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

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.

Hybrid Closed Loop Using a Do-It-Yourself Artificial Pancreas System in Adults With Type 1 Diabetes

OBJECTIVE

There is increasing use of open-source artificial pancreas systems (APS) in the management of Type 1 diabetes. Our aim was to assess the safety and efficacy of the automated insulin delivery system AndroidAPS (AAPS), compared with stand-alone pump therapy in people with type 1 diabetes. The primary outcome was the difference in the percentage of time in range (TIR, 70-180 mg/dL). Secondary aims included mean sensor glucose value and percent continuous glucose monitor (CGM) time below range (TBR, <70 mg/dL).

RESEARCH DESIGN AND METHODS

This open-label single-center randomized crossover study (ANZCTR, Australian New Zealand clinical trial registry, ANZCTR-ACTRN12620001191987) comprised 20 participants with type 1 diabetes on established pump therapy, assigned to either stand-alone insulin pump therapy or the open-source AAPS hybrid closed-loop system for four weeks, with crossover to the alternate arm for the following four weeks. The CGM outcome parameters were measured by seven-day CGM at baseline and the final week of each four-week study arm.

RESULTS

Twenty participants were recruited (60% women), aged 45.8 ± 15.9 years, with mean diabetes duration of 23.9 ± 13.2 years, baseline glycated hemoglobin (HbA1c) 7.5% ± 0.5% (58 ± 6 mmol/mol) and mean TIR 62.3% ± 12.9%. The change in TIR from baseline for AAPS compared with stand-alone pump therapy was 18.6% (11.4-25.9), (P < .001), TIR 76.6% ± 11.7%, 58.0% ± 15.6%, for AAPS and stand-alone pump, respectively. Time glucose <54 mg/dL was not increased (mean = -2.0%, P = .191). No serious adverse events or episodes of severe hypoglycemia were recorded.

CONCLUSIONS

This clinical trial of the open-source AAPS hybrid closed-loop system performed in an at-home setting demonstrated comparable safety to stand-alone pump therapy. The glycemic outcomes of AAPS were superior with improved TIR, and there was no significant difference in TBR compared with stand-alone pump therapy.

Exploring Technology's Influence on Health Behaviours and Well-being in Type 1 Diabetes: a Review

PURPOSE OF REVIEW

Maintaining positive health behaviours promotes better health outcomes for people with type 1 diabetes (T1D). However, implementing these behaviours may also lead to additional management burdens and challenges. Diabetes technologies, including continuous glucose monitoring systems, automated insulin delivery systems, and digital platforms, are being rapidly developed and widely used to reduce these burdens. Our aim was to review recent evidence to explore the influence of these technologies on health behaviours and well-being among adults with T1D and discuss future directions.

RECENT FINDINGS

Current evidence, albeit limited, suggests that technologies applied in diabetes self-management education and support (DSME/S), nutrition, physical activity (PA), and psychosocial care areas improved glucose outcomes. They may also increase flexibility in insulin adjustment and eating behaviours, reduce carb counting burden, increase confidence in PA, and reduce mental burden. Technologies have the potential to promote health behaviours changes and well-being for people with T1D. More confirmative studies on their effectiveness and safety are needed to ensure optimal integration in standard care practices.

Removing Barriers, Bridging the Gap, and the Changing Role of the Health Care Professional with Automated Insulin Delivery Systems

