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

Cost-effectiveness of a novel hybrid closed-loop system compared with continuous subcutaneous insulin infusion in people with type 1 diabetes in the UK

AIMS

The MiniMed 670 G insulin pump system is the first commercially available hybrid closed-loop (HCL) insulin delivery system and clinical studies have shown that this device is associated with incremental benefits in glycemic control relative to continuous subcutaneous insulin infusion (CSII) with or without continuous glucose monitoring (CGM). The aim was to evaluate the long-term cost-effectiveness of the MiniMed 670 G system versus CSII alone in people with type 1 diabetes (T1D) in the UK.

MATERIALS AND METHODS

Cost-effectiveness analysis was performed using the IQVIA CORE Diabetes Model. Clinical input data were sourced from a clinical trial of the MiniMed 670 G system in 124 adults and adolescents with T1D. The analysis was performed over a lifetime time horizon and both future costs and clinical outcomes were discounted at 3.5% per annum. The analysis was performed from a healthcare payer perspective.

RESULTS

The use of the MiniMed 670 G system led to an improvement in quality-adjusted life expectancy of 1.73 quality-adjusted life years (QALYs), relative to CSII. Total lifetime direct costs were GBP 35,425 higher with the MiniMed 670 G system than with CSII resulting in an incremental cost-effectiveness ratio (ICER) of GBP 20,421 per QALY gained. Sensitivity analyses revealed that the ICER was sensitive to assumptions around glycemic control and assumptions relating to the quality-of-life benefit associated with a reduction in fear of hypoglycemia.

LIMITATIONS

Long-term projections from short-term data are inherently associated with uncertainty but represent arguably the best available evidence in lieu of long-term clinical trials.

CONCLUSIONS

In the UK, over patient lifetimes, the incremental clinical benefits associated with the use of MiniMed 670 G system means that it is likely to be cost-effective relative to the continued use of CSII in people with T1D, particularly for those with a fear of hypoglycemia or poor baseline glycemic control.

Review of the Long-Term Implantable Senseonics Continuous Glucose Monitoring System and Other Continuous Glucose Monitoring Systems

The article published by Kevin Cowart in this issue of the Journal of Diabetes Science and Technology (JDST) is a detailed overview of the clinical trial data and analysis used to demonstrate the safety and effectiveness of the Eversense continuous glucose monitoring (CGM) System for regulatory approval and clinical acceptance. The article describes the published study results for safety, accuracy, reliability, ease of insertion/removal, adverse events, and ease of diabetes patient-use for controlling their glucose levels short and long term. The author nicely compares Eversense CGM System safety and performance with the short-term subcutaneous tissue CGM systems being commercialized by Dexcom, Medtronic Diabetes, and Abbott Diabetes. This comparison may help the clinician define which type of patient with diabetes might benefit the most from the long-term implantable CGM system. The majority of studied patients describe a positive experience managing their diabetes with the Eversense CGM System and request implantation of a new sensor 90 or 180 days later.

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

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

A Pilot Study of Youth With Type 1 Diabetes Initiating Use of a Hybrid Closed-Loop System While Receiving a Behavioral Economics Intervention

OBJECTIVE

Many youth do not use the hybrid closed-loop system for type 1 diabetes effectively. This study evaluated the impact of financial incentives for diabetes-related tasks on use of the 670G hybrid closed-loop system and on glycemia.

METHODS

At auto mode initiation and for 16 weeks thereafter, participants received a flat rate for wearing and calibrating the sensor ($1/day), administering at least 3 mealtime insulin boluses per day ($1/day), and uploading ($5/week). Weekly bonuses were given for maintaining at least 70% of the time in auto mode, which were increased for persistent auto mode use from $3/week to a maximum of $13/week. If a participant failed to maintain auto mode for a week, the rewards were reset to baseline. Data from 17 participants aged 15.9 years ± 2.5 years (baseline hemoglobin A1c [HbA1c] 8.6% ± 1.1%) were collected at 6, 12, and 16 weeks. The reinforcers were withdrawn at 16 weeks, with a follow-up assessment at 24 weeks.

RESULTS

With reinforcers, the participants administered an average of at least 3 mealtime insulin boluses per day and wore the sensor over 70% of the time. However, auto mode use waned. HbA1c levels decreased by 0.5% after 6 weeks, and this improvement was maintained at 12 and 16 weeks (P < .05). Upon withdrawal of reinforcers, HbA1c levels increased back to baseline at 24 weeks.

CONCLUSION

Compensation for diabetes-related tasks was associated with lower HbA1c levels, consistent administration of mealtime insulin boluses, and sustained sensor use. These results support the potential of financial rewards for improving outcomes in youth with type 1 diabetes.

