Effect of artificial pancreas systems on glycaemic control in patients with type 1 diabetes: a systematic review and meta-analysis of outpatient randomised controlled trials

Six Months of Hybrid Closed-Loop Versus Manual Insulin Delivery With Fingerprick Blood Glucose Monitoring in Adults With Type 1 Diabetes: A Randomized, Controlled Trial

OBJECTIVE

To investigate glycemic and psychosocial outcomes with hybrid closed-loop (HCL) versus user-determined insulin dosing with multiple daily injections (MDI) or insulin pump (i.e., standard therapy for most adults with type 1 diabetes).

RESEARCH DESIGN AND METHODS

Adults with type 1 diabetes using MDI or insulin pump without continuous glucose monitoring (CGM) were randomized to 26 weeks of HCL (Medtronic 670G) or continuation of current therapy. The primary outcome was masked CGM time in range (TIR; 70-180 mg/dL) during the final 3 weeks.

RESULTS

Participants were randomized to HCL (n = 61) or control (n = 59). Baseline mean (SD) age was 44.2 (11.7) years, HbA_1c was 7.4% (0.9%) (57 [10] mmol/mol), 53% were women, and 51% used MDI. HCL TIR increased from (baseline) 55% (13%) to (26 weeks) 70% (10%) with the control group unchanged: (baseline) 55% (12%) and (26 weeks) 55% (13%) (difference 15% [95% CI 11, 19]; P < 0.0001). For HCL, HbA_1c was lower (median [95% CI] difference -0.4% [-0.6, -0.2]; -4 mmol/mol [-7, -2]; P < 0.0001) and diabetes-specific positive well-being was higher (difference 1.2 [95% CI 0.4, 1.9]; P < 0.0048) without a deterioration in diabetes distress, perceived sleep quality, or cognition. Seventeen (9 device-related) versus 13 serious adverse events occurred in the HCL and control groups, respectively.

CONCLUSIONS

In adults with type 1 diabetes, 26 weeks of HCL improved TIR, HbA_1c, and their sense of satisfaction from managing their diabetes compared with those continuing with user-determined insulin dosing and self-monitoring of blood glucose. For most people living with type 1 diabetes globally, this trial demonstrates that HCL is feasible, acceptable, and advantageous.

Prospective Analysis of the Impact of Commercialized Hybrid Closed-Loop System on Glycemic Control, Glycemic Variability, and Patient-Related Outcomes in Children and Adults: A Focus on Superiority Over Predictive Low-Glucose Suspend Technology

Background: Automatization of insulin delivery by closed-loop systems represents a major step in type 1 diabetes management. The aim of this study was to analyze the effect of the commercialized hybrid closed-loop system, the MiniMed 670G system, on glycemic control, glycemic variability, and patient satisfaction. Methods: A prospective study, including type 1 diabetes patients consecutively starting on the 670G system in one adult and two pediatric hospitals, was performed. Baseline and 3-month visits were documented. Two weeks of data from the system were downloaded. Glycemic variability measures were calculated. Adults and adolescents completed a set of questionnaires (Gold and Clarke scores, Hypoglycemia Fear Survey, Diabetes Quality of Life [DQoL], Diabetes Treatment Satisfaction [DTS], Diabetes Distress Scale, Pittsburgh Sleep Quality Index). Results: Fifty-eight patients were included (age: 28 ± 15 years [7-63], <18 years old: 38% [n = 22], 59% [n = 34] females, previous use of SAP-PLGS [predictive low-glucose suspend]: 60% [n = 35]). HbA1c was reduced from 57 ± 10 to 53 ± 7 mmol/L (7.4% ± 0.9% to 7.0% ± 0.6%) (P < 0.001) and time in range 70-180 mg/dL was increased from 63.0% ± 11.4% to 72.7% ± 8.7% (P < 0.001). In patients with high baseline hypoglycemia risk, time <54 and <70 mg/dL were reduced from 0.9% ± 1.1% to 0.45% ± 0.7% (P = 0.021) and from 3.3% ± 2.8% to 2.1% ± 2.1% (P = 0.019), respectively. Glycemic variability measures improved. Time in auto mode was 85% ± 17%, the number of auto mode exits was 0.6 ± 0.3 per day, and the number of alarms was 8.5 ± 3.7 per day. Fear of hypoglycemia, DQoL, DTS, and diabetes distress improved, while the percentage of patients with poor sleep quality was reduced. The discontinuation rate was 3%. Conclusion: The commercialized hybrid closed-loop system improves glycemic control and glycemic variability in children and adults, reducing the burden of living with type 1 diabetes.

Closed-loop insulin delivery systems in children and adolescents with type 1 diabetes

Introduction: Optimal glycemic control remains challenging in children and adolescents with type 1 diabetes due to highly variable day-to-day and night-to-night insulin requirements. This hurdle could be addressed by glucose-responsive insulin delivery based on real-time continuous glucose measurements.Areas covered: This review summaries recent advances of closed-loop systems in children and adolescents with type 1 diabetes, using both single- and dual-hormone closed-loop systems. The main outcomes, proportions of time spent in target range 70-180 mg/dl, and time spent in hypoglycemia below 70 mg/dl, are assessed particularly during unsupervised free-living randomized controlled trials.Expert opinion: Noteworthy and clinically meaningful translation of experimental investigations from controlled in-hospital settings to unrestricted home studies have been achieved over the past years, resulting in the regulatory approval of the first hybrid closed-loop system also in the pediatric population and with several other advanced devices in the pipeline. Large multinational and pivotal clinical trials including broad age populations are underway to facilitate the use of closed-loop systems in routine clinical practice.

Practical implementation of automated closed-loop insulin delivery: A French position statement

Automated closed-loop (CL) insulin therapy has come of age. This major technological advance is expected to significantly improve the quality of care for adults, adolescents and children with type 1 diabetes. To improve access to this innovation for both patients and healthcare professionals (HCPs), and to promote adherence to its requirements in terms of safety, regulations, ethics and practice, the French Diabetes Society (SFD) brought together a French Working Group of experts to discuss the current practical consensus. The result is the present statement describing the indications for CL therapy with emphasis on the idea that treatment expectations must be clearly defined in advance. Specifications for expert care centres in charge of initiating the treatment were also proposed. Great importance was also attached to the crucial place of high-quality training for patients and healthcare professionals. Long-term follow-up should collect not only metabolic and clinical results, but also indicators related to psychosocial and human factors. Overall, this national consensus statement aims to promote the introduction of marketed CL devices into standard clinical practice.

Glycemic control in people with type 1 diabetes using a hybrid closed loop system and followed by telemedicine during the COVID-19 pandemic in Italy

AIMS

This study aims at evaluating the metrics of glycemic control in people with type 1 diabetes using the hybrid closed loop (HCL) system during the COVID-19 lockdown.

METHODS

This is a retrospective study of thirty adults with type 1 diabetes using HCL and followed with telemedicine at an Italian University Hospital. Data on metrics of glucose control were collected at different times: two weeks before the lockdown (Time 0), first two weeks of lockdown (Time 1), last two weeks of lockdown (Time 2) and first two weeks after the lockdown (Time 3). The primary endpoint was the change in glucose management indicator (GMI) across the different time points.

