Diabetes Technology Meeting 2023

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 1 to November 4, 2023. Meeting topics included digital health; metrics of glycemia; the integration of glucose and insulin data into the electronic health record; technologies for insulin pumps, blood glucose monitors, and continuous glucose monitors; diabetes drugs and analytes; skin physiology; regulation of diabetes devices and drugs; and data science, artificial intelligence, and machine learning. A live demonstration of a personalized carbohydrate dispenser for people with diabetes was presented.

Integration of a Safety Module to Prevent Rebound Hypoglycemia in Closed-Loop Artificial Pancreas Systems

BACKGROUND

With automated insulin delivery (AID) systems becoming widely adopted in the management of type 1 diabetes, we have seen an increase in occurrences of rebound hypoglycemia or generated hypoglycemia induced by the controller's response to rapid glucose rises following rescue carbohydrates. Furthermore, as AID systems aim to enable complete automation of prandial control, algorithms are designed to react even more strongly to glycemic rises. This work introduces a rebound hypoglycemia prevention layer (HypoSafe) that can be easily integrated into any AID system.

METHODS

HypoSafe constrains the maximum permissible insulin delivery dose based on the minimum glucose reading from the previous hour and the current glucose level. To demonstrate its efficacy, we integrated HypoSafe into the latest University of Virginia (UVA) AID system and simulated two scenarios using the 100-adult cohort of the UVA/Padova T1D simulator: a nominal case including three unannounced meals, and another case where hypoglycemia was purposely induced by an overestimated manual bolus.

RESULTS

In both simulation scenarios, rebound hypoglycemia events were reduced with HypoSafe (nominal: from 39 to 0, hypo-induced: from 55 to 7) by attenuating the commanded basal (nominal: 0.27U vs. 0.04U, hypo-induced: 0.27U vs. 0.03U) and bolus (nominal: 1.02U vs. 0.05U, hypo-induced: 0.43U vs. 0.02U) within the 30-minute interval after treating a hypoglycemia event. No clinically significant changes resulted for time in the range of 70 to 180 mg/dL or above 180 mg/dL.

CONCLUSION

HypoSafe was shown to be effective in reducing rebound hypoglycemia events without affecting achieved time in range when combined with an advanced AID system.

Risks and Benefits of SGLT-2 Inhibitors for Type 1 Diabetes Patients Using Automated Insulin Delivery Systems-A Literature Review

The primary treatment for autoimmune Diabetes Mellitus (Type 1 Diabetes Mellitus-T1DM) is insulin therapy. Unfortunately, a multitude of clinical cases has demonstrated that the use of insulin as a sole therapeutic intervention fails to address all issues comprehensively. Therefore, non-insulin adjunct treatment has been investigated and shown successful results in clinical trials. Various hypoglycemia-inducing drugs such as Metformin, glucagon-like peptide 1 (GLP-1) receptor agonists, dipeptidyl peptidase-4 (DPP-4) inhibitors, amylin analogs, and Sodium-Glucose Cotransporters 2 (SGLT-2) inhibitors, developed good outcomes in patients with T1DM. Currently, SGLT-2 inhibitors have remarkably improved the treatment of patients with diabetes by preventing cardiovascular events, heart failure hospitalization, and progression of renal disease. However, their pharmacological potential has not been explored enough. Thus, the substantial interest in SGLT-2 inhibitors (SGLT-2is) underlines the present review. It begins with an overview of carrier-mediated cellular glucose uptake, evidencing the insulin-independent transport system contribution to glucose homeostasis and the essential roles of Sodium-Glucose Cotransporters 1 and 2. Then, the pharmacological properties of SGLT-2is are detailed, leading to potential applications in treating T1DM patients with automated insulin delivery (AID) systems. Results from several studies demonstrated improvements in glycemic control, an increase in Time in Range (TIR), a decrease in glycemic variability, reduced daily insulin requirements without increasing hyperglycemic events, and benefits in weight management. However, these advantages are counterbalanced by increased risks, particularly concerning Diabetic Ketoacidosis (DKA). Several clinical trials reported a higher incidence of DKA when patients with T1DM received SGLT-2 inhibitors such as Sotagliflozin and Empagliflozin. On the other hand, patients with T1DM and a body mass index (BMI) of ≥27 kg/m2 treated with Dapagliflozin showed similar reduction in hyperglycemia and body weight and insignificantly increased DKA incidence compared to the overall trial population. Additional multicenter and randomized studies are required to establish safer and more effective long-term strategies based on patient selection, education, and continuous ketone body monitoring for optimal integration of SGLT-2 inhibitors into T1DM therapeutic protocol.