Are Physicians in Saudi Arabia Ready for Patients with an Insulin Pump? An Examination of Physician Knowledge and Attitude

Aims: The use of insulin pump therapy in patients with diabetes continues to expand worldwide. Although insulin pumps have been demonstrated to be successful and safe, physicians’ insufficient knowledge may carry a risk to the patients using insulin pumps. This study aimed to assess the attitude and knowledge among physicians in Saudi Arabia regarding insulin pump therapy. Methods: Three hundred and seven physicians, including 82 family physicians, 76 pediatricians, 48 internists, 27 pediatric endocrinologists, 17 adult endocrinologists, and 57 physicians from other specialties, completed a questionnaire that evaluated their knowledge and attitude toward insulin pump therapy. Results: Among the evaluated physicians, 56.7% had poor knowledge level, while 53.4% had positive attitude. Statistical tests revealed that older age, years of practice, consultancy, and endocrinology specialty were the influential factors of knowledge (p < 0.001). Non-endocrinologists demonstrated poor knowledge despite seeing patients with insulin pumps; however, those who had previously cared for such patients scored significantly higher knowledge scores. Conclusions: There was a significant lack of knowledge among physicians regarding insulin pump therapy; however, the perceived attitude of physicians toward this therapy was deemed positive. These findings support the implementation of insulin pump education programs.

Hypoglycemia in cystic fibrosis: Prevalence, impact and treatment

Hypoglycemia is a common and feared complication of insulin therapy. As in type 1 and type 2 diabetes, people with cystic fibrosis related diabetes are also at risk for hypoglycemia related to insulin therapy. Spontaneous hypoglycemia is also common in patients with CF without diabetes, who are not on glucose lowering medications. Spontaneous hypoglycemia in CF may also occur during or after an oral glucose tolerance test. In this review, we will discuss the definition, epidemiology, pathophysiology and impact of hypoglycemia, with a focus on people with cystic fibrosis. We will also review strategies to manage and prevent hypoglycemia.

Weight Management in Youth with Type 1 Diabetes and Obesity: Challenges and Possible Solutions

PURPOSE OF REVIEW

This review highlights challenges associated with weight management in children and adolescents with type 1 diabetes (T1D). Our purpose is to propose potential solutions to improve weight outcomes in youth with T1D.

RECENT FINDINGS

A common barrier to weight management in T1D is reluctance to engage in exercise for fear of hypoglycemia. Healthcare practitioners generally provide limited guidance for insulin dosing and carbohydrate modifications to maintain stable glycemia during exercise. Adherence to dietary guidelines is associated with improved glycemia; however, youth struggle to meet recommendations. When psychosocial factors are addressed in combination with glucose trends, this often leads to successful T1D management. Newer medications also hold promise to potentially aid in glycemia and weight management, but further research is necessary. Properly addressing physical activity, nutrition, pharmacotherapy, and psychosocial factors while emphasizing weight management may reduce the likelihood of obesity development and its perpetuation in this population.

Lower Daily Carbohydrate Intake Is Associated With Improved Glycemic Control in Adults With Type 1 Diabetes Using a Hybrid Closed-Loop System

OBJECTIVE

To assess the association between daily carbohydrate (CHO) intake and glycemic control in adult hybrid closed-loop (HCL) users with type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

Mean individual daily CHO intake (MIDC) and relative deviation from MIDC (≤80% low, 81-120% medium, >120% high CHO consumption) were compared with parameters of glycemic control assessed by continuous glucose monitoring.

RESULTS

Records from 36 patients (26 male, 10 female; age 36.9 ± 13.5 years; HbA_1c 7.1 ± 0.9% [54 ± 10 mmol/mol]) provided 810 days of data (22.5 ± 6.7 days per patient). Time in range (70-180 mg/dL) for low, medium, and high CHO consumption was 77.4 ± 15.4%, 75.2 ± 16.7%, and 70.4 ± 17.8%, respectively (P < 0.001). Time above range (>180 mg/dL) was 20.1 ± 14.7%, 22.0 ± 16.9%, and 27.2 ± 18.4%, respectively (P < 0.001). There was no between-group difference for time in hypoglycemia (<70 mg/dL; P = 0.50).

CONCLUSIONS

Daily CHO intake was inversely associated with glycemic control in adults with T1D using an HCL system. Lower CHO intake may be a strategy to optimize glucose control in HCL users.

Baseline Glucose Variability and Interweek Variability Affects the Time to Stability of Continuous Glucose Monitoring-Derived Glycemic Indices

Objectives: To study the effect of baseline glucose variability (GV) on the time to stability and interweek variability (IWV) of continuous glucose monitoring (CGM)-derived glycemic indices. Materials and Methods: Anonymized CGM data (median duration 32 weeks, ≥70% data coverage) of 85 adults with type 1 diabetes; age (41 ± 12 years), 66.3% women, HbA1c (7.5% ± 1.2%, 58 mmol/mol) were analyzed. We evaluated the time to stability, that is, the minimum duration of data that provided a close (r² ≥ 0.9) correlation with data taken across the whole sampling period and IWV. We also evaluated the impact of baseline variability on the time to stability. Results: For the whole data set, all indices achieved stability (r² ≥ 0.9) by 9 weeks (range 5-9). Time to stability progressively increased from the lowest quartile to the highest quartile of baseline coefficient of variation (CV). Time above range (TAR) and time below range (TBR) had higher IWV than time in range (TIR) (%CV_IWV: TIR-16%, TAR-31%, TBR-62%). Conclusion: Baseline GV and IWV of indices affect the time to stability of glycemic indices. We recommend a minimum of 9 weeks of data to represent long-term CGM data.