As all people with type 1 diabetes (T1D) and some with type 2 diabetes (T2D) require insulin, there is a need to develop management methods that not only achieve glycemic targets but also reduce the burden of living with diabetes. After insulin pumps and continuous glucose monitors, the next step in the evolution of diabetes technology is automated insulin delivery (AID) systems, which have transformed intensive insulin management over the past decade, as these systems address the shortcomings of previous management options. However, AID use remains fairly limited, and access represents a major barrier to use for many people with diabetes, despite these systems being standard of care. Therefore, the future of AID will necessitate addressing barriers related to social determinants of health, finances, and an expansion of the number and type of health care professionals (HCPs) prescribing AID systems. These crucial steps will be essential to ensure that everyone with intensively managed diabetes can use AID systems. The impact of implementing these changes will create a shift in the future of diabetes care that will result in achievement of more targeted glycemia and psychosocial outcomes for all people with diabetes and an expansion of the role of all HCPs in AID-related diabetes care. Even more importantly, by addressing social determinants of health and clinical inertia related to AID, the field can address disparities in outcomes across countries, race, gender, socioeconomic status, and insurance status. Furthermore, the increased use of AID system will provide more time during appointments for a shift in the discussion away from fine tuning insulin dosing and toward a focus on more topics related to behavior and conversations about general health. This will include psychosocial outcomes, and quality of life. In addition, these changes can hopefully allow for time to discuss more general issues, such as cardiovascular health, obesity prevention, diabetes-related complications, and other health-related concerns.

Retrospective Comparison of Commercially Available Automated Insulin Delivery With Open-Source Automated Insulin Delivery Systems in Type 1 Diabetes

BACKGROUND

Automated insulin delivery (AID) systems have shown to improve glycemic control in a range of populations and settings. At the start of this study, only one commercial AID system had entered the Austrian market (MiniMed 670G, Medtronic). However, there is an ever-growing community of people living with type 1 diabetes (PWT1D) using open-source (OS) AID systems.

MATERIALS AND METHODS

A total of 144 PWT1D who used either the MiniMed 670G (670G) or OS-AID systems routinely for a period of at least three to a maximum of six months, between February 18, 2020 and January 15, 2023, were retrospectively analyzed (116 670G aged from 2.6 to 71.8 years and 28 OS-AID aged from 3.4 to 53.5 years). The goal is to evaluate and compare the quality of glycemic control of commercially available AID and OS-AID systems and to present all data by an in-depth descriptive analysis of the population. No statistical tests were performed.

RESULTS

The PWT1D using OS-AID systems spent more time in range (TIR)70-180 mg/dL (81.7% vs 73.9%), less time above range (TAR)181-250 mg/dL (11.1% vs 19.6%), less TAR>250 mg/dL (2.5% vs 4.3%), and more time below range (TBR)54-69 mg/dL (2.2% vs 1.7%) than PWT1D using the 670G system. The TBR<54 mg/dL was comparable in both groups (0.3% vs 0.4%). In the OS-AID group, median glucose level and glycated hemoglobin (HbA1c) were lower than in the 670G system group (130 vs 150 mg/dL; 6.2% vs 7.0%).

CONCLUSION

In conclusion, both groups were able to achieve satisfactory glycemic outcomes independent of age, gender, and diabetes duration. However, the PWT1D using OS-AID systems attained an even better glycemic control with no clinical safety concerns.

Open-source Artificial Pancreas Systems Are Safe and Effective When Supported In-clinic: Outcomes in 248 Consecutive Type 1 Diabetes Clients

OBJECTIVE

Our aim in this study was to determine the safety, glycemia, and quality of life (QoL) associated with in-clinic installation and management of supported open-source artificial pancreas systems (SOSAPS) in type 1 diabetes (T1D).

METHODS

This investigation is a retrospective cohort study of consecutive SOSAPS users at a Canadian diabetes centre. SOSAPS were offered to all moderately tech-savvy T1D clients on sensor-augmented multiple daily injection or pump, able to pay for hardware, and willing to sign a consent and waiver document. SOSAPS were installed and maintained by clinic staff at no cost to clients. iPhone users were assigned to either Loop (n=108) or iPhone artificial pancreas systems (iAPS; n=114) and Android users to Android-type APS (n=24). Outcomes included severe hypoglycemia and diabetic ketoacidosis (DKA), time in range (TIR) 4.0 to 10.0 mmol/L, time below range (TBR) <4 mmol/L, glucose management indicator (GMI), mean sensor glucose (MSG), change in glycated hemoglobin (A1C), and QoL.