RESULTS

GMI did not worsen over time (Time 1 vs Time 3, 7% vs 6.9%, P < 0.05), whereas a reduction of mean glucose (P = 0.004) and indices of glucose variability was observed. Time in range (TIR) significantly increased (68.5% vs 73.5%, P = 0.012), and time above range (TAR) level 2 (251-400 mg/dL) significantly decreased (P = 0.002). The improvement of TIR and glucose variability was mainly observed in participants < 35 years.

CONCLUSIONS

Adults with type 1 diabetes using HCL showed a significant improvement of most of the metrics of glucose control during the COVID-19 lockdown.

Dual-Hormone Closed-Loop System Using a Liquid Stable Glucagon Formulation Versus Insulin-Only Closed-Loop System Compared With a Predictive Low Glucose Suspend System: An Open-Label, Outpatient, Single-Center, Crossover, Randomized Controlled Trial

OBJECTIVE

To assess the efficacy and feasibility of a dual-hormone (DH) closed-loop system with insulin and a novel liquid stable glucagon formulation compared with an insulin-only closed-loop system and a predictive low glucose suspend (PLGS) system.

RESEARCH DESIGN AND METHODS

In a 76-h, randomized, crossover, outpatient study, 23 participants with type 1 diabetes used three modes of the Oregon Artificial Pancreas system: 1) dual-hormone (DH) closed-loop control, 2) insulin-only single-hormone (SH) closed-loop control, and 3) PLGS system. The primary end point was percentage time in hypoglycemia (<70 mg/dL) from the start of in-clinic aerobic exercise (45 min at 60% VO_2max) to 4 h after.

RESULTS

DH reduced hypoglycemia compared with SH during and after exercise (DH 0.0% [interquartile range 0.0-4.2], SH 8.3% [0.0-12.5], P = 0.025). There was an increased time in hyperglycemia (>180 mg/dL) during and after exercise for DH versus SH (20.8% DH vs. 6.3% SH, P = 0.038). Mean glucose during the entire study duration was DH, 159.2; SH, 151.6; and PLGS, 163.6 mg/dL. Across the entire study duration, DH resulted in 7.5% more time in target range (70-180 mg/dL) compared with the PLGS system (71.0% vs. 63.4%, P = 0.044). For the entire study duration, DH had 28.2% time in hyperglycemia vs. 25.1% for SH (P = 0.044) and 34.7% for PLGS (P = 0.140). Four participants experienced nausea related to glucagon, leading three to withdraw from the study.

CONCLUSIONS

The glucagon formulation demonstrated feasibility in a closed-loop system. The DH system reduced hypoglycemia during and after exercise, with some increase in hyperglycemia.

A qualitative study exploring the expectations of people living with type 1 diabetes regarding prospective use of a hybrid closed-loop system

AIM

To identify the expectations of a diversified sample of informed adults with type 1 diabetes on their prospective use of a hybrid closed-loop system.

METHODS

Semi-structured interviews were conducted with 16 adults with type 1 diabetes who shared their expectations on an experimental hybrid closed-loop system after receiving information on its design, functioning and capability. The sample had equal representation of genders and diabetes management methods and was diversified according to age, education and occupation when possible. Qualitative content analysis of the interview transcripts with MaxQDA was used to identify expected benefits, expected inconveniences and concerns, expected improvements to design and functionalities, and interest and trust in the system.

RESULTS

Participants expected benefits regarding diabetes management, clinical outcomes, psychosocial aspects of their lives, nutrition and meals, and physical activity. Participants expected inconveniences or shared concerns regarding wearability, costs and technical limitations. According to participants, improvements could be made to the system's physical appearance, practical convenience, functionalities, and software integration. Overall, 12 participants would use the system. While participants' trust could be immediate or grow over time, it could ultimately be conditional on the system's performance.

CONCLUSION

Prospective users' general enthusiasm and trust foster the clinical and commercial success of hybrid closed-loop systems. However, poor user satisfaction caused by unrealistic expectations and plausible inconveniences and concerns may limit this success. Providing prospective users with comprehensive information while validating their understanding could mitigate unrealistic expectations. Improvements to design and coverage policies could favour uptake.

Hypoglycaemia and its management in primary care setting

Hypoglycaemia is common in patients with type 1 diabetes and type 2 diabetes and constitutes a major limiting factor in achieving glycaemic control among people with diabetes. While hypoglycaemia is defined as a blood glucose level under 70 mg/dL (3.9 mmol/L), symptoms may occur at higher blood glucose levels in individuals with poor glycaemic control. Severe hypoglycaemia is defined as an episode requiring the assistance of another person to actively administer carbohydrate, glucagon, or take other corrective actions to assure neurologic recovery. Hypoglycaemia is the most important safety outcome in clinical studies of glucose lowering agents. The American Diabetes Association Standards of Medical Care recommends that a management protocol for hypoglycaemia should be designed and implemented by every hospital, along with a clear prevention and treatment plan. A tailored approach, using clinical and pathophysiologic disease stratification, can help individualize glycaemic goals and promote new therapies to improve quality of life of patients. Data from recent large clinical trials reported low risk of hypoglycaemic events with the use of newer anti-diabetic drugs. Increased hypoglycaemia risk is observed with the use of insulin and/or sulphonylureas. Vulnerable patients with T2D at dual risk of severe hypoglycaemia and cardiovascular outcomes show features of "frailty." Many of such patients may be better treated by the use of GLP-1 receptor agonists or SGLT2 inhibitors rather than insulin. Continuous glucose monitoring (CGM) should be considered for all individuals with increased risk for hypoglycaemia, impaired hypoglycaemia awareness, frequent nocturnal hypoglycaemia and with history of severe hypoglycaemia. Patients with impaired awareness of hypoglycaemia benefit from real-time CGM. The diabetes educator is an invaluable resource and can devote the time needed to thoroughly educate the individual to reduce the risk of hypoglycaemia and integrate the information within the entire construct of diabetes self-management. Conversations about hypoglycaemia facilitated by a healthcare professional may reduce the burden and fear of hypoglycaemia among patients with diabetes and their family members. Optimizing insulin doses and carbohydrate intake, in addition to a short warm up before or after the physical activity sessions may help avoiding hypoglycaemia. Several therapeutic considerations are important to reduce hypoglycaemia risk during pregnancy including administration of rapid-acting insulin analogues rather than human insulin, pre-conception initiation of insulin analogues, and immediate postpartum insulin dose reduction.

Use of a Hybrid Adeno-Associated Viral Vector Transposon System to Deliver the Insulin Gene to Diabetic NOD Mice

Previously, we used a lentiviral vector to deliver furin-cleavable human insulin (INS-FUR) to the livers in several animal models of diabetes using intervallic infusion in full flow occlusion (FFO), with resultant reversal of diabetes, restoration of glucose tolerance and pancreatic transdifferentiation (PT), due to the expression of beta (β)-cell transcription factors (β-TFs). The present study aimed to determine whether we could similarly reverse diabetes in the non-obese diabetic (NOD) mouse using an adeno-associated viral vector (AAV) to deliver INS-FUR ± the β-TF Pdx1 to the livers of diabetic mice. The traditional AAV8, which provides episomal expression, and the hybrid AAV8/piggyBac that results in transgene integration were used. Diabetic mice that received AAV8-INS-FUR became hypoglycaemic with abnormal intraperitoneal glucose tolerance tests (IPGTTs). Expression of β-TFs was not detected in the livers. Reversal of diabetes was not achieved in mice that received AAV8-INS-FUR and AAV8-Pdx1 and IPGTTs were abnormal. Normoglycaemia and glucose tolerance were achieved in mice that received AAV8/piggyBac-INS-FUR/FFO. Definitive evidence of PT was not observed. This is the first in vivo study using the hybrid AAV8/piggyBac system to treat Type 1 diabetes (T1D). However, further development is required before the system can be used for gene therapy of T1D.