Multi-Hour Blood Glucose Prediction in Type 1 Diabetes: A Patient-Specific Approach Using Shallow Neural Network Models

Background: Considering current insulin action profiles and the nature of glycemic responses to insulin, there is an acute need for longer term, accurate, blood glucose predictions to inform insulin dosing schedules and enable effective decision support for the treatment of type 1 diabetes (T1D). However, current methods achieve acceptable accuracy only for prediction horizons of up to 1 h, whereas typical postprandial excursions and insulin action profiles last 4-6 h. In this study, we present models for prediction horizons of 60-240 min developed by leveraging "shallow" neural networks, allowing for significantly lower complexity compared with related approaches. Methods: Patient-specific neural network-based predictive models are developed and tested on previously collected data from a cohort of 24 subjects with T1D. Models are designed to avoid serious pitfalls through incorporating essential physiological knowledge into model structure. Patient-specific models were generated to predict glucose 60, 90, 120, 180, and 240 min ahead, and a "transfer learning" approach to improve accuracy for patients where data are limited. Finally, we determined subgroup characteristics that result in higher model accuracy overall. Results: Root mean squared error was 28 ± 4, 33 ± 4, 38 ± 6, 40 ± 8, and 43 ± 12 mg/dL for 60, 90, 120, 180, and 240 min, respectively. For all prediction horizons, at least 93% of predictions were clinically acceptable by the Clarke error grid. Variance of historic continuous glucose monitor (CGM) values was a strong predictor for the need of transfer learning approaches. Conclusions: A shallow neural network, using features extracted from past CGM data and insulin logs, can achieve multi-hour glucose predictions with satisfactory accuracy. Models are patient specific, learnt on readily available data without the need for additional tests, and improve accuracy while lowering complexity compared with related approaches, paving the way for new advisory and closed loop algorithms able to encompass most of the insulin action timeframe.

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.

Glycemic Status Assessment by the Latest Glucose Monitoring Technologies

The advanced and performing technologies of glucose monitoring systems provide a large amount of glucose data that needs to be properly read and interpreted by the diabetology team in order to make therapeutic decisions as close as possible to the patient's metabolic needs. For this purpose, new parameters have been developed, to allow a more integrated reading and interpretation of data by clinical professionals. The new challenge for the diabetes community consists of promoting an integrated and homogeneous reading, as well as interpretation of glucose monitoring data also by the patient himself. The purpose of this review is to offer an overview of the glycemic status assessment, opened by the current data management provided by latest glucose monitoring technologies. Furthermore, the applicability and personalization of the different glycemic monitoring devices used in specific insulin-treated diabetes mellitus patient populations will be evaluated.

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.

Cost-Effectiveness Analysis of a Hybrid Closed-Loop System Versus Multiple Daily Injections and Capillary Glucose Testing for Adults with Type 1 Diabetes

Background: Hybrid closed-loop systems may offer improved HbA1c levels, more time-in-range, and less hypoglycemia than alternative treatment strategies. However, it is unclear if glycemic improvements offset this technology's higher acquisition costs. Among adults with type 1 diabetes in Australia, we sought to evaluate the cost-effectiveness of a hybrid closed-loop system in comparison with the current standard of care, comprising insulin injections and capillary glucose testing. Methods: Cost-effectiveness analysis was performed using decision analysis in combination with a Markov model to simulate disease progression in a cohort of adults with type 1 diabetes and compare the downstream health and economic consequences of hybrid closed-loop therapy versus current standard of care. Transition probabilities and utilities were sourced from published studies. Costs were considered from the perspective of the Australian health care system. A lifetime horizon was considered, with annual discount rates of 5% applied to future costs and outcomes. Uncertainty was assessed with probabilistic and deterministic sensitivity analyses. Results: Use of a hybrid closed-loop system resulted in an incremental cost-effectiveness ratio of Australian dollars (AUD) 37,767 per quality-adjusted life year (QALY) gained. This is below the traditionally cited willingness to pay a threshold of $50,000 per QALY gained in the Australian setting. Sensitivity analyses that varied baseline glycemic control, treatment effects, technology costs, age, discount rates, and time horizon indicated the results to be robust. Conclusions: For adults with type 1 diabetes, hybrid closed-loop therapy is likely to be cost-effective compared with multiple daily injections and capillary glucose testing in Australia.

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.

Patient Input for Design of a Decision Support Smartphone Application for Type 1 Diabetes

BACKGROUND

Decision support smartphone applications integrated with continuous glucose monitors may improve glycemic control in type 1 diabetes (T1D). We conducted a survey to understand trends and needs of potential users to inform the design of decision support technology.

METHODS

A 70-question survey was distributed October 2017 through May 2018 to adults aged 18-80 with T1D from a specialty clinic and T1D Exchange online health community (myglu.org). The survey responses were used to evaluate potential features of a diabetes decision support tool by Likert scale and open responses.