Intelligent Insulin vs. Artificial Intelligence for Type 1 Diabetes: Will the Real Winner Please Stand Up?

Research in the treatment of type 1 diabetes has been addressed into two main areas: the development of "intelligent insulins" capable of auto-regulating their own levels according to glucose concentrations, or the exploitation of artificial intelligence (AI) and its learning capacity, to provide decision support systems to improve automated insulin therapy. This review aims to provide a synthetic overview of the current state of these two research areas, providing an outline of the latest development in the search for "intelligent insulins," and the results of new and promising advances in the use of artificial intelligence to regulate automated insulin infusion and glucose control. The future of insulin treatment in type 1 diabetes appears promising with AI, with research nearly reaching the possibility of finally having a "closed-loop" artificial pancreas.

Racial Disparities in Diabetes Technology Adoption and Their Association with HbA1c and Diabetic Ketoacidosis

Aim

Poorer glycemic control and higher diabetic ketoacidosis (DKA) rates are seen in racial/ethnic minorities with type 1 diabetes (T1D). Use of diabetes technologies such as continuous glucose monitors (CGM), continuous subcutaneous insulin infusion (CSII) and automated insulin delivery (AID) systems has been shown to improve glycemic control and reduce DKA risk. We examined race/ethnicity differences in diabetes technology use and their relationship with HbA1c and DKA.

Methods

Data from patients aged ≥12 years with T1D for ≥1 year, receiving care from a single diabetes center, were examined. Patients were classified as Non-Hispanic White (n=3945), Non-Hispanic Black (Black, n=161), Hispanic (n=719), and Multiracial/Other (n=714). General linear models and logistic regression were used.

Results

Black (OR=0.22, 0.15-0.32) and Hispanic (OR=0.37, 0.30-0.45) patients were less likely to use diabetes technology. This disparity was greater in the pediatric population (p-interaction=0.06). Technology use associated with lower HbA1c in each race/ethnic group. Among technology users, AID use associated with lower HbA1c compared to CGM and/or CSII (HbA1c of 8.4% vs 9.2%, respectively), with the greatest difference observed for Black adult AID users. CSII use associated with a lower odds of DKA in the past year (OR=0.73, 0.54-0.99), a relationship that did not vary by race (p-interaction =0.69); this inverse association with DKA was not observed for CGM or AID.

Conclusion

Disparities in diabetes technology use, DKA, and glycemic control were apparent among Black and Hispanic patients with T1D. Differences in technology use ameliorated but did not fully account for disparities in HbA1c or DKA.

UK's Association of British Clinical Diabetologist's Diabetes Technology Network (ABCD-DTN): Best practice guide for hybrid closed-loop therapy

This best practice guide is written with the aim of providing an overview of current hybrid closed-loop (HCL) systems in use within the United Kingdom's (UK) National Health Service (NHS) and to provide education and advice for their management on both an individual and clinical service level. The environment of diabetes technology, and particularly HCL systems, is rapidly evolving. The past decade has seen unprecedented advances in the development of HCL systems. These systems improve glycaemic outcomes and reduce the burden of treatment for people with type 1 diabetes (pwT1D). It is anticipated that access to these systems will increase in England as a result of updates in National Institute of Health and Care Excellence (NICE) guidance providing broader support for the use of real-time continuous glucose monitoring (CGM) for pwT1D. NICE is currently undertaking multiple-technology appraisal into HCL systems. Based on experience from centres involved in supporting advanced technologies as well as from the recent NHS England HCL pilot, this guide is intended to provide healthcare professionals with UK expert consensus on the best practice for initiation, optimisation and ongoing management of HCL therapy.

The Evolution of Diabetes Technology - Options Towards Personalized Care

Advances in diabetes technology, especially in the last few decades, have transformed our ability to deliver care to persons with diabetes (PWD). Developments in glucose monitoring, especially continuous glucose monitoring systems (CGM), have revolutionized diabetes care and empowered our patients to manage their disease. CGM has also played an integral role in advancing automated insulin delivery systems. Currently available and upcoming advanced hybrid-closed loop systems aim to decrease patient involvement and are approaching the functionality of a fully automated artificial pancreas. Other advances, such as smart insulin pens and daily patch pumps, offer more options for patients and require less complicated and costly technology. Evidence to support the role of diabetes technology is growing, and PWD and clinicians must choose the right type of technology with a personalized strategy to manage diabetes effectively. Here, we review currently available diabetes technologies, summarize their individual features and highlight key patient factors to consider when creating a personalized treatment plan. We also address current challenges and barriers to the adoption of diabetes technologies.