RESULTS

Two hundred forty-eight subjects (131 males, 117 females), with a mean age of 36 years and diabetes duration of 21 years, experienced 3 episodes of severe hypoglycemia and no DKA over a follow-up of 17 months. TIR rose by 16%, from 64% to 80% (p<0.0001); TBR fell by 1.0%, from 3.5% to 2.5% (p=0.001); MSG fell from 9.0 to 8.1 mmol/L (p<0.001); GMI fell from 7.3% to 6.7% (p<0.001); and A1C fell from 7.2% to 6.7% (p<0.0001). QoL scores were healthy before and improved after SOSAPS.

CONCLUSIONS

Clients with T1D using SOSAPS and supported with no-cost care to the client (software, technology, and physician/physician assistant) safely achieved improved TIR, GMI, A1C, and QoL.

Does Insulin Delivery Technology Change Our Relationship with Foods? A Scoping Review

Introduction: Automated insulin delivery (AID) systems reduce burden and improve glycemic management for people with type 1 diabetes (PwT1D) by automatically adjusting insulin as a response to measured glucose levels. There is a lack of evidence on AID and nutrition variables such as dietary intake, eating behaviors, and disordered eating. Objectives: This scoping review aims to provide a summary of the literature regarding AID and nutrition variables and to identify gaps that require further investigation. Methods: Two researchers conducted a blinded search of Medline (OVID) and PubMed for studies, including AID use (compared to non-AID use) and nutrition variables. Studies from January 2000 to July 2023 were included, as were PwT1D of all ages. Results: A total of 3132 articles were screened for appropriateness. After exclusions, 7 studies were included (2017-2023): 4 qualitative, 1 crossover, 1 randomized controlled, and 1 observational. Studies included adolescents (n = 1), adults (n = 3) or both (n = 2), and all ages (n = 1). In quantitative studies, AID was associated with lower eating distress (-0.43 ± 0.12, P = 0.004) and higher quality of life (3.1, 95% confidence interval [CI]: 0.8-5.4, P = 0.01), but not grams of carbohydrates at meals (1.0; 95% CI: -0.7 to 3.0; P = 0.24) and snacks (0.004; 95% CI: -0.8 to 0.8; P = 0.99) compared to non-AID use. In qualitative studies, AID increased the frequency and portions of food intake and led to less dietary control from parents. AID users reported eating foods higher in energy density. PwT1D were less worried about achieving accurate carbohydrate counting (CC) when using AID. Conclusions: AID use appears to influence eating behaviors, dietary patterns, and CC, although evidence was limited. AID may reduce food management burden due to the perception that AID can correct for CC inaccuracy. Significance: Further research needs to determine if AID allows for simplification of CC and improves eating behaviors while maintaining glycemic stability.

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.

Open-source automated insulin delivery systems and formal healthcare: A qualitative study of challenges in the interaction between service-users with type 1 diabetes and healthcare professionals

OBJECTIVES

To explore the challenges that open-source automated insulin delivery systems pose to the encounter between service-users and healthcare professionals and how these challenges might be addressed in the future.

METHODS

Five adult service-users and six healthcare professionals participated in semi-structured interviews. A six-step thematic analysis was conducted, the focus being on challenges and needs for improvement of the interactions.

RESULTS

The analysis revealed three overarching challenges and wishes: (1) Lack of exchange of experiences. Service-users are reticent about disclosing their use of the systems to healthcare professionals. (2) Unclear ethical responsibility. Service-users are aware of their responsibility and guidelines can help to alleviate healthcare professional's legal responsibility; however, ambiguities around ethical responsibility for healthcare professionals remain an impediment to meaningful clinical interactions. (3) Unresolved individual and mutual expectations. Service-users expect better access to technology and focus on psychosocial aspects. In contrast, healthcare professionals fear the burden associated with the rising technical expectations.