RESULTS

There were 1542 responses (mean age 46.1 years [SD 15.2], mean duration of diabetes 26.5 years [SD 15.8]). The majority (84.2%) have never used an app to manage diabetes; however, a large majority (77.8%) expressed interest in using a decision support app. The ability to predict and avoid hypoglycemia was the most important feature identified by a majority of the respondents, with 91% of respondents indicating the highest level of interest in these features. The task that respondents find most difficult was management of glucose during exercise (only 47% of participants were confident in glucose management during exercise). The respondents also highly desired features that help manage glucose during exercise (85% of respondents were interested). The responses identified integration and interoperability with peripheral devices/apps and customization of alerts as important. Responses from participants were generally consistent across stratified categories.

CONCLUSIONS

These results provide valuable insight into patient needs in decision support applications for management of T1D.

Diabetes in ageing: pathways for developing the evidence base for clinical guidance

Older adults with diabetes are heterogeneous in their medical, functional, and cognitive status, and require careful individualisation of their treatment regimens. However, in the absence of detailed information from clinical trials involving older people with varying characteristics, there is little evidence-based guidance, which is a notable limitation of current approaches to care. It is important to recognise that older people with diabetes might vary in their profiles according to age category, functional health, presence of frailty, and comorbidity profiles. In addition, all older adults with diabetes require an individualised approach to care, ranging from robust individuals to those residing in care homes with a short life expectancy, those requiring palliative care, or those requiring end-of-life management. In this Review, our multidisciplinary team of experts describes the current evidence in several important areas in geriatric diabetes, and outlines key research gaps and research questions in each of these areas with the aim to develop evidence-based recommendations to improve the outcomes of interest in older adults.

Glycemic Monitoring and Management in Advanced Chronic Kidney Disease

Glucose and insulin metabolism in patients with diabetes are profoundly altered by advanced chronic kidney disease (CKD). Risk of hypoglycemia is increased by failure of kidney gluconeogenesis, impaired insulin clearance by the kidney, defective insulin degradation due to uremia, increased erythrocyte glucose uptake during hemodialysis, impaired counterregulatory hormone responses (cortisol, growth hormone), nutritional deprivation, and variability of exposure to oral antihyperglycemic agents and exogenous insulin. Patients with end-stage kidney disease frequently experience wide glycemic excursions, with common occurrences of both hypoglycemia and hyperglycemia. Assessment of glycemia by glycated hemoglobin (HbA1c) is hampered by a variety of CKD-associated conditions that can bias the measure either to the low or high range. Alternative glycemic biomarkers, such as glycated albumin or fructosamine, are not fully validated. Therefore, HbA1c remains the preferred glycemic biomarker despite its limitations. Based on observational data for associations with mortality and risks of hypoglycemia with intensive glycemic control regimens in advanced CKD, an HbA1c range of 7% to 8% appears to be the most favorable. Emerging data on the use of continuous glucose monitoring in this population suggest promise for more precise monitoring and treatment adjustments to permit fine-tuning of glycemic management in patients with diabetes and advanced CKD.

A clinical review of the t:slim X2 insulin pump

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

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.

Advances in the management of diabetes: new devices for type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune condition that affects a significant number of people worldwide, with higher prevalence in white European populations. The condition is responsible for a high burden of microvascular complications, especially when poorly controlled. The condition is also burdensome on the patient and has major psychosocial and occupational impacts. It requires lifelong frequent blood glucose monitoring and regular insulin injections. Important technological advances in the management of T1D have occurred in recent years. These include the advent of new glucose testing devices using interstitial glucose, and new insulin delivery devices. These technologies may improve quality of life, and glucose management in this condition. This review aims to outline the current advances in the management of T1D for the general physician, with a particular focus on new technologies.

Cost-effectiveness of health technologies in adults with type 1 diabetes: a systematic review and narrative synthesis

BACKGROUND

With the rapid development of technologies for type 1 diabetes, economic evaluations are integral in guiding cost-effective clinical and policy decisions. We therefore aimed to review and synthesise the current economic literature for available diabetes management technologies and outline key determinants of cost-effectiveness.

METHODS

A systematic search was conducted in April 2019 that focused on modelling or trial based economic evaluations. Searched databases included Medline, Medline in-process and other non-indexed citations, EMBASE, PubMed, All Evidenced Based Medicine Reviews, EconLit, Cost-effectiveness analysis Registry, Research Papers in Economics, Web of Science, PsycInfo, CINAHL, and PROSPERO from inception. We assessed quality of included studies with the Questionnaire to Assess Relevance and Credibility of Modeling Studies for Informing Health Care Decision Making an ISPOR-AMCP-NPC good practice task force report. Screening of abstracts and full-texts, appraisal, and extraction were performed by two independent researches.

RESULTS

We identified 16,772 publications, of which 35 were analysed and included 11 health technologies. Despite a lack of consensus, most studies reported that insulin pumps (56%) or interstitial glucose sensors (62%) were cost-effective, although incremental cost-effectiveness ratios ranged widely ($14,266-$2,997,832 USD). Cost-effectiveness for combined insulin pumps and glucose sensors was less clear. Determinants of cost-effectiveness included treatment effects on glycosylated haemoglobin and hypoglycaemia, costing of technologies and complications, and measures of utility.