Glycemic Risk Index Profiles and Predictors Among Diverse Adults With Type 1 Diabetes

BACKGROUND

The Glycemia Risk Index (GRI) was introduced as a single value derived from the ambulatory glucose profile that identifies patients who need attention. This study describes participants in each of the five GRI zones and examines the percentage of variation in GRI scores that is explained by sociodemographic and clinical variables among diverse adults with type 1 diabetes.

METHODS

A total of 159 participants provided blinded continuous glucose monitoring (CGM) data over 14 days (mean age [SD] = 41.4 [14.5] years; female = 54.1%, Hispanic = 41.5%). Glycemia Risk Index zones were compared on CGM, sociodemographic, and clinical variables. Shapley value analysis examined the percentage of variation in GRI scores explained by different variables. Receiver operating characteristic curves examined GRI cutoffs for those more likely to have experienced ketoacidosis or severe hypoglycemia.

RESULTS

Mean glucose and variability, time in range, and percentage of time in high, and very high, glucose ranges differed across the five GRI zones (P values < .001). Multiple sociodemographic indices also differed across zones, including education level, race/ethnicity, age, and insurance status. Sociodemographic and clinical variables collectively explained 62.2% of variance in GRI scores. A GRI score ≥84.5 reflected greater likelihood of ketoacidosis (area under the curve [AUC] = 0.848), and scores ≥58.2 reflected greater likelihood of severe hypoglycemia (AUC = 0.729) over the previous six months.

CONCLUSIONS

Results support the use of the GRI, with GRI zones identifying those in need of clinical attention. Findings highlight the need to address health inequities. Treatment differences associated with the GRI also suggest behavioral and clinical interventions including starting individuals on CGM or automated insulin delivery systems.

School Nurse Confidence with Diabetes Devices in Relation to Diabetes Knowledge and Prior Training: A Study of Convergent Validity

Objective

The Diabetes Device Confidence Scale (DDCS) is a new scale designed to evaluate school nurse confidence with diabetes devices. We hypothesized that DDCS score would be associated with related constructs of school nurse diabetes knowledge, experience, and training.

Research Design and Methods

In a cross-sectional study, we co-administered the DDCS and Diabetes Knowledge Test 2 (DKT2) questionnaires to school nurses in Pennsylvania. We summarized DDCS scores (range 1-5) descriptively. We evaluated the relationship between DKT2 percent score and DDCS mean score with the Spearman correlation coefficient. Simple linear regression examined school nurse characteristics as predictors of DDCS score.

Results

A total of 271 completed surveys were received. Mean DDCS score was 3.16±0.94, indicating moderate confidence with devices overall. School nurses frequently reported low confidence in items representing specific skills, including suspending insulin delivery (40%), giving a manual bolus (42%), knowing when to calibrate a continuous glucose monitor (48%), changing an insulin pump site (54%), and setting a temporary basal rate (58%). Mean DKT2 score was 89.5±0.1%, which was weakly but not significantly correlated with DDCS score (r=0.12, p=0.06). Formal device training (p<0.001), assisting ≥5 students with diabetes devices in the past 5 years (p<0.01), and a student caseload between 1000-1500 students (p<0.001) were associated with higher mean DDCS score.

Conclusions

DDCS score is related to prior training and experience, providing evidence for the scale's convergent validity. The DDCS may be a useful tool for assessing school nurse readiness to use devices and identify areas to enhance knowledge and practical skills.

Hybrid Closed-Loop Insulin Pump Technology Can Be Safely Used in the Inpatient Setting

BACKGROUND

Hybrid closed-loop (HCL) systems, also known as automated insulin delivery systems, are a rapidly growing technology in diabetes management. Because more patients are using these systems in the outpatient setting, it is important to also assess inpatient safety to determine whether HCL use can be continued when those patients become hospitalized.

METHODS

The records of patients using HCL technology on admission to our hospital between June 1, 2020, and June 30, 2021, were analyzed.

RESULTS

The final analysis included 71 patients divided into 3 categories based on their pump use as an inpatient: (1) HCL users; (2) manual pump users; and (3) pump removed. All cohorts were similar in age, sex, race, hemoglobin A1C at admission, and in Medicare Severity Diagnosis Related Group. Pairwise comparisons indicated that patient-stay mean glucose levels, frequency of patient-specific hyperglycemic measurements, and frequency of hypoglycemic events were similar between all groups. No adverse events, particularly occurrences of diabetic ketoacidosis, pump site complications or infection, or equipment malfunction, were reported.

CONCLUSION

This preliminary case series review indicates that continued use of HCL technology in the hospital is safe. Moreover, glycemic control in HCL users was comparable with that in those using insulin pump with manual settings and those converted to basal-bolus insulin therapy.