CONCLUSION

Transparency and openness towards open-source systems need to be part of service-user and healthcare professionals interaction. Requirements for future care include improved knowledge about the systems, an openminded approach towards user-driven initiatives among healthcare professionals, and a focus on psychosocial aspects in the interaction.

Characteristics associated with having a hemoglobin A1c ≤ 7 % (≤53 mmol/mol) among adults with type 1 diabetes using an automated insulin delivery system

BACKGROUND

We aim to investigate which characteristics are associated with having an HbA1c ≤ 7 % (≤53 mmol/mol) among adult automated insulin delivery (AID) users living with type 1 diabetes (T1D).

METHODS

Cross-sectional study using data from the T1D BETTER registry.

INCLUSION CRITERIA

aged ≥ 18 years old, using a commercial AID system, and with a reported HbA1c range value. Participants were divided into two groups (HbA1c ≤ 7 % group, N = 57; and HbA1c > 7 % group, N = 74).

RESULTS

A total of 131 participants were included: 61.8 % females, median age (Q1-Q3) was 43.0 (30.0, 55.0) years, and median duration of T1D was 24.0 (16.0, 36.0) years. Logistic regression analysis suggested that participants with a bachelor's degree or above were more likely (OR 3.04, 95 %CI 1.22, 7.58; P = 0.017) and with a longer duration of pump use were less likely (OR 0.90, 95 %CI 0.84, 0.98; P = 0.009) to report an HbA1c ≤ 7 % when using an AID, after adjusting for age, sex, body mass index, and annual household income.

CONCLUSIONS

Our study indicates that among AID users, in order to maximize benefits, additional support is needed for those who do not have a bachelor's degree and/or who have been using an insulin pump for a long time.

The impact of hypoglycaemia on quality of life among adults with type 1 diabetes: Results from "YourSAY: Hypoglycaemia"

AIMS

Research on hypoglycaemia and quality of life (QoL) has focused mostly on severe hypoglycaemia and psychological outcomes, with less known about other aspects of hypoglycaemia (e.g., self-treated episodes) and impacts on other QoL domains (e.g., relationships). Therefore, we examined the impact of all aspects of hypoglycaemia on QoL in adults with type 1 diabetes (T1DM).

METHODS

Participants completed an online survey, including assessment of hypoglycaemia-specific QoL (using the 12-item Hypoglycaemia Impact Profile). Mann-Whitney U tests examined differences in hypoglycaemia-specific QoL by hypoglycaemia frequency, severity, and awareness. Hierarchical linear regression examined associations with QoL.

RESULTS

Participants were 1028 adults with T1DM (M ± SD age: 47 ± 15 years; diabetes duration: 27 ± 16 years). Severe and self-treated hypoglycaemia and impaired awareness negatively impacted on overall QoL and several QoL domains, including leisure activities, physical health, ability to keep fit/be active, sleep, emotional well-being, spontaneity, independence, work/studies, and dietary freedom. Diabetes distress was most strongly associated with hypoglycaemia-specific QoL, followed by generic emotional well-being, fear of hypoglycaemia, and confidence in managing hypoglycaemia. Hypoglycaemia frequency and awareness were no longer significantly associated with QoL once psychological factors were considered.

CONCLUSIONS

Hypoglycaemia negatively impacts on several QoL domains. Psychological factors supersede the effect of hypoglycaemia frequency and awareness in accounting for this negative impact.

Glucose Variability Analysis in Two Large-Scale and Real-World Data Sets of Open-Source Automated Insulin Delivery Systems

BACKGROUND

Open-source automated insulin delivery (OS-AID) systems combine commercially available insulin pumps and continuous glucose monitors with open-source algorithms to automate insulin dosing for people with insulin-requiring diabetes. Two data sets (OPEN and the OpenAPS Data Commons) contain anonymized OS-AID user data.

METHODS

We assessed glycemic variability (GV) outcomes in the OPEN data set and characterized it alongside a comparison to the n = 122 version of the OpenAPS Data Commons. Glucose data are analyzed using an unsupervised machine learning algorithm for clustering, and GV metrics are quantified using statistical tests for distribution comparison. Demographic data are also analyzed quantitatively.