CONCLUSIONS

Insulin pumps or glucose sensors appeared cost-effective, particularly in populations with higher HbA1c levels and rates of hypoglycaemia. However, cost-effectiveness for combined insulin pumps and glucose sensors was less clear.

REGISTRATION

The study was registered with PROSPERO, number CRD42017077221.

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.

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

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

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.

Where Do We Stand with Closed-Loop Systems and Their Challenges?

Treatments for type 1 diabetes have advanced significantly over recent years. There are now multiple hybrid closed-loop systems commercially available and additional systems are in development. Challenges remain, however. This review outlines the recent advances in closed-loop systems and outlines the remaining challenges, including post-prandial hyperglycemia and exercise-related dysglycemia.

Glucose outcomes of a learning-type artificial pancreas with an unannounced meal in type 1 diabetes

BACKGROUND AND OBJECTIVES

Glycemic control with unannounced meals is the major challenge for artificial pancreas. In this study, we described the performance and safety of learning-type model predictive control (L-MPC) for artificial pancreas challenged by an unannounced meal in type 1 diabetes (T1D).

METHODS

This closed-loop (CL) system was tested in 29 T1D patients at one site in a 4 h inpatient open-label study. Participants used an L-MPC CL system for 6 days after 2-day system identification using open-loop (OL) insulin system. During the CL period, the L-MPC system was started from 8:00 am to noon each day. At 9:00 am, each participant consumed 50 g of carbohydrates with no prandial insulin bolus. At 9:30 am on CL-Day 4 or CL-Day 6, participants rode bicycles for 20 minutes or drank 50 ml of beer, in a random order.

RESULTS

As the primary outcome, TIR on CL-Day 3 was 65.2±23.3%, which was 9.8 points higher (95% CI 1.8 to 17.8; P = 0.019) than that on CL-Day 1. The time of glucose >10 mmol/L was decreased by 11.0% (95% CI -18.7 to 3.3; P = 0.007), and mean glucose level was decreased by 1.1 mmol/L (95% CI -1.1 to 0.5; P = 0.000). The total daily insulin dosage showed no significant difference (-0.1U, 95% CI -1.34 to 1.32; P = 0.982). Compared with OL-Day1 with a postprandial bolus, the TIR was increased by 13.7 points (95% CI 1.4 to 26.0; P = 0.030), the time of glucose >10 mmol/L and the mean glucose level were also decreased. Compared with the exercise day (CL-Day E, 62.0 ± 23.3%; P = 0.347) or alcohol day (CL-Day A, 64.0 ± 23.6%; P = 0.756), there was no statistically significant difference in terms of TIR, time of glucose >10 mmol/L and mean glucose level. No severe hypoglycemic events occurred and hypoglycemic episodes were not increased by using closed-loop insulin system.

CONCLUSION

The L-MPC CL insulin system achieved good glycemic control challenged by an unannounced meal.

A Comparison of Different Models of Glycemia Dynamics for Improved Type 1 Diabetes Mellitus Management with Advanced Intelligent Analysis in an Internet of Things Context

The metabolic disease Type 1 Diabetes Mellitus (DM1) is caused by a reduction in the production of pancreatic insulin, which causes chronic hyperglycemia. Patients with DM1 are required to perform multiple blood glucose measurements on a daily basis to monitor their blood glucose dynamics through the use of capillary glucometers. In more recent times, technological developments have led to the development of cutting-edge biosensors and Continuous Glucose Monitoring (CGM) systems that can monitor patients’ blood glucose levels on a real-time basis. This offers medical providers access to glucose oscillations modeling interventions that can enhance DM1 treatment and management approaches through the use of novel disruptive technologies, such as Cloud Computing (CC), big data, Intelligent Data Analysis (IDA) and the Internet of Things (IoT). This work applies some advanced modeling techniques to a complete data set of glycemia-related biomedical features—obtained through an extensive, passive monitoring campaign undertaken with 25 DM1 patients under real-world conditions—in order to model glucose level dynamics through the proper identification of patterns. Hereby, four methods, which are run through CC due to the high volume of data collected, are applied and compared within an IoT context. The results show that Bayesian Regularized Neural Networks (BRNN) offer the best performance (0.83 R2) with a reduced Root Median Squared Error (RMSE) of 14.03 mg/dL.