Glucagon for hypoglycaemia treatment in type 1 diabetes

To achieve strict glycaemic control and avoid chronic diabetes complications, individuals with type 1 diabetes (T1D) are recommended to follow an intensive insulin regimen. However, the risk and fear of hypoglycaemia often prevent individuals from achieving the treatment goals. Apart from early insulin suspension in insulin pump users, carbohydrate ingestion is the only option for preventing and treating non-severe hypoglycaemic events. These rescue treatments may give extra calories and cause overweight. As an alternative, the use of low-dose glucagon to counter hypoglycaemia has been proposed as a tool to raise glucose concentrations without adding extra calories. Previously, the commercially available glucagon formulations required reconstitution from powder to a solution before being injected subcutaneously or intramuscularly-making it practical only for treating severe hypoglycaemia. Several companies have developed more stable formulations that do not require the time-consuming reconstitution process before use. As well as treating severe hypoglycaemia, non-severe and impending hypoglycaemia can also be treated with lower doses of glucagon. Once available, low-dose glucagon can be either delivered manually, as an injection, or automatically, by an infusion pump. This review focuses on the role and perspectives of using glucagon to treat and prevent hypoglycaemia in T1D.

Lessons from Use of Continuous Glucose Monitoring Systems in Digital Healthcare

We live in a digital world where a variety of wearable medical devices are available. These technologies enable us to measure our health in our daily lives. It is increasingly possible to manage our own health directly through data gathered from these wearable devices. Likewise, healthcare professionals have also been able to indirectly monitor patients' health. Healthcare professionals have accepted that digital technologies will play an increasingly important role in healthcare. Wearable technologies allow better collection of personal medical data, which healthcare professionals can use to improve the quality of healthcare provided to the public. The use of continuous glucose monitoring systems (CGMS) is the most representative and desirable case in the adoption of digital technology in healthcare. Using the case of CGMS and examining its use from the perspective of healthcare professionals, this paper discusses the necessary adjustments required in clinical practices. There is a need for various stakeholders, such as medical staff, patients, industry partners, and policy-makers, to utilize and harness the potential of digital technology.

Exposure to Closed Loop Barriers Using Virtual Reality

BACKGROUND

Closed loop (CL) automated insulin delivery systems are demonstrated to be safe and effective in regulating glucose levels and reducing cognitive burden in people with type 1 diabetes (T1D). However, given the limited market options and the do-it-yourself nature of most systems, it can be difficult for potential users to shape their expectations fitting them into daily lives and management routines. As such, we examined the potential feasibility of a virtual reality (VR) intervention.

METHODS

A four-part VR intervention was created to expose adults with T1D to expected CL system barriers: body image, perceived hassles of using CL, deskilling fears, and unwanted social attention. Goals of the pilot were to assess feasibility and expose patients to CL. Surveys were conducted pre- and postparticipating in the VR experience.

RESULTS

A total of 20 adults with T1D completed the pilot. Average time to complete the experience was 14.1 minutes (8.8-39.9). Reported VR sickness was low. Willingness to use VR was maintained in 90% (n = 18) and did not change expectations of CL in 95% (n = 19). Virtual reality changed perceived hassles of CL in 25% (n = 5) with four concerned over alarms and one connectivity issues: positive diabetes technology attitudes, confidence in managing hypoglycemia, overall perceptions of appearance, and positive affect maintained after the VR intervention. Negative affect significantly decreased after exposure and perceptions of being overweight trended toward significance.

CONCLUSION

This pilot VR intervention demonstrated high potential in addressing expected barriers to uptake and usage of CL systems without decreasing enthusiasm or changing expectations of CL.

Assessment of Risks and Benefits of Beta Cell Replacement Versus Automated Insulin Delivery Systems for Type 1 Diabetes

PURPOSE OF REVIEW

Current approaches to insulin replacement in type 1 diabetes are unable to achieve optimal levels of glycemic control without substantial risk of hypoglycemia and substantial burden of self-management. Advances in biology and technology present beta cell replacement and automated insulin delivery as two alternative approaches. Here we discuss current and future prospects for the relative risks and benefits for biological and psychosocial outcomes from the perspective of researchers, clinicians, and persons living with diabetes.

RECENT FINDINGS

Beta cell replacement using pancreas or islet transplant can achieve insulin independence but requires immunosuppression. Although insulin independence may not be sustained, time in range of 80-90%, minimal glycemic variability and abolition of hypoglycemia is routine after islet transplantation. Clinical trials of potentially unlimited supply of stem cell-derived beta cells are showing promise. Automated insulin delivery (AID) systems can achieve 70-75% time in range, with reduced glycemic variability. Impatient with the pace of commercially available AID, users have developed their own algorithms which appear to be at least equivalent to systems developed within conventional regulatory frameworks. The importance of psychosocial factors and the preferences and values of persons living with diabetes are emerging as key elements on which therapies should be evaluated beyond their impact of biological outcomes. Biology or technology to deliver glucose dependent insulin secretion is associated with substantial improvements in glycemia and prevention of hypoglycemia while relieving much of the substantial burden of diabetes. Automated insulin delivery, currently, represents a more accessible bridge to a biologic cure that we expect future cellular therapies to deliver.

Use of a do-it-yourself artificial pancreas system is associated with better glucose management and higher quality of life among adults with type 1 diabetes

BACKGROUND

Previous studies show that the use of do-it-yourself artificial pancreas system (DIYAPS) may be associated with better glycemic control characterized by improved estimated hemoglobin A1c (eHbA1c) and time in range among adults with type 1 diabetes (T1D). However, few studies have demonstrated the changes in laboratory-measured HbA1c, which is a more accepted index for glycemic control, after using a DIYAPS.

METHODS

This is a retrospective before-after study approaching patients who reported self-use of AndroidAPS. The main inclusion criteria included: T1D; aged ⩾18 years; having complete record of ⩾3 months of continuous AndroidAPS use; with laboratory-measured HbA1c and quality of life scale data before and after 3 months of AndroidAPS use; and not pregnant. The primary outcome was the change in HbA1c between baseline and 3 months after initiation of AndroidAPS use.

RESULTS

Overall, 15 patients (10 females) were included; the median age was 32.2 years (range: 19.2-69.4), median diabetes duration was 9.7 years (range: 1.8-23.7) and median baseline HbA1c was 7.3% (range: 6.4-10.1). The 3 months of AndroidAPS use was associated with substantial reductions in HbA1c [6.79% (SD: 1.29) versus 7.63% (SD: 1.06), p = 0.002] and glycemic variability when compared with sensor-augmented pump therapy. A lower level of fear of hypoglycemia [22.13 points (SD: 6.87) versus 26.27 points (SD: 5.82), p = 0.010] was also observed after using AndroidAPS.

CONCLUSIONS

The 3 months of AndroidAPS use was associated with significant improvements in glucose management and quality of life among adults with T1D.

Glycemic Outcomes of Use of CLC Versus PLGS in Type 1 Diabetes: A Randomized Controlled Trial

OBJECTIVE

Limited information is available about glycemic outcomes with a closed-loop control (CLC) system compared with a predictive low-glucose suspend (PLGS) system.