RESULTS

The n = 75 OPEN data set contains 36 827 days worth of data. Mean TIR is 82.08% (TOR < 70: 3.66%; TOR > 180: 14.3%). LBGI (P < .05) differs by gender whereas HBGI distributions are similar (P > .05). GV metrics (except TOR < 70, LBGI) show a statistically significant difference (P < .05) between data sets.

CONCLUSIONS

Both the OPEN and OpenAPS Data Commons data sets show TOR < 70, TIR, and TOR > 180 within recommended goals, adding additional evidence of real-world efficacy of OS-AID. Future research should evaluate in more detail potential data set differences and relationships between individual patterns of user behaviors and GV outcomes.

Efficacy and safety of Android artificial pancreas system use at home among adults with type 1 diabetes mellitus in China: protocol of a 26-week, free-living, randomised, open-label, two-arm, two-phase, crossover trial

INTRODUCTION

Do-it-yourself artificial pancreas system (DIY APS) is built using commercially available insulin pump, continuous glucose monitoring (CGM) and an open-source algorithm. Compared with commercial products, DIY systems are affordable, allow personalised settings and provide updated algorithms, making them a more promising therapy for most patients with type 1 diabetes mellitus (T1DM). Many small and self-reported observational studies have found that their real-world use was associated with potential metabolic and psychological benefits. However, rigorous-designed studies are urgently needed to confirm its efficacy and safety.

METHODS AND ANALYSIS

In this 26-week randomised, open-label, two-arm, two-phase, crossover trial, participants aged 18-75 years, with T1DM and glycated haemoglobin (HbA1c) 7-11%, will use AndroidAPS during one 12-week period and sensor-augmented pump during another 12-week period. This study will recruit at least 24 randomised participants. AndroidAPS consists of three components: (1) real-time CGM; (2) insulin pump; (3) AndroidAPS algorithm implemented in Android smartphone. The primary endpoint is time in range (3.9-10.0 mmol/L) derived from CGM. The main secondary endpoints include percentage of sensor glucose values below, within and above target range; mean sensor glucose value; measures of glycaemic variability and centralised HbA1c. Safety endpoints mainly include the frequency of hypoglycaemia events, diabetic ketoacidosis and other serious adverse events.

ETHICS AND DISSEMINATION

This study has been approved by the Ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University. There will be verbal and written information regarding the trial given to each participant. The study will be disseminated through peer-reviewed publications and conference presentations.

OVERALL STATUS

Recruiting.

STUDY START

11 February 2023.

PRIMARY COMPLETION

31 July 2024.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Registry (NCT05726461).

Effect of diabetes technologies on the fear of hypoglycaemia among people living with type 1 diabetes: a systematic review and meta-analysis

Background

Fear of hypoglycaemia (FOH) significantly disrupts the daily management of type 1 diabetes (T1D) and increases the risk of complications. Recent technological advances can improve glucose metrics and reduce hypoglycaemia frequency, yet their impact on FOH is unclear. This systematic review and meta-analysis (SRMA) aimed to synthesize the current literature to understand the impact of diabetes technologies on FOH in T1D.

Methods

In this SRMA, we searched PubMed, Medline, Scopus, and Web of Science from inception up to May 21st, 2023 for studies assessing the effect of using real-time or intermittently scanned continuous glucose monitors (rtCGM or isCGM); insulin pumps (CSII); and their combinations on FOH as the primary outcome, measured using the Hypoglycaemia Fear Survey (HFS; including total, worries [HFS-W], and behaviours [HFS-B] scores), in non-pregnant adults with T1D. Data was extracted by the first and second authors. Results were pooled using a random-effects model based on study design (RCT and non-RCT), with subgroup analysis based on the type of technology, reported change in hypoglycaemia frequency, and duration of use. Risk of bias was evaluated with Cochrane and Joanna Briggs Institute tools. This study is registered with PROSPERO, CRD42021253618.