Artificial Intelligence in Decision Support Systems for Type 1 Diabetes

Type 1 diabetes (T1D) is a chronic health condition resulting from pancreatic beta cell dysfunction and insulin depletion. While automated insulin delivery systems are now available, many people choose to manage insulin delivery manually through insulin pumps or through multiple daily injections. Frequent insulin titrations are needed to adequately manage glucose, however, provider adjustments are typically made every several months. Recent automated decision support systems incorporate artificial intelligence algorithms to deliver personalized recommendations regarding insulin doses and daily behaviors. This paper presents a comprehensive review of computational and artificial intelligence-based decision support systems to manage T1D. Articles were obtained from PubMed, IEEE Xplore, and ScienceDirect databases. No time period restrictions were imposed on the search. After removing off-topic articles and duplicates, 562 articles were left to review. Of those articles, we identified 61 articles for comprehensive review based on algorithm evaluation using real-world human data, in silico trials, or clinical studies. We grouped decision support systems into general categories of (1) those which recommend adjustments to insulin and (2) those which predict and help avoid hypoglycemia. We review the artificial intelligence methods used for each type of decision support system, and discuss the performance and potential applications of these systems.

Evolution of Insulin Delivery Devices: From Syringes, Pens, and Pumps to DIY Artificial Pancreas

The year 2021 will mark 100 years since the discovery of insulin. Insulin, the first medication to be discovered for diabetes, is still the safest and most potent glucose-lowering therapy. The major challenge of insulin despite its efficacy has been the occurrence of hypoglycemia, which has resulted in sub-optimal dosages being prescribed in the vast majority of patients. Popular devices used for insulin administration are syringes, pens, and pumps. An artificial pancreas (AP) with a closed-loop delivery system with > 95% time in range is believed to soon become a reality. The development of closed-loop delivery systems has gained momentum with recent advances in continuous glucose monitoring (CGM) and computer algorithms. This review discusses the evolution of syringes, disposable, durable pens and connected pens, needles, tethered and patch insulin pumps, bionic pancreas, alternate controller-enabled infusion (ACE) pumps, and do-it-yourself artificial pancreas systems (DIY-APS).

10-Day structured initiation protocol from multiple daily injection to hybrid closed-loop system in children and adolescents with type 1 diabetes

AIM

The aim of this study was to evaluate the 10-day initiation protocol for MiniMed 670G hybrid closed-loop (HCL) system in individuals with type 1 diabetes on multiple daily injection (MDI) in achieving desirable glycemic control.

METHODS

An open-label single-arm, single-center, clinical investigation in children aged 7-18 years on MDI following a structured protocol: 2 days, HCL system assessment; 5 days, HCL system training (2-h sessions on 5 consecutive days with groups of 3-5 participants and families); 3 days, Manual Mode use of HCL system; 84 days, Auto Mode use of the HCL system, cumulating in 10 days from MDI to Auto Mode activation.

RESULTS

A total of 30 children (age 10.24 ± 2.6 years) were enrolled in the study, and all completed the planned 84 days on Auto Mode. The participants used the sensor for a median of 92% of the time and spent a median of 89% in Auto Mode. The mean HbA1c decreased from 8.2 ± 1.4% (66 ± 15.3 mmol/mol) at baseline to 6.7 ± 0.5% (50 ± 5.5 mmol/mol) at the end of the study (p = 0.017). Time in range (70-180 mg/dL) increased from 46.9 ± 18.5% at baseline to 75.6 ± 6.9% in Auto Mode (p < 0.001). This was achieved while spending 2.8% of the time below 70 mg/dL and without any severe hypoglycemia or DKA.

CONCLUSION

Children and adolescents with type 1 diabetes on MDI therapy can successfully initiate the HCL system, using a concise structured 10-day protocol.

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.

The Effect of Acarbose on Glycemic Variability in Patients with Type 2 Diabetes Mellitus Using Premixed Insulin Compared to Metformin (AIM): An Open-Label Randomized Trial

Background: Acarbose (ACA) can effectively reduce the postprandial blood glucose and has similar antidiabetic effects as metformin (MET). To our knowledge, few studies have compared the effect of ACA or MET on glucose fluctuations. In the present study, we explored the effect of ACA or MET combined with premixed insulin (INS) on glycemic control and glycemic variability (GV). Methods: This was an open-label randomized trial that was conducted in type 2 diabetic patients taking premixed insulin. The patients were assigned to 12 weeks of MET (n = 62) or ACA (n = 62) treatment combined with INS. The main outcomes were changes in GV and glycosylated hemoglobin A1c (HbA1c) compared with baseline. Results: Compared with baseline, several GV indices (standard deviation [SD], mean amplitude of glycemic excursions [MAGE]) and blood glucose control indices (mean glucose [MG], time in range [TIR] and HbA1c) were both significantly improved in INS+ACA and INS+MET after 12-week therapy. However, coefficient of variation (CV) was significantly reduced in INS+ACA but not in INS+MET. Moreover, compared with INS+MET, INS+ACA led to a more pronounced percentage change from baseline in CV (26.3% [1.7%-44.6%] vs. 11.9% [-7.0% to 29.9%], P = 0.022), MAGE (40.5% [20.1%-60.5%] vs. 25.2% [-2.1% to 43.4%], P = 0.007) and SD (38.6% [25.2%-57.9%] vs. 30.1% [10.8%-46.5%], P = 0.041). Conclusion: Both MET and ACE combined with INS effectively reduced blood glucose. Compared with MET, ACA combined with INS reduced GV.