RESEARCH DESIGN AND METHODS

After 6 months of use of a CLC system in a randomized trial, 109 participants with type 1 diabetes (age range, 14-72 years; mean HbA_1c, 7.1% [54 mmol/mol]) were randomly assigned to CLC (N = 54, Control-IQ) or PLGS (N = 55, Basal-IQ) groups for 3 months. The primary outcome was continuous glucose monitor (CGM)-measured time in range (TIR) for 70-180 mg/dL. Baseline CGM metrics were computed from the last 3 months of the preceding study.

RESULTS

All 109 participants completed the study. Mean ± SD TIR was 71.1 ± 11.2% at baseline and 67.6 ± 12.6% using intention-to-treat analysis (69.1 ± 12.2% using per-protocol analysis excluding periods of study-wide suspension of device use) over 13 weeks on CLC vs. 70.0 ± 13.6% and 60.4 ± 17.1% on PLGS (difference = 5.9%; 95% CI 3.6%, 8.3%; P < 0.001). Time >180 mg/dL was lower in the CLC group than PLGS group (difference = -6.0%; 95% CI -8.4%, -3.7%; P < 0.001) while time <54 mg/dL was similar (0.04%; 95% CI -0.05%, 0.13%; P = 0.41). HbA_1c after 13 weeks was lower on CLC than PLGS (7.2% [55 mmol/mol] vs. 7.5% [56 mmol/mol], difference -0.34% [-3.7 mmol/mol]; 95% CI -0.57% [-6.2 mmol/mol], -0.11% [1.2 mmol/mol]; P = 0.0035).

CONCLUSIONS

Following 6 months of CLC, switching to PLGS reduced TIR and increased HbA_1c toward their pre-CLC values, while hypoglycemia remained similarly reduced with both CLC and PLGS.

Safety and Efficacy of Initializing the Control-IQ Artificial Pancreas System Based on Total Daily Insulin in Adolescents with Type 1 Diabetes

Objective: To assess the safety and efficacy of a simplified initialization for the Tandem t:slim X2 Control-IQ hybrid closed-loop system, using parameters based on total daily insulin ("MyTDI") in adolescents with type 1 diabetes under usual activity and during periods of increased exercise. Research Design and Methods: Adolescents with type 1 diabetes 12-18 years of age used Control-IQ for 5 days at home using their usual parameters. Upon arrival at a 60-h ski camp, participants were randomized to either continue Control-IQ using their home settings or to reinitialize Control-IQ with MyTDI parameters. Control-IQ use continued for 5 days following camp. The effect of MyTDI on continuous glucose monitoring outcomes were analyzed using repeated measures analysis of variance (ANOVA): baseline, camp, and at home. Results: Twenty participants were enrolled and completed the study; two participants were excluded from the analysis due to absence from ski camp (1) and illness (1). Time in range was similar between both groups at home and camp. A tendency to higher time <70 mg/dL in the MyTDI group was present but only during camp (median 3.8% vs. 1.4%, P = 0.057). MyTDI users with bolus/TDI ratios >40% tended to show greater time in the euglycemic range improvements between baseline and home than users with ratios <40% (+16.3% vs. -9.0%, P = 0.012). All participants maintained an average of 95% time in closed loop (84.1%-100%). Conclusions: MyTDI is a safe, effective, and easy way to determine insulin parameters for use in the Control-IQ artificial pancreas. Future modifications to account for the influence of carbohydrate intake on MyTDI calculations might further improve time in range.

Time in Range for Multiple Technologies in Type 1 Diabetes: A Systematic Review and Network Meta-analysis

BACKGROUND

Time in range is a key glycemic metric, and comparisons of management technologies for this outcome are critical to guide device selection.

PURPOSE

We conducted a systematic review and network meta-analysis to compare and rank technologies for time in glycemic ranges.

DATA SOURCES

We searched Evidenced-Based Medicine Reviews, CINAHL, Embase, MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PROSPERO, PsycInfo, PubMed, and Web of Science until 24 April 2019.

STUDY SELECTION

We included randomized controlled trials ≥2 weeks' duration comparing technologies for management of type 1 diabetes in adults (≥18 years of age), excluding pregnant women.

DATA EXTRACTION

Data were extracted using a predefined template. Outcomes were percent time with sensor glucose levels 3.9-10.0 mmol/L (70-180 mg/dL), >10.0 mmol/L (180 mg/dL), and <3.9 mmol/L (70 mg/dL).

DATA SYNTHESIS

We identified 16,772 publications, of which 14 eligible studies compared eight technologies comprising 1,043 participants. Closed-loop systems led to greater percent time in range than any other management strategy, and mean percent time in range was 17.85 (95% predictive interval 7.56-28.14) longer than with usual care of multiple daily injections with capillary glucose testing. Closed-loop systems ranked best for percent time in range or above range with use of Surface Under the Cumulative RAnking curve (SUCRA) (98.5% and 93.5%, respectively). Closed-loop systems also ranked highly for time below range (SUCRA 62.2%).

LIMITATIONS

Overall risk of bias ratings were moderate for all outcomes. Certainty of evidence was very low.

CONCLUSIONS

In the first integrated comparison of multiple management strategies considering time in range, we found that the efficacy of closed-loop systems appeared better than all other approaches.

Closed-loop control in insulin pumps for type-1 diabetes mellitus: safety and efficacy

INTRODUCTION

Type 1 diabetes is a lifelong disease with high management burden. The majority of people with type 1 diabetes fail to achieve glycemic targets. Algorithm-driven automated insulin delivery (closed-loop) systems aim to address these challenges. This review provides an overview of commercial and emerging closed-loop systems.

AREAS COVERED

We review safety and efficacy of commercial and emerging hybrid closed-loop systems. A literature search was conducted and clinical trials using day-and-night closed-loop systems during free-living conditions were used to report on safety data. We comment on efficacy where robust randomized controlled trial data for a particular system are available. We highlight similarities and differences between commercial systems.

EXPERT OPINION

Study data shows that hybrid closed-loop systems are safe and effective, consistently improving glycemic control when compared to standard therapy. While a fully closed-loop system with minimal burden remains the end-goal, these hybrid closed-loop systems have transformative potential in diabetes care.

Time In Range in Children with Type 1 Diabetes Using Treatment Strategies Based on Nonautomated Insulin Delivery Systems in the Real World

Background: Glucose sensors consist of real-time continuous glucose monitoring (rtCGM) and intermittently scanned CGM (isCGM). Their clinical use has been widely increasing during the past 5 years. The aim of this study is to evaluate percentage of time in range (TIR) in a large group of children with type 1 diabetes (T1D) using glucose sensors with nonautomated insulin delivery systems, in a real-world setting. Methods: An 11-center cross-sectional study was conducted during January-May 2019. Children with T1D <18 years, all using rtCGM or isCGM for >1 year, treated with multiple daily injections (MDI) or nonautomated insulin pump (IP), were recruited consecutively. Clinical data, HbA1c measurement, and CGM downloaded data were collected by each center and included in a centralized database for the analysis. Glucose metrics of four treatment strategies were analyzed: isCGM-MDI, rtCGM-MDI, isCGM-IP, and rtCGM-IP. Results: Data from 666 children with T1D (51% male and 49% female), median age 12 years, diabetes duration 5 years, were analyzed. An rtCGM was used by 51% of the participants, and a nonautomated IP by 46%. For isCGM-MDI, rtCGM-MDI, isCGM-IP, and rtCGM-IP, the median TIR 70-180 mg/dL values were 49%, 56%, 56%, and 61% (P < 0.001), respectively; HbA1c 7.6%, 7.5%, 7.3%, and 7.3% (P < 0.001), respectively. Use of rtCGM was associated with significant lower time below target range <70 mg/dL and reduced the percentage coefficient of variation of glucose (%CV), independently by the insulin delivery system used. Conclusions: Among nonautomated insulin delivery strategies, simultaneous use of rtCGM and IP was associated with higher percentage of TIR, lower time above range >180 mg/dL and lower HbA1c. If there are no barriers, an upgrade of the treatment strategy with a higher performing technology should be offered to all children who do not achieve blood glucose metrics within the suggested range.

Toward precision health: applying artificial intelligence analytics to digital health biometric datasets

The rapid development of digital health devices has enabled patients to engage in their care to an unprecedented degree and holds the possibility of significantly improving the diagnosis, treatment and monitoring of many medical conditions. Combined with the emergence of artificial intelligence algorithms, biometric datasets produced from these digital health devices present new opportunities to create precision-based, personalized approaches for healthcare delivery. For effective implementation of such innovations to patient care, clinicians will require an understanding of the types of datasets produced from digital health technologies; the types of analytic methods including feature selection, convolution neural networking, and deep learning that can be used to analyze digital data; and how the interpretation of these findings are best translated to patient care. In this perspective, we aim to provide the groundwork for clinicians to be able to apply artificial intelligence to this transformation of healthcare.

CREATE (Community deRivEd AutomaTEd insulin delivery) trial. Randomised parallel arm open label clinical trial comparing automated insulin delivery using a mobile controller (AnyDANA-loop) with an open-source algorithm with sensor augmented pump therapy in type 1 diabetes

Background

Commercialised automated insulin delivery (AID) systems have demonstrated improved outcomes in type 1 diabetes (T1D), however, they have limited capacity for algorithm individualisation, and can be prohibitively expensive if an individual is without access to health insurance or health funding subsidy. Freely available open-source algorithms, which have the ability to individualise algorithm parameters paired with commercial insulin pumps, and continuous glucose monitoring make up the so-called "do it yourself" (DIY) approach to AID. Limited data on the open-source approach have shown promising results, but data from a large randomised control trial are lacking.

Methods

The CREATE (Community deRivEd AutomaTEd insulin delivery) trial is an open-labelled, randomised, parallel 24-week, multi-site trial comparing sensor augmented pump therapy (SAPT) to our AnyDANA-loop. The three components of AnyDANA-loop are: 1) OpenAPS algorithm implemented in a smartphone (a version of AndroidAPS), 2) DANA-i™ insulin pump and, 3) Dexcom G6^R continuous glucose monitor (CGM). The primary outcome measure is the percentage of time in target sensor glucose range (3.9 -10mmol/L). Secondary outcomes include psycho-social factors and platform performance. Analysis of online collective learning, characteristic of the open-source approach, is planned. 100 participants with T1D aged 7 - 70 years (age stratified into children/adolescents 7-15 years and adults 16-70 years), will be recruited from four sites in New Zealand. A 24-week continuation phase follows, to assess long-term safety.

New technical approach to the diabetes therapy

Optimal glycemic control remains challenging in individuals with type 1 diabetes. With the comprehensive clinical evidence on safety and efficiency, the adoption of continuous glucose monitoring (CGM), insulin pumps, and control algorithms merging the two into closed-loop systems is rapidly increasing. Particularly the CGM and intermittently scanned CGM improved diabetes management outcomes in large populations. A meaningful translation from clinical trials in highly controlled settings to numerous evaluations of closed-loop technology in the unrestricted home environment ended with its commercialization and use in routine clinical practice. Although it is still not a cure, the closed-loop currently seems to be the most promising advancement in the treatment of diabetes, with promising results also reported from routine clinical practice in children and adults with type 1 diabetes. We summarize different aspects of a technological approach to diabetes care, list currently available devices and systems in the pipeline, and the key supporting clinical evidence for their use. We consider human factors associated with technology use and the importance of health economics to support implementation and reimbursement.

Measuring glucose at the site of insulin delivery with a redox-mediated sensor

Automated insulin delivery systems for people with type 1 diabetes rely on an accurate subcutaneous glucose sensor and an infusion cannula that delivers insulin in response to measured glucose. Integrating the sensor with the infusion cannula would provide substantial benefit by reducing the number of devices inserted into subcutaneous tissue. We describe the sensor chemistry and a calibration algorithm to minimize impact of insulin delivery artifacts in a new glucose sensing cannula. Seven people with type 1 diabetes undergoing automated insulin delivery used two sensing cannulae whereby one delivered a rapidly-acting insulin analog and the other delivered a control phosphate buffered saline (PBS) solution with no insulin. While there was a small artifact in both conditions that increased for larger volumes, there was no difference between the artifacts in the sensing cannula delivering insulin compared with the sensing cannula delivering PBS as determined by integrating the area-under-the-curve of the sensor values following delivery of larger amounts of fluid (P = 0.7). The time for the sensor to recover from the artifact was found to be longer for larger fluid amounts compared with smaller fluid amounts (10.3 ± 8.5 min vs. 41.2 ± 78.3 s, P < 0.05). Using a smart-sampling Kalman filtering smoothing algorithm improved sensor accuracy. When using an all-point calibration on all sensors, the smart-sampling Kalman filter reduced the mean absolute relative difference from 10.9% to 9.5% and resulted in 96.7% of the data points falling within the A and B regions of the Clarke error grid. Despite a small artifact, which is likely due to dilution by fluid delivery, it is possible to continuously measure glucose in a cannula that simultaneously delivers insulin.

Advances in artificial pancreas systems

The artificial pancreas for managing type 1 diabetes has progressed from research into clinical practice, revealing areas for future advancements.

Artificial Intelligence and Digital Tools: Future of Diabetes Care

Diabetes mellitus has become a global threat, especially in the emerging economies. In the United States, there are about 24 million people with diabetes mellitus. Diabetes represents a trove of physiologic and sociologic data that are only superficially understood by the health care system. Artificial intelligence can address many problems posed by the prevalence of diabetes mellitus and the impact of diabetes on individual and societal health. We provide a brief overview of artificial intelligence and discuss case studies that illustrate how artificial intelligence can enhance diabetes care.

The Evolving Treatment of Diabetic Retinopathy

Purpose

To review the current therapeutic options for the management of diabetic retinopathy (DR) and diabetic macular edema (DME) and examine the evidence for integration of laser and pharmacotherapy.

Methods

A review of the PubMed database was performed using the search terms diabetic retinopathy, diabetic macular edema, neovascularization, laser photocoagulation, intravitreal injection, vascular endothelial growth factor (VEGF), vitrectomy, pars plana vitreous surgery, antiangiogenic therapy. With additional cross-referencing, this yielded 835 publications of which 301 were selected based on content and relevance.