Findings

A total of 51 studies (n = 8966) were included, 22 of which were RCTs. Studies on rtCGM and CSII reported lower FOH levels with ≥8 weeks of use. Studies on CSII and rtCGM combinations reported lower FOH levels after ≥13 weeks of automated insulin delivery (AID) use or 26 weeks of sensor-augmented pump (SAP) use. The meta-analysis showed an overall lower FOH with technologies, specifically for the HFS-W subscale. The RCT meta-analysis showed lower HFS-W scores with rtCGM use (standard mean difference [95%CI]: -0.14 [-0.23, -0.05], I2 = 0%) and AID (-0.17 [-0.33, -0.01], I2 = 0%). Results from non-RCT studies show that SAP users (-0.33 [-0.38, -0.27], I2 = 0%) and rtCGM users (-0.38 [-0.61, -0.14], I2 = 0%) had lower HFS-W.

Interpretation

We found consistent, yet small to moderate, effects supporting that diabetes technologies (specifically rtCGM, SAP, and AID) may reduce hypoglycaemia-related worries in adults with T1D. Current literature, however, has limitations including discrepancies in baseline characteristics and limited, mainly descriptive, statistical analysis. Thus, future studies should assess FOH as a primary outcome, use validated surveys, and appropriate statistical analysis to evaluate the clinical impacts of technology use beyond just glucose metrics.

Funding

Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation Ltd.

"Empowering Us": A Community-Led Survey of Real-World Perspectives of Adults with Type 1 Diabetes Using Insulin Pumps and Continuous Glucose Monitoring to Manage Their Glucose Levels

OBJECTIVE

To conduct an Australian community-led survey of adults with type 1 diabetes (T1D), identifying priorities for, and barriers to, optimal use of advanced glucose management technologies.

RESEARCH DESIGN AND METHODS

A 30-question online survey of current or past users of insulin pump therapy (IPT), real-time continuous glucose monitoring (RT-CGM), or intermittently scanned CGM (isCGM) explored perceptions regarding device design, access, education, outcomes, and support.

RESULTS

Between November 2021 and January 2022, surveys were completed by 3,380 participants (age [mean±SD] 45±16 years; 62% female; 20±14 years diabetes), with 55%, 82%, and 55% reporting experience with IPT, RT-CGM, and isCGM, respectively. Overall, most considered diabetes technology '(extremely) important' for maintaining target glucose levels (98%) and reducing hypoglycaemia severity and frequency (93%). For most, technology contributed positively to emotional well-being (IPT 89%; RT-CGM 91%; isCGM 87%), which was associated with device effectiveness in maintaining glucose in range, comfort, and convenience. Barriers included affordability (IPT 68%; RT-CGM 81%; isCGM 69%) and insufficient information for informed choices about device suitability (IPT 39%; RT-CGM 41%; isCGM 36%).

CONCLUSIONS

Technology is perceived by adults with T1D as important for managing glycaemia and emotional well-being. Modifiable barriers to use include affordability, and information regarding device suitability.

Open-source automated insulin delivery systems (OS-AIDs) in a pediatric population with type 1 diabetes in a real-life setting: the AWeSoMe study group experience

PURPOSE

The use of open-source automated insulin delivery systems (OS-AIDs), for the management of type 1 diabetes (T1D), has increased over recent years in all age groups. Real-life data has demonstrated the safety and efficacy of these systems, however, studies in the pediatric population remain limited. In this study, we aimed to examine the effect of transition to an OS-AIDs on glycemic parameters, and on several aspects related to quality of life. In addition, we aimed to characterize the socioeconomic position of families who chose this treatment modality, assess their motivations to do so, and evaluate treatment satisfaction.

