Extended Use of an Open-Source Automated Insulin Delivery System in Children and Adults with Type 1 Diabetes: The 24-Week Continuation Phase Following the CREATE Randomized Controlled Trial

Insulin Pump Therapy and Adverse Skin Reactions With Focus on Allergic Contact Dermatitis in Individuals Living With Diabetes Mellitus: A Systematic Review and Clinical-Based Update

BACKGROUND

The use of insulin pumps (continuous subcutaneous insulin infusion [CSII]) in individuals living with type 1 diabetes (T1D) improves disease control. However, adverse skin reactions may hamper compliance. We aimed to assess the relationship of insulin pumps, particularly that of infusion set therapy, used in children and adults with T1D and dermatitis including allergic contact dermatitis (ACD).

METHODS

A systematic search of PubMed, and EMBASE, of full-text studies reporting dermatitis in persons with diabetes using a CSII was conducted from 2020 to 2023. The Newcastle-Ottawa Scale was used to assess study quality. The inventory performed at the Department of Occupational and Environmental Dermatology, Malmö, Sweden (YMDA) was also performed highlighting the diagnostic process.

RESULTS

Among the 391 screened abstracts, 21 studies fulfilled the inclusion criteria. Seven studies included data on children only, four studies were on adults, and nine studies reported data on both children and adults. Participants were exposed to a broad range of pumps. Dermatitis was rarely specified. Up to 60% of those referred to a university hospital due to skin reactions possibly related to insulin pumps had an ACD.

CONCLUSIONS

The review and our findings indicate that there is not sufficient focus on contact allergy in the primary toxicological evaluations of substances used also for insulin pump therapy products and that possible adverse skin reactions are not correctly followed up in the clinical setting.

Automated Insulin Delivery Systems in Pediatric Type 1 Diabetes: A Narrative Review

This narrative review assesses the use of automated insulin delivery (AID) systems in managing persons with type 1 diabetes (PWD) in the pediatric population. It outlines current research, the differences between various AID systems currently on the market and the challenges faced, and discusses potential opportunities for further advancements within this field. Furthermore, the narrative review includes various expert opinions on how different AID systems can be used in the event of challenges with rapidly changing insulin requirements. These include examples, such as during illness with increased or decreased insulin requirements and during physical activity of different intensities or durations. Case descriptions give examples of scenarios with added user-initiated actions depending on the type of AID system used. The authors also discuss how another AID system could have been used in these situations.

Point-Counterpoint: The Need for Do-It-Yourself (DIY) Open Source (OS) AID Systems in Type 1 Diabetes Management

In the last decade, technology developed by people with diabetes and their loved ones has added to the options for diabetes management. One such example is that of automated insulin delivery (AID) algorithms, which were created and shared as open source by people living with type 1 diabetes (T1D) years before commercial systems were first available. Now, numerous options for commercial systems exist in some countries, yet tens of thousands of people with diabetes are still choosing Open-Source AID (OS-AID), previously called "do-it-yourself" (DIY) systems, which are noncommercial versions of these open-source AID systems. In this article, we provide point and counterpoint perspectives regarding (1) safety and efficacy, (2) regulation and support, (3) user choice and flexibility, (4) access and affordability, and (5) patient and provider education, for open source and commercial AID systems. The perspectives reflected here include that of a person living with T1D who uses and has developed OS-AID systems, a physician-researcher based in the United States who conducts clinical trials to support development of commercial AID systems and supports people with diabetes using all types of AID, and an endocrinologist with T1D who uses both systems and treats people with diabetes using all types of AID.

9. Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2024

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

7. Diabetes Technology: Standards of Care in Diabetes-2024

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

Comparison of Control-IQ and open-source AndroidAPS automated insulin delivery systems in adults with type 1 diabetes: The CODIAC study

AIM

To compare open-source AndroidAPS (AAPS) and commercially available Control-IQ (CIQ) automated insulin delivery (AID) systems in a prospective, open-label, single-arm clinical trial.

METHODS

Adults with type 1 diabetes who had been using AAPS by their own decision entered the first 3-month AAPS phase then were switched to CIQ for 3 months. The results of this treatment were compared with those after the 3-month AAPS phase. The primary endpoint was the change in time in range (% TIR; 70-80 mg/dL).

RESULTS

Twenty-five people with diabetes (mean age 34.32 ± 11.07 years; HbA1c 6.4% ± 3%) participated in this study. CIQ was comparable with AAPS in achieving TIR (85.72% ± 7.64% vs. 84.24% ± 8.46%; P = .12). Similarly, there were no differences in percentage time above range (> 180 and > 250 mg/dL), mean sensor glucose (130.3 ± 13.9 vs. 128.3 ± 16.9 mg/dL; P = .21) or HbA1c (6.3% ± 2.1% vs. 6.4% ± 3.1%; P = .59). Percentage time below range (< 70 and < 54 mg/dL) was significantly lower using CIQ than AAPS. Even although participants were mostly satisfied with CIQ (63.6% mostly agreed, 9.1% strongly agreed), they did not plan to switch to CIQ.