Results

Many recent studies have evaluated the pharmacological, laser and surgical therapeutic strategies for the treatment and prevention of DR and DME. Several newer diagnostic systems such as optical coherence tomography (OCT), microperimetry, and multifocal electroretinography (mfERG) are also assisting in further refinements in the staging and classification of DR and DME. Pharmacological therapies for both DR and DME include both systemic and ocular agents. Systemic agents that promote intensive glycemic control, control of dyslipidemia and antagonists of the renin-angiotensin system demonstrate beneficial effects for both DR and DME. Ocular therapies include anti-VEGF agents, corticosteroids and nonsteroidal anti-inflammatory drugs. Laser therapy, both as panretinal and focal or grid applications continue to be employed in management of DR and DME. Refinements in laser devices have yielded more tissue-sparing (subthreshold) modes in which many of the benefits of conventional continuous wave (CW) lasers can be obtained without the adverse side effects. Recent attempts to lessen the burden of anti-VEGF injections by integrating laser therapy have met with mixed results. Increasingly, vitreoretinal surgical techniques are employed for less advanced stages of DR and DME. The development and use of smaller gauge instrumentation and advanced anesthesia agents have been associated with a trend toward earlier surgical intervention for diabetic retinopathy. Several novel drug delivery strategies are currently being examined with the goal of decreasing the therapeutic burden of monthly intravitreal injections. These fall into one of the five categories: non-biodegradable polymeric drug delivery systems, biodegradable polymeric drug delivery systems, nanoparticle-based drug delivery systems, ocular injection devices and with sustained release refillable devices. At present, there remains no one single strategy for the management of the particular stages of DR and DME as there are many options that have not been rigorously tested through large, randomized, controlled clinical trials.

Conclusion

Pharmacotherapy, both ocular and systemic, will be the primary mode of intervention in the management of DR and DME in many cases when cost and treatment burden are less constrained. Conventional laser therapy has become a secondary intervention in these instances, but remains a first-line option when cost and treatment burden are more constrained. Results with subthreshold laser appear promising but will require more rigorous study to establish its role as adjunctive therapy. Evidence to support an optimal integration of the various treatment options is lacking. Central to the widespread adoption of any therapeutic regimen for DR and DME is substantiation of safety, efficacy, and cost-effectiveness by a body of sound clinical trials.

Role of Glucagon in Automated Insulin Delivery

Treatment of type 1 diabetes with exogenous insulin often results in unpredictable daily glucose variability and hypoglycemia, which can be dangerous. Automated insulin delivery systems can improve glucose control while reducing burden for people with diabetes. One approach to improve treatment outcomes is to incorporate the counter-regulatory hormone glucagon into the automated delivery system to help prevent the hypoglycemia that can be induced by the slow pharmacodynamics of insulin action. This article explores the advantages and disadvantages of incorporating glucagon into dual-hormone automated hormone delivery systems.

Efficacy of the Diabeloop closed-loop system to improve glycaemic control in patients with type 1 diabetes exposed to gastronomic dinners or to sustained physical exercise

AIMS

To compare closed-loop (CL) and open-loop (OL) systems for glycaemic control in patients with type 1 diabetes (T1D) exposed to real-life challenging situations (gastronomic dinners or sustained physical exercise).

METHODS

Thirty-eight adult patients with T1D were included in a three-armed randomized pilot trial (Diabeloop WP6.2 trial) comparing glucose control using a CL system with use of an OL device during two crossover 72-hour periods in one of the three following situations: large (gastronomic) dinners; sustained and repeated bouts of physical exercise (with uncontrolled food intake); or control (rest conditions). Outcomes included time in spent in the glucose ranges of 4.4-7.8 mmol/L and 3.9-10.0 mmol/L, and time in hypo- and hyperglycaemia.

RESULTS

Time spent overnight in the tight range of 4.4 to 7.8 mmol/L was longer with CL (mean values: 63.2% vs 40.9% with OL; P ≤ .0001). Time spent during the day in the range of 3.9 to 10.0 mmol/L was also longer with CL (79.4% vs 64.1% with OL; P ≤ .0001). Participants using the CL system spent less time during the day with hyperglycaemic excursions (glucose >10.0 mmol/L) compared to those using an OL system (17.9% vs 31.9%; P ≤ .0001), and the proportions of time spent during the day with hyperglycaemic excursions of those using the CL system in the gastronomic dinner and physical exercise subgroups were of similar magnitude to those in the control subgroup (18.1 ± 6.3%, 17.2 ± 8.1% and 18.4 ± 12.5%, respectively). Finally, times spent in hypoglycaemia were short and not significantly different among the groups.

CONCLUSIONS

The Diabeloop CL system is superior to OL devices in reducing hyperglycaemic excursions in patients with T1D exposed to gastronomic dinners, or exposed to physical exercise followed by uncontrolled food and carbohydrate intake.

Randomized Controlled Trial of Mobile Closed-Loop Control

OBJECTIVE

Assess the efficacy of inControl AP, a mobile closed-loop control (CLC) system.

RESEARCH DESIGN AND METHODS

This protocol, NCT02985866, is a 3-month parallel-group, multicenter, randomized unblinded trial designed to compare mobile CLC with sensor-augmented pump (SAP) therapy. Eligibility criteria were type 1 diabetes for at least 1 year, use of insulin pumps for at least 6 months, age ≥14 years, and baseline HbA1c <10.5% (91 mmol/mol). The study was designed to assess two coprimary outcomes: superiority of CLC over SAP in continuous glucose monitor (CGM)-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L.

RESULTS

Between November 2017 and May 2018, 127 participants were randomly assigned 1:1 to CLC (n = 65) versus SAP (n = 62); 125 participants completed the study. CGM time below 3.9 mmol/L was 5.0% at baseline and 2.4% during follow-up in the CLC group vs. 4.7% and 4.0%, respectively, in the SAP group (mean difference -1.7% [95% CI -2.4, -1.0]; P < 0.0001 for superiority). CGM time above 10 mmol/L was 40% at baseline and 34% during follow-up in the CLC group vs. 43% and 39%, respectively, in the SAP group (mean difference -3.0% [95% CI -6.1, 0.1]; P < 0.0001 for noninferiority). One severe hypoglycemic event occurred in the CLC group, which was unrelated to the study device.

CONCLUSIONS

In meeting its coprimary end points, superiority of CLC over SAP in CGM-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L, the study has demonstrated that mobile CLC is feasible and could offer certain usability advantages over embedded systems, provided the connectivity between system components is stable.

Automated Insulin Delivery in Adults

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

Real world hybrid closed-loop discontinuation: Predictors and perceptions of youth discontinuing the 670G system in the first 6 months

OBJECTIVE

To describe predictors of hybrid closed loop (HCL) discontinuation and perceived barriers to use in youth with type 1 diabetes.

SUBJECTS

Youth with type 1 diabetes (eligible age 2-25 y; recruited age 8-25 y) who initiated the Minimed 670G HCL system were followed prospectively for 6 mo in an observational study.

RESEARCH DESIGN AND METHODS

Demographic, glycemic (time-in-range, HbA1c), and psychosocial variables [Hypoglycemia Fear Survey (HFS); Problem Areas in Diabetes (PAID)] were collected for all participants. Participants who discontinued HCL (<10% HCL use at clinical visit) completed a questionnaire on perceived barriers to HCL use.

RESULTS

Ninety-two youth (15.7 ± 3.6 y, HbA1c 8.8 ± 1.3%, 50% female) initiated HCL, and 28 (30%) discontinued HCL, with the majority (64%) discontinuing between 3 and 6 mo after HCL start. Baseline HbA1c predicted discontinuation (P = .026) with the odds of discontinuing 2.7 times higher (95% CI: 1.123, 6.283) for each 1% increase in baseline HbA1c. Youth who discontinued HCL rated difficulty with calibrations, number of alarms, and too much time needed to make the system work as the most problematic aspects of HCL. Qualitatively derived themes included technological difficulties (error alerts, not working correctly), too much work (calibrations, fingersticks), alarms, disappointment in glycemic control, and expense (cited by parents).

CONCLUSIONS

Youth with higher HbA1c are at greater risk for discontinuing HCL than youth with lower HbA1c, and should be the target of new interventions to support device use. The primary reasons for discontinuing HCL relate to the workload required to use HCL.

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

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

Evolution of Diabetes Technology

Technological innovations have fundamentally changed diabetes care. Insulin pump use and continuous glucose monitoring are associated with improved glycemic control along with a better quality of life; automated insulin-dosing advisors facilitate and improve decision making. Glucose-responsive automated insulin delivery enables the highest targets for time in range, lowest rate and duration of hypoglycemia, and favorable quality of life. Clear targets for time in ranges and a standard visualization of the data will help the diabetes technology to be used more efficiently. Decision support systems within and integrated cloud environment will further simplify, unify, and improve modern routine diabetes care.

Basics and use of continuous glucose monitoring (CGM) in diabetes therapy

Background

For a long time, self-monitoring of blood glucose (SMBG) was widely viewed as the essential glucose measurement procedure in the therapy of insulin-treated people with diabetes. With increasing accuracy and simplified handling of continuous glucose monitoring (CGM) systems, this evolving technology challenges and at least partly replaces SMBG systems.

Content

Sensors of all currently available CGM systems measure glucose levels in the subcutaneous interstitial fluid for 6–14 days. The only available implantable sensor facilitates a measurement span of up to 6 months. Depending on the used system, glucose levels are either shown in real time (rtCGM systems) or after scanning (iscCGM systems). Functions such as alerts, alarms and trend arrows and data presentation encourage independent self-management of diabetes therapy. The high frequency of glucose data and the multitude of existing functions require an extensive training of people with diabetes and their caregivers.

Summary

CGM systems provide a much more detailed picture of glycemia in people with diabetes. Educated patients can use these data to react adequately to their glucose levels and therefore avoid hypoglycemic and hyperglycemic events. Studies showed that glycated hemoglobin (HbA1c) levels and hypoglycemic events can be significantly reduced by frequent use of CGM systems.

Evening and overnight closed-loop control versus 24/7 continuous closed-loop control for type 1 diabetes: a randomised crossover trial

Background

Automated closed-loop control (CLC), known as the "artificial pancreas" is emerging as a treatment option for Type 1 Diabetes (T1D), generally superior to sensor-augmented insulin pump (SAP) treatment. It is postulated that evening-night (E-N) CLC may account for most of the benefits of 24-7 CLC; however, a direct comparison has not been done.

Methods

In this trial (NCT02679287), adults with T1D were randomised 1:1 to two groups, which followed different sequences of four 8-week sessions, resulting in two crossover designs comparing SAP vs E-N CLC and E-N CLC vs 24-7 CLC, respectively. Eligibility: T1D for at least 1 year, using an insulin pump for at least six months, ages 18 years or older. Primary hypothesis: E-N CLC compared to SAP will decrease percent time <70mg/dL (3.9mmol/L) measured by continuous glucose monitoring (CGM) without deterioration in HbA1c. Secondary Hypotheses: 24-7 CLC compared to SAP will increase CGM-measured time in target range (TIR, 70-180mg/dL; 3.9-10mmol/L) and will reduce glucose variability during the day.

Findings

Ninety-three participants were randomised and 80 were included in the analysis, ages 18-69 years; HbA1c levels 5.4-10.6%; 66% female. Compared to SAP, E-N CLC reduced overall time <70mg/dL from 4.0% to 2.2% () resulting in an absolute difference of 1.8% (95%CI: 1.2-2.4%), p<0.0001. This was accompanied by overall reduction in HbA1c from 7.4% at baseline to 7.1% at the end of study, resulting in an absolute difference of 0.3% (95% CI: 0.1-0.4%), p<0.0001. There were 5 severe hypoglycaemia adverse events attributed to user-directed boluses without malfunction of the investigational device, and no diabetic ketoacidosis events.

Interpretation

In type 1 diabetes, evening-night closed-loop control was superior to sensor-augmented pump therapy, achieving most of the glycaemic benefits of 24-7 closed-loop.

Glucose Sensor Accuracy After Subcutaneous Glucagon Injections Near to Sensor Site

Background: Integrated hormone delivery and glucose sensing is warranted, but system performance could be challenged by glucose sensor susceptibility to pharmacological interferences. The aim of this study was to compare sensor accuracy (Medtronic Enlite 2^®) after subcutaneous (s.c.) administration of low-dose glucagon near to versus remote from sensor site. Methods: Twelve adults with insulin-pump-treated type 1 diabetes wore two continuous glucose monitors (CGM_glucagon and CGM_control) placed on each side of the abdomen before, during, and after two overnight 14-h in-clinic visits. During each visit, a s.c. 100 μg glucagon injection was administered 2 cm next to the CGM_glucagon followed by another injection of 100 μg glucagon 2 h later at the same site. CGM performance was evaluated using 4-h in-clinic Yellow Spring Instrument (YSI) measurements and 3-day self-monitoring of blood glucose (SMBG) in free-living conditions. Results: Using YSI as comparator, no difference in the median absolute relative difference (MARD) for CGM_glucagon (15.7%) and CGM_control (13.4%) was found (P = 0.195). Similarly, no difference in MARD was found between CGM_glucagon (11.0%) and CGM_control (6.2%) using SMBG as comparator (P = 0.148). Values in zone A + B of Clarke error grid analysis did not differ between CGM_glucagon and CGM_control using YSI (93.9% vs. 91.1%, P = 0.250) and SMBG (97.3% vs. 95.0%, P = 0.375) as reference measurement. The precision absolute relative deviation between sensors was 13.7%. Conclusions: Sensor accuracy was not significantly affected by administration of s.c. glucagon near to sensor site.

In Silico Trials of an Open-Source Android-Based Artificial Pancreas: A New Paradigm to Test Safety and Efficacy of Do-It-Yourself Systems

Objective: Safety data on Do-It-Yourself Artificial Pancreas Systems are missing. The most widespread in Europe is the AndroidAPS implementation of the OpenAPS algorithm. We used the UVA/Padova Type 1 Diabetes Simulator to in silico test safety and efficacy of this algorithm in different scenarios. Methods: We tested five configurations of the AndroidAPS algorithm differing in aggressiveness and patient's interaction with the system. All configurations were tested with insulin sensitivity variation of ±30%. The most promising configurations were tested in real-life scenarios: over- and underestimated bolus by 50%, bolus delivered 15 min before meal, and late bolus delivered 15 min after meal. Continuous Glucose Monitoring (CGM) time in ranges (TIRs) metrics were used to assess the glycemic control. Results: In silico testing showed that open-source closed-loop system AndroidAPS works effectively and safely. The best results were reached if AndroidAPS algorithm worked with microboluses and when half of calculated bolus was issued (mean glycemia 131 mg/dL, SD 27 mg/dL, TIR 91%, time between 54 and 70 mg/dL <1%, and low blood glucose index even <1). The meal bolus over- and underestimation as well as late bolus did not affect the TIR and, importantly, the time between 54 and 70 mg/dL. Conclusion: In silico testing proved that AndroidAPS implementation of the OpenAPS algorithm is safe and effective, and it showed a great potential to be tested in prospective home setting study.