METHODS

In this multi-center observational real-life study from the AWeSoMe Group, we compared glycemic parameters of 52 individuals with T1D (56% males, mean diabetes duration 4.2 ± 3.9 years), from the last clinic visit prior to OS-AIDs initiation to the most recent clinic visit while using the system. Socioeconomic position (SEP) index was retrieved from the Israel Central Bureau of Statistics. Caregivers completed questionnaires assessing reasons for system initiation and treatment satisfaction.

RESULTS

Mean age at OS-AIDs initiation was 11.2 ± 4 years, range 3.3-20.7 years with a median usage duration of 11.1 months (range 3-45.7). Mean SEP Index was 1.033 ± 0.956 (value range: -2.797 to 2.590). Time in range (TIR) of 70 to 180 mg/dl increased from 69.0 ± 11.9 to 75.5 ± 11.7%, (P < 0.001), and HbA1c decreased from 6.9 ± 0.7 to 6.4 ± 0.6%, (P < 0.001). Time in tight range (TITR) of 70 to 140 mg/dl increased from 49.7 ± 12.9 to 58.8 ± 10.8% (P < 0.001). No episodes of severe hypoglycemia or DKA were reported. Reduction in diabetes burden and sleep quality improvement were the main reasons for OS-AID initiation.

CONCLUSIONS

In our cohort of youth with T1D, the transition to an OS-AID resulted in greater TIR and less severe hypoglycemia regardless of age, diabetes duration or SEP, which was found to be above average. The overall improvement in glycemic parameters in our study population with excellent baseline glycemic control, provides additional evidence of beneficence and efficacy of OS-AIDs in the pediatric population.

Association between early glycemic management and diabetes complications in type 1 diabetes mellitus: A retrospective cohort study

AIMS

To investigate the association between early HbA1c levels near diagnosis and future glycemic management, and analyzed risk factors of complications in people with T1DM.

METHODS

This retrospective cohort study included 201 children and adolescents with T1DM. Patient data including sex, age at diagnosis, duration of disease, HbA1c levels, HbA1c variability during the follow-up period, and diabetes complications and comorbidities were collected.

RESULTS

The mean follow-up period of patients was 16.4 years. HbA1c levels in all three examined time points after diagnosis (first year, second year, and first two years) were significantly associated with recent HbA1c level, and second-year HbA1c was most closely correlated with recent HbA1c level. Elevated second-year HbA1c was a risk factor of diabetic ketoacidosis (DKA) and retinopathy, and increased variability of HbA1c was significantly related to various microvascular complications. When HbA1c is stratified into quartiles, the subjects of each quartile trend to stay within that quartile over the follow-up period.

CONCLUSIONS

Early HbA1c levels were closely associated with recent HbA1c levels and diabetes complications in patients with T1DMs. Strict glucose management after diagnosis and reducing variability of HbA1c may prevent future diabetes complications and comorbidities.

Quality of life and psychological well-being among children and adolescents with diabetes and their caregivers using open-source automated insulin delivery systems: Findings from a multinational survey

BACKGROUND

Open-source automated insulin delivery (AID) systems have shown to be safe and effective in children and adolescents with type 1 diabetes (T1D) in real-world studies. However, there is a lack of evidence on the effect on their caregivers' quality-of-life (QoL) and well-being. The aim of this study was to assess the QoL of caregivers and children and adolescents using open-source AID systems using validated measures.

METHODS

In this cross-sectional online survey we examined the caregiver-reported QoL and well-being of users and non-users. Validated questionnaires assessed general well-being (WHO-5), diabetes-specific QoL (PAID, PedsQL) and sleep quality (PSQI).

RESULTS

168 caregivers from 27 countries completed at least one questionnaire, including 119 caregivers of children using open-source AID and 49 not using them. After inclusion of covariates, all measures but the PAID and one subscale of the PedsQL showed significant between-group differences with AID users reporting higher general (WHO-5: p = 0.003), sleep-related (PSQI: p = 0.001) and diabetes-related QoL (PedsQL: p < 0.05).

CONCLUSIONS

The results show the potential impact of open-source AID on QoL and psychological well-being of caregivers and children and adolescents with T1D, and can therefore help to inform academia, regulators, and policymakers about the psychosocial health implications of open-source AID.