Increased proportion of time in hybrid closed-loop "Auto Mode" is associated with improved glycaemic control for adolescent and young patients with adult type 1 diabetes using the MiniMed 670G insulin pump

The Medtronic MiniMed 670G system delivers insulin to patients with type 1 diabetes mellitus (T1DM) using either its hybrid closed-loop (HCL) "Auto Mode" feature or an open-loop mode. In this retrospective, cross-sectional analysis, we quantified the association between time in Auto Mode and both haemoglobin A1c (HbA1c) and time in range (TIR, sensor glucose 70-180 mg/dL) among 96 paediatric and young adult patients with T1DM. The median percentage time in Auto Mode was 38.5% (interquartile range 0%-64%). The percentage time in Auto Mode significantly correlated with HbA1c after adjustment for covariables (β = -0.008, P = 0.014). Each daily 3.4-h increase in Auto Mode time was associated with a 0.1% decrease in HbA1c. Auto Mode time was also correlated with TIR after adjustment for covariables (β = 0.14, P = 0.02): for each daily 8.6-h increase in Auto Mode time, TIR increased by 5%. While Auto Mode use was low, increased time in Auto Mode was associated with a significantly lower HbA1c and increased TIR. These findings emphasize the importance of identifying strategies to improve the ease of use of HCL systems.

Long-term real-life glycaemic outcomes with a hybrid closed-loop system compared with sensor-augmented pump therapy in patients with type 1 diabetes

AIM

To compare glycaemic metrics at 3 and 6 months in patients with type 1 diabetes on a 670G hybrid closed-loop (HCL) system after using a sensor-augmented pump (SAP) for at least 3 months.

MATERIALS AND METHODS

A retrospective study from a centre that has the largest number of 670G users in the United States was conducted. Data from 202 SAP users were reviewed. Sixty-one patients were excluded (two for steroid use, four for pregnancy, 27 for previous Enlite use, and 28 for non-continuous use of 670G). Out of 141 patients who met the inclusion criteria, 127 (aged 21-68 years) had complete data.

RESULTS

HbA1c levels decreased by 0.4% at 3 months and were maintained at 6 months (7.6 ± 0.07 vs. 7.2 ± 0.08, P < 0.001) with no weight gain at 6 months. Time-in-range (70-180 mg/dL) increased from 59.5% ± 1.1% to 70.2% ± 1.2% and 70.1% ± 1.1% at 3 and 6 months (P < 0.001), respectively. At 6 months, time spent in hypoglycaemia (<70 mg/dL) and time spent in hyperglycaemia (>180 mg/dL) were reduced by 30% (2.2% ± 0.2% vs. 3.2% ± 0.2%; P < 0.05) and 26% (28.3% ± 1.2% vs. 38.1% ± 1.2%; P < 0.001), respectively. More time in auto-mode was associated with improved continuous glucose monitoring metrics, lower HbA1c and decreased glycaemic variability. Time in auto-mode declined in men after 3 months, while women maintained similar auto-mode use throughout the study.

CONCLUSIONS

The HCL system improved HbA1c levels and time-in-range, and decreased time spent in hypoglycaemia and hyperglycaemia at 6 months. Auto-mode use was significantly correlated with continuous glucose monitoring metrics and glycaemic outcomes.

Switching from Suspend-Before-Low Insulin Pump Technology to a Hybrid Closed-Loop System Improves Glucose Control and Reduces Glucose Variability: A Retrospective Observational Case-Control Study

There are no data whether hybrid closed-loop (HCL) systems are superior to sensor-augmented pump (SAP) therapy with predictive low glucose suspend (PLGS) feature in improving glucose control. Aim of our study was to evaluate the effect on metabolic control and glucose variability of the switch from SAP therapy with PLGS to a HCL system in type 1 diabetic individuals. Forty adults with type 1 diabetes, who had been using SAP therapy with PLGS feature (Minimed 640G; Medtronic, Northridge, CA) for at least 12 months were evaluated in a 6-month case-control observational retrospective study. Twenty subjects who consecutively switched from Minimed 640G to a HCL system (Minimed 670G; Medtronic) (670G group) were compared with a control group consisting of 20 subjects who continued with the MiniMed 640G pump (640G group) matched for age, gender, and HbA_1c. At the end of the study there was a significant reduction in average HbA_1c levels (-4.9 ± 6.4 mmol/mol [-0.4% ± 0.6%], P < 0.01), sensor glucose concentrations (-15.4 ± 17.7 mg/dL, P < 0.005), coefficient of variation of sensor glucose concentrations (-3.8% ± 3.6%, P < 0.01), percentage time spent in both hyperglycemic range 181-250 mg/dL (-5.1% ± 4.5%, P < 0.05), and >250 mg/dL (-6.1% ± 6.9%, P < 0.05) in the 670G group, whereas they remained unchanged in the 640G group. Percentage of time spent in euglycemic range significantly increased (11.6% ± 8.3%, P < 0.005) only in the 670G group. There was no change in time spent in hypoglycemic range in both groups. In adults with type 1 diabetes, switching from a 640G to a 670G system significantly improved glucose control and reduced glucose variability, thus reaching in most cases the recommended targets for time spent in euglycemic and hyperglycemic ranges without increasing the risk of hypoglycemia.