Therapeutic Inertia in Pediatric Diabetes: Challenges to and Strategies for Overcoming Acceptance of the Status Quo

Despite significant advances in therapies for pediatric type 1 diabetes, achievement of glycemic targets remains elusive, and management remains burdensome for patients and their families. This article identifies common challenges in diabetes management at the patient-provider and health care system levels and proposes practical approaches to overcoming therapeutic inertia to enhance health outcomes for youth with type 1 diabetes.

[What is the current state of the artificial pancreas in diabetes care?]

The artificial pancreas (also referred to as closed-loop system) brings us one step closer to the decade-long dream of automated insulin delivery. The closed-loop system directs subcutaneous insulin delivery corresponding to the glucose concentration using a control algorithm. Evidence shows that closed-loop systems substantially improve glucose control and quality of life; however, fully automated closed-loop systems have not yet been accomplished. Active input from patients is required for mealtime insulin dosing and corrections. This article provides an overview on the current state of development of the artificial pancreas in the treatment of diabetes.

The Athlete with Type 1 Diabetes: Transition from Case Reports to General Therapy Recommendations

Fear of hypoglycemia is a common barrier to exercise and physical activity for individuals with type 1 diabetes. While some of the earliest studies in this area involved only one or two participants, the link between exercise, exogenous insulin, and hypoglycemia was already clear, with the only suggested management strategies being to decrease insulin dosage and/or consume carbohydrates before and after exercise. Over the past 50 years, a great deal of knowledge has been developed around the impact of different types and intensities of exercise on blood glucose levels in this population. Recent decades have also seen the development of technologies such as continuous glucose monitors, faster-acting insulins and commercially available insulin pumps to allow for the real-time observation of interstitial glucose levels, and more precise adjustments to insulin dosage before, during and after activity. As such, there are now evidence-based exercise and physical activity guidelines for individuals with type 1 diabetes. While the risk of hypoglycemia has not been completely eliminated, therapy recommendations have evolved considerably. This review discusses the evolution of the knowledge and the technology related to type 1 diabetes and exercise that have allowed this evolution to take place.

Realizing a Closed-Loop (Artificial Pancreas) System for the Treatment of Type 1 Diabetes

Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an "artificial pancreas" that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system.

Glycaemic variability: The under-recognized therapeutic target in type 1 diabetes care

Type 1 diabetes mellitus (T1DM) remains one of the most challenging long-term conditions to manage. Despite robust evidence to demonstrate that near normoglycaemia minimizes, but does not completely eliminate, the risk of complications, its achievement has proved almost impossible in a real-world setting. HbA1c to date has been used as the gold standard marker of glucose control and has been shown to reflect directly the risk of diabetes complications. However, it has been recognized that HbA1c is a crude marker of glucose control. Continuous glucose monitoring (CGM) provides the ability to measure and observe inter- and intraday glycaemic variability (GV), a more meaningful measure of glycaemic control, more relevant to daily living for those with T1DM. This paper reviews the relationship between GV and hypoglycaemia, and micro- and macrovascular complications. It also explores the impact on GV of CGM, insulin pumps, closed-loop technologies, and newer insulins and adjunctive therapies. Looking to the future, there is an argument that GV should become a key determinant of therapeutic success. Further studies are required to investigate the pathological and psychological benefits of reducing GV.

Patient Perception and Satisfaction With Insulin Pump System: Pilot User Experience Survey

BACKGROUND

The goal of this study was to assess patient perspectives and satisfaction with the MiniMed 670G insulin pump. Those participants who used the pump as part of a hybrid closed loop were also asked to provide their views on the automatic feature (auto mode).

METHODS

Adults with type 1 diabetes mellitus using the Medtronic™ 670G pump were asked about their experience with the device using a semi-structured survey developed by the research team. Responses were quantified to identify emergent themes.

RESULTS

Seventeen participants used the pump as part of a hybrid closed loop system, while four participants used the pump in combination with a nonintegrated continuous glucose monitoring system. Overall, participants indicated a high level of satisfaction with the pump (14/21) mostly because of improvements in blood glucose (BG) control (15/21). Least liked features were physical design and structure (6/21), frequency of user input (5/21), alert frequency (4/21), and difficulty of use (3/21). Those using the hybrid closed loop were satisfied with the auto mode feature (11/17), mostly because of improvements in BG control (9/17). The least liked features of the auto mode technology were that blood glucose levels remained elevated (5/17) and the frequency of alerts (4/17).

CONCLUSION

Participants indicated a high level of satisfaction with the pump and its auto mode featured mostly because of improvements in BG control. They also pointed out some key aspects of the device that are of potential clinical or commercial relevance. Additional research is needed to further evaluate users' perspectives on this new device.

Artificial Pancreas Systems and Physical Activity in Patients with Type 1 Diabetes: Challenges, Adopted Approaches, and Future Perspectives

Physical activity is important for patients living with type 1 diabetes (T1D) but limited by the challenges associated with physical activity induced glucose variability. Optimizing glycemic control without increasing the risk of hypoglycemia is still a hurdle despite many advances in insulin formulations, delivery methods, and continuous glucose monitoring systems. In this respect, the artificial pancreas (AP) system is a promising therapeutic option for a safer practice of physical activity in the context of T1D. It is important that healthcare professionals as well as patients acquire the necessary knowledge about how the AP system works, its limits, and how glucose control is regulated during physical activity. This review aims to examine the current state of knowledge on exercise-related glucose variations especially hypoglycemic risk in T1D and to discuss their effects on the use and development of AP systems. Though effective and highly promising, these systems warrant further research for an optimized use around exercise.

Feasibility Studies of an Insulin-Only Bionic Pancreas in a Home-Use Setting

BACKGROUND

We tested the safety and performance of the "insulin-only" configuration of the bionic pancreas (BP) closed-loop blood-glucose control system in a home-use setting to assess glycemic outcomes using different static and dynamic glucose set-points.

METHOD

This is an open-label non-randomized study with three consecutive intervention periods. Participants had consecutive weeks of usual care followed by the insulin-only BP with (1) an individualized static set-point of 115 or 130 mg/dL and (2) a dynamic set-point that automatically varied within 110 to 130 mg/dL, depending on hypoglycemic risk. Human factors (HF) testing was conducted using validated surveys. The last five days of each study arm were used for data analysis.

RESULTS

Thirteen participants were enrolled with a mean age of 28 years, mean A1c of 7.2%, and mean daily insulin dose of 0.6 U/kg (0.4-1.0 U/kg). The usual care arm had an average glucose of 145 ± 20 mg/dL, which increased in the static set-point arm (159 ± 8 mg/dL, P = .004) but not in the dynamic set-point arm (154 ± 10 mg/dL, P = ns). There was no significant difference in time spent in range (70-180 mg/dL) among the three study arms. There was less time <70 mg/dL with both the static (1.8% ± 1.4%, P = .009) and dynamic set-point (2.7±1.5, P = .051) arms compared to the usual-care arm (5.5% ± 4.2%). HF testing demonstrated preliminary user satisfaction and no increased risk of diabetes burden or distress.

CONCLUSIONS

The insulin-only configuration of the BP using either static or dynamic set-points and initialized only with body weight performed similarly to other published insulin-only systems.