Improved Glycemia and Quality of Life Among Loop Users: Analysis of Real-world Data From a Single Center

BACKGROUND

Despite do-it-yourself automated insulin delivery being an unapproved method of insulin delivery, an increasing number of people with type 1 diabetes (T1D) worldwide are choosing to use Loop, a do-it-yourself automated insulin delivery system.

OBJECTIVE

In this study, we aimed to assess glycemic outcomes, safety, and the perceived impact on quality of life (QOL) in a local Edmonton cohort of known Loop users.

METHODS

An observational study of adults with T1D who used Loop was performed. An assessment of glycemic and safety outcomes, HbA1c, time in range, hospital admissions, and time below range compared users most recent 6 months of Loop use, with their prior regulatory approved insulin delivery method. QOL outcomes were assessed using Insulin Dosing Systems: Perceptions, Ideas, Reflections, and Expectations, diabetes impact, and device satisfaction measures (with maximum scores of 100, 10, and 10, respectively) and semistructured interviews.

RESULTS

The 24 adults with T1D who took part in this study 16 (67%) were female, with a median age of 33 (IQR 28-45) years, median duration of diabetes of 22 (IQR 17-32) years, median pre-Loop HbA1c of 7.9% (IQR 7.6%-8.3%), and a median duration of Loop use of 18 (IQR 12-25) months. During Loop use, the participants had median (IQR) values of 7.1% (6.5%-7.5%), 54 mmol (48-58) for HbA1c and 76.5% (64.6%-81.9%) for time in range, which were a significant improvement from prior therapy (P=.001 and P=.005), with a nonsignificant reduction in time below range; 3.0 to 3.9 mmol/L (P=.17) and <3 mmol/L (P=.53). Overall, 2 episodes of diabetic ketoacidosis occurred in a total of 470 months of Loop use, and no severe hypoglycemia occurred. The positive impact of Loop use on QOL was explored in qualitative analysis and additionally demonstrated through a median Insulin Dosing Systems: Perceptions, Ideas, Reflections, and Expectations score of 86 (IQR 79-95), a median diabetes impact score of 2.8 (IQR 2.1-3.9), and a median device satisfaction score of 9 (IQR 8.2-9.4).

CONCLUSIONS

This local cohort of people with T1D demonstrated a beneficial effect of Loop use on both glycemic control and QOL, with no safety concerns being highlighted.

Practical Guidance on Open Source and Commercial Automated Insulin Delivery Systems: A Guide for Healthcare Professionals Supporting People with Insulin-Requiring Diabetes

As increasing numbers of people with insulin-managed diabetes use automated insulin delivery (AID) systems or seek such technologies, healthcare providers are faced with a steep learning curve. Healthcare providers need to understand how to support these technologies to help inform shared decision making, discussing available options, implementing them in the clinical setting, and guiding users in special situations. At the same time, there is a growing diversity of commercial and open source automated insulin delivery systems that are evolving at a rapid pace. This practical guide seeks to provide a conversational framework for healthcare providers to first understand and then jointly assess AID system options with users and caregivers. Using this framework will help HCPs in learning how to evaluate potential new commercial or open source AID systems, while also providing a guide for conversations to help HCPs to assess the readiness and understanding of users for AID systems. The choice of an AID system is not as simple as whether the system is open source or commercially developed, and indeed there are multiple criteria to assess when choosing an AID system. Most importantly, the choices and preferences of the person living with diabetes should be at the center of any decision around the ideal automated insulin delivery system or any other diabetes technology. This framework highlights issues with AID use that may lead to burnout or perceived failures or may otherwise cause users to abandon the use of AID. It discusses the troubleshooting of basic AID system operation and discusses more advanced topics regarding how to maximize the time spent on AID systems, including how to optimize settings and behaviors for the best possible outcomes with AID technology for people with insulin-requiring diabetes. This practical approach article demonstrates how healthcