% ± 0.9% to 6.8% ± 0.5% for the no prior CGM group. For those with prior CGM experience, the mean percentage of in-target SG values increased from 66.9% ± 12.5% to 72.6% ± 9.1%, and for those with no prior CGM experience it increased from 66.6% ± 11.7% to 71.5% ± 8.5%. Similar improvement in glucose values in the low and high ranges, relative to baseline, was observed for both groups. Resulting outcomes, from baseline to study end, did not differ between each group. These findings suggest that individuals without prior CGM experience, and those already using CGM, will benefit similarly with use of the FDA-approved MiniMed 670G HCL system therapy.

A Personalized Week-to-Week Updating Algorithm to Improve Continuous Glucose Monitoring Performance

BACKGROUND

Continuous glucose monitoring (CGM) systems are increasingly becoming essential components in type 1 diabetes mellitus (T1DM) management. Current CGM technology requires frequent calibration to ensure accurate sensor performance. The accuracy of these systems is of great importance since medical decisions are made based on monitored glucose values and trends.

METHODS

In this work, we introduce a calibration strategy that is augmented with a weekly updating feature. During the life cycle of the sensor, the calibration mechanism periodically estimates the parameters of a calibration model to fit self-monitoring blood glucose (SMBG) measurements. At the end of each week of use, an optimization problem that minimizes the sum of squared residuals between past reference and predicted blood glucose values is solved remotely to identify personalized calibration parameters. The newly identified parameters are used to initialize the calibration mechanism of the following week.

RESULTS

The proposed method was evaluated using two sets of clinical data both consisting of 6 weeks of Dexcom G4 Platinum CGM data on 10 adults with T1DM (over 10 000 hours of CGM use), with seven SMBG data points per day measured by each subject in an unsupervised outpatient setting. Updating the calibration parameters using the history of calibration data indicated a positive trend of improving CGM performance.

CONCLUSIONS

Although not statistically significant, the updating framework showed a relative improvement of CGM accuracy compared to the non-updating, static calibration method. The use of information collected for longer periods is expected to improve the performance of the sensor over time.

Type 1 diabetes: where are we in 2017?

Type 1 diabetes mellitus is a chronic state of insulin deficiency which results from destruction of beta cells by the immune system. The long term microvascular and macrovascular complications can be devastating. Since the discovery of insulin almost 100 years ago new medical therapies have improved the long-term survival for people with type 1 diabetes. Each year we come closer to discovering a cure but much work still needs to be done to eliminate this disease.

Keeping Up with the Diabetes Technology: 2016 Endocrine Society Guidelines of Insulin Pump Therapy and Continuous Glucose Monitor Management of Diabetes

PURPOSE OF REVIEW

Decades after the invention of insulin pump, diabetes management has encountered a technology revolution with the introduction of continuous glucose monitoring, sensor-augmented insulin pump therapy and closed-loop/artificial pancreas systems. In this review, we discuss the significance of the 2016 Endocrine Society Guidelines for insulin pump therapy and continuous glucose monitoring and summarize findings from relevant diabetes technology studies that were conducted after the publication of the 2016 Endocrine Society Guidelines.

RECENT FINDINGS

The 2016 Endocrine Society Guidelines have been a great resource for clinicians managing diabetes in this new era of diabetes technology. There is good body of evidence indicating that using diabetes technology systems safely tightens glycemic control while managing both type 1 and type 2 diabetes. The first-generation diabetes technology systems will evolve as we gain more experience and collaboratively work to improve them with an ultimate goal of keeping people with diabetes complication and burden-free until the cure for diabetes becomes a reality.

Insulin delivery and nocturnal glucose control in children and adolescents with type 1 diabetes

Introduction: Nocturnal glucose control remains challenging in children and adolescents with type 1 diabetes due to highly variable overnight insulin requirements. The issue may be addressed by glucose responsive insulin delivery based on real-time continuous glucose measurements.

Areas covered: This review outlines recent developments of glucose responsive insulin delivery systems from a paediatric perspective. We cover threshold-based suspend application, predictive low glucose suspend, and more advanced single hormone and dual-hormone closed-loop systems. Approaches are evaluated in relation to nocturnal glucose control particularly during outpatient randomised controlled trials.

Expert opinion: Significant progress translating research from controlled clinical centre settings to free-living unsupervised home studies have been achieved over the past decade. Nocturnal glycaemic control can be improved whilst reducing the risk of hypoglycaemia with closed-loop systems. Following the US regulatory approval of the first hybrid closed-loop system in non-paediatric population, large multinational closed-loop clinical trials and pivotal studies including paediatric populations are underway or in preparation to facilitate the use of closed-loop systems in clinical practice.