CONCLUSIONS

The CODIAC study is the first prospective study investigating the switch between open-source and commercially available AID systems. CIQ and AAPS were comparable in achieving TIR. However, hypoglycaemia was significantly lower with CIQ.

Psychosocial Outcomes Among Users and Nonusers of Open-Source Automated Insulin Delivery Systems: Multinational Survey of Adults With Type 1 Diabetes

BACKGROUND

Emerging research suggests that open-source automated insulin delivery (AID) may reduce diabetes burden and improve sleep quality and quality of life (QoL). However, the evidence is mostly qualitative or uses unvalidated, study-specific, single items. Validated person-reported outcome measures (PROMs) have demonstrated the benefits of other diabetes technologies. The relative lack of research investigating open-source AID using PROMs has been considered a missed opportunity.

OBJECTIVE

This study aimed to examine the psychosocial outcomes of adults with type 1 diabetes using and not using open-source AID systems using a comprehensive set of validated PROMs in a real-world, multinational, cross-sectional study.

METHODS

Adults with type 1 diabetes completed 8 validated measures of general emotional well-being (5-item World Health Organization Well-Being Index), sleep quality (Pittsburgh Sleep Quality Index), diabetes-specific QoL (modified DAWN Impact of Diabetes Profile), diabetes-specific positive well-being (4-item subscale of the 28-item Well-Being Questionnaire), diabetes treatment satisfaction (Diabetes Treatment Satisfaction Questionnaire), diabetes distress (20-item Problem Areas in Diabetes scale), fear of hypoglycemia (short form of the Hypoglycemia Fear Survey II), and a measure of the impact of COVID-19 on QoL. Independent groups 2-tailed t tests and Mann-Whitney U tests compared PROM scores between adults with type 1 diabetes using and not using open-source AID. An analysis of covariance was used to adjust for potentially confounding variables, including all sociodemographic and clinical characteristics that differed by use of open-source AID.

RESULTS

In total, 592 participants were eligible (attempting at least 1 questionnaire), including 451 using open-source AID (mean age 43, SD 13 years; n=189, 41.9% women) and 141 nonusers (mean age 40, SD 13 years; n=90, 63.8% women). Adults using open-source AID reported significantly better general emotional well-being and subjective sleep quality, as well as better diabetes-specific QoL, positive well-being, and treatment satisfaction. They also reported significantly less diabetes distress, fear of hypoglycemia, and perceived less impact of the COVID-19 pandemic on their QoL. All were medium-to-large effects (Cohen d=0.5-1.5). The differences between groups remained significant after adjusting for sociodemographic and clinical characteristics.

CONCLUSIONS

Adults with type 1 diabetes using open-source AID report significantly better psychosocial outcomes than those not using these systems, after adjusting for sociodemographic and clinical characteristics. Using validated, quantitative measures, this real-world study corroborates the beneficial psychosocial outcomes described previously in qualitative studies or using unvalidated study-specific items.

Utility and precision evidence of technology in the treatment of type 1 diabetes: a systematic review

BACKGROUND

The greatest change in the treatment of people living with type 1 diabetes in the last decade has been the explosion of technology assisting in all aspects of diabetes therapy, from glucose monitoring to insulin delivery and decision making. As such, the aim of our systematic review was to assess the utility of these technologies as well as identify any precision medicine-directed findings to personalize care.

METHODS

Screening of 835 peer-reviewed articles was followed by systematic review of 70 of them (focusing on randomized trials and extension studies with ≥50 participants from the past 10 years).

RESULTS

We find that novel technologies, ranging from continuous glucose monitoring systems, insulin pumps and decision support tools to the most advanced hybrid closed loop systems, improve important measures like HbA1c, time in range, and glycemic variability, while reducing hypoglycemia risk. Several studies included person-reported outcomes, allowing assessment of the burden or benefit of the technology in the lives of those with type 1 diabetes, demonstrating positive results or, at a minimum, no increase in self-care burden compared with standard care. Important limitations of the trials to date are their small size, the scarcity of pre-planned or powered analyses in sub-populations such as children, racial/ethnic minorities, people with advanced complications, and variations in baseline glycemic levels. In addition, confounders including education with device initiation, concomitant behavioral modifications, and frequent contact with the healthcare team are rarely described in enough detail to assess their impact.

CONCLUSIONS

Our review highlights the potential of technology in the treatment of people living with type 1 diabetes and provides suggestions for optimization of outcomes and areas of further study for precision medicine-directed technology use in type 1 diabetes.