Case series of a hybrid closed-loop system used in pregnancies in clinical practice

BACKGROUND

Hybrid closed-loop (HCL) therapy is rarely studied in pregnancy. We present three cases of women with type 1 diabetes who used the Medtronic 670G HCL system for most or all of gestation.

METHODS

The Medtronic 670G system has a manual mode (no automated insulin delivery) and an auto mode (AM, HCL therapy). Women in this case series used AM off-label in gestation.

RESULTS

Case 1 started HCL therapy in the second trimester, her sensor glucose time spent <3.9 and >10 mmol/L improved thereafter. Case 1 had average sensor glucose (ASG) levels of 6.4 ± 2.4 mmol/L in the first trimester, 7.0 ± 2.7 mmol/L in the second trimester before HCL use, 7.1 ± 2.1 mmol/L in the second trimester after HCL use, and 6.8 ± 1.9 mmol/L in the third trimester. Case 1 continued AM during operative delivery and post-partum. Cases 2 and 3 used HCL therapy throughout gestation but with inconsistent time in AM. When they increased time in AM their glycaemic indices improved. Case 2 had ASG of 9.5 ± 3.4, 8.6 ± 2.9, and 7.9 ± 2.5 mmol/L in the first through third trimesters, respectively. Case 3 had ASG of 11.1 ± 4.8 and 3.9 to 10 mmol/L in the first and second trimesters, respectively. Case 2 continued HCL therapy post-partum, Case 3 did not.

CONCLUSIONS

CareLink® Clinical Software only reports the non-pregnant time in range. Nonetheless, this represents the first report of HCL therapy in pregnancy with a system approved by the Food and Drug Administration in non-pregnant populations.

Six months of hybrid closed loop in the real-world: An evaluation of children and young adults using the 670G system

OBJECTIVE

To describe glycemic and psychosocial outcomes in youth with type 1 diabetes using a hybrid closed loop (HCL) system.

SUBJECTS

Youth with type 1 diabetes (2-25 years) starting the 670G HCL system for their diabetes care were enrolled in an observational study.

METHODS

Prospective data collection occurred during routine clinical care and included glycemic variables (sensor time in range [70-180 mg/dL], HbA1c), and psychosocial variables (Hypoglycemia Fear Survey [HFS]; Problem Areas in Diabetes [PAID]). Mixed models were used to analyze change across time.

RESULTS

Ninety-two youth (mean age 15.7 ± 3.6 years, 50% female, HbA1c 8.8% ± 1.8%) started HCL for their diabetes care. Youth used Auto Mode 65.5% ± 3.0% of the time at month 1, which decreased to 51.2% ± 3.4% at month 6 (P = .001). Sensor time in range increased from 50.7% ± 1.8% at baseline to 56.9% ± 2.1% at 6 months (P = .007). HbA1c decreased from 8.7% ± 0.2% at baseline to 8.4% ± 0.2% after 6 months of use (P ≤ .0001), with the greatest HbA1c decline in participants with high baseline HbA1c. Increased percent time in auto mode was associated with lower HbA1c (P = .02). Thirty percent of youth discontinued HCL in the first 6 months of use. There were no changes in the HFS or PAID scores across time.

CONCLUSIONS

HCL use is associated with improved glycemic control and no change in psychosocial outcomes in this clinical sample. The decline in HCL use across time suggests that youth experience barriers in sustaining use of HCL. Further research is needed to understand reasons for HCL discontinuation and determine intervention strategies.

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.

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.

A Clinical Training Program for Hybrid Closed Loop Therapy in a Pediatric Diabetes Clinic

BACKGROUND

Hybrid closed loop (HCL) therapy is now available in clinical practice for treatment of type 1 diabetes; however, there is limited research on how to educate patients on this new therapy. The purpose of this quality improvement project was to optimize a HCL education program for pediatric patients with type 1 diabetes (T1D).

METHODS

Our multidisciplinary team developed a novel HCL clinical training program for current insulin pump users, using a quality improvement process called the Plan-Do-Study-Act model. Seventy-two patients participated in the HCL training program, which included (1) an in-person group class to reinforce conventional insulin pump and CGM use on the new system, (2) a live video conference class to teach HCL use, and (3) three follow-up phone calls in the first 4 weeks after HCL training to assess system use, make insulin adjustments, and provide targeted reeducation. Diabetes educators collected data during follow-up calls, and patients completed a training satisfaction survey.

RESULTS

The quality improvement process resulted in a training program that emphasized education on HCL exits, CGM use, and optimizing insulin to carbohydrate ratio settings. Patients successfully sustained time in HCL in the initial weeks of use and rated the trainings and follow-up calls highly.

CONCLUSIONS

Ongoing educational support is vital in the early weeks of HCL use. This quality improvement project is the first to examine strategies for implementation of HCL therapy into a large pediatric diabetes center, and may inform best practices for implementation of new diabetes technologies into other diabetes clinics.