Design and Testing of a Smartphone Application for Real-Time Tracking of CSII and CGM Site Rotation Compliance in Patients With Type 1 Diabetes

INTRODUCTION

Glycemic control in patients with type 1 diabetes can be difficult to achieve. One critical aspect of insulin delivery is site rotation, which is necessary to reduce dermatologic complications of repeated insulin infusion. No current application is designed to help patients track sites and instruct on overused sites.

OBJECTIVE

The objectives of this study were to (1) design a smartphone app, Insulin Site Guide, to gather real-time information on continuous subcutaneous insulin infusion (CSII) and continuous glucose monitor (CGM) site location and rotation compliance and instruct subjects on the use of an overused site; (2) conduct a usability study to measure site rotation compliance; and (3) report subject satisfaction with the app.

DESIGN

The app is installed on the subject's smartphone. Subjects use the app to record CSII and CGM placement in real-time. Data are sent to the study team at the end of the study. Subjects complete a questionnaire concerning the app.

RESULTS

We report site rotation compliance data for eight subjects and survey responses for 10 subjects. Initial data from eight subjects indicate a high site rotation compliance of 84% for insulin pumps. In general, the majority of users indicate high satisfaction with the app.

CONCLUSIONS

Insulin Site Guide is a mobile app that uses a novel algorithm to better guide site rotation. Use of the app has the potential to improve site rotation and decrease dermatologic complications of diabetes with long-term use.

A real-world study of user characteristics, safety and efficacy of open-source closed-loop systems and Medtronic 670G

We report a real-world evaluation of the first commercially approved automated insulin delivery (AID) system, MiniMed 670G (670G), and open source-automated insulin delivery (OS-AID) systems. This was undertaken as a retrospective observational study in adults with type 1 diabetes using AID systems for 6 months or longer in a publicly funded health service using clinically validated data. Sixty-eight adults (38 670G, 30 OS-AID systems) were included. OS-AID system users were younger, had a shorter diabetes duration and a higher education status. OS-AID systems displayed a significantly better change in HbA1c (median -0.9% [-0.4%, -1.1%] vs. -0.1% [IQR -0.7%, 0.2%], P = .004) and time in range 3.9-10 mmol/L (mean 78.5%, SD ± 12.0% vs. 68.2% ± 14.7%, P = .024) compared with 670G. Both systems showed minimal hypoglycaemia, with OS-AID systems revealing significantly improved secondary outcomes of mean glucose and percentage of time more than 10 mmol/L, with a higher percentage of time of less than 3 mmol/L. OS-AID system users displayed improved glycaemic outcomes with no clinical safety concerns compared with 670G, although higher weight-adjusted insulin dose and weight gain were noted. The study highlights key differences in OS-AID system user characteristics that are important for interpreting real-world findings from recent OS-AID system studies.

Evidence on User-Led Innovation in Diabetes Technology (The OPEN Project): Protocol for a Mixed Methods Study

Background

Digital innovations in health care have traditionally followed a top-down pathway, with manufacturers leading the design and production of technology-enabled solutions and those living with chronic conditions involved only as passive recipients of the end product. However, user-driven open-source initiatives in health care are becoming increasingly popular. An example is the growing movement of people with diabetes, who create their own “Do-It-Yourself Artificial Pancreas Systems” (DIYAPS).

Objective

The overall aim of this study is to establish the empirical evidence base for the clinical effectiveness and quality-of-life benefits of DIYAPS and identify the challenges and possible solutions to enable their wider diffusion.

Methods

A research program comprising 5 work packages will examine the outcomes and potential for scaling up DIYAPS solutions. Quantitative and qualitative methodologies will be used to examine clinical and self-reported outcome measures of DIYAPS users. The majority of members of the research team live with type 1 diabetes and are active DIYAPS users, making Outcomes of Patients’ Evidence With Novel, Do-It-Yourself Artificial Pancreas Technology (OPEN) a unique, user-driven research project.

Results

This project has received funding from the European Commission’s Horizon 2020 Research and Innovation Program, under the Marie Skłodowska-Curie Action Research and Innovation Staff Exchange. Researchers with both academic and nonacademic backgrounds have been recruited to formulate research questions, drive the research process, and disseminate ongoing findings back to the DIYAPS community and other stakeholders.

Conclusions

The OPEN project is unique in that it is a truly patient- and user-led research project, which brings together an international, interdisciplinary, and intersectoral research group, comprising health care professionals, technical developers, biomedical and social scientists, the majority of whom are also living with diabetes. Thus, it directly addresses the core research and user needs of the DIYAPS movement. As a new model of cooperation, it will highlight how researchers in academia, industry, and the patient community can create patient-centric innovation and reduce disease burden together.

International Registered Report Identifier (IRRID)

PRR1-10.2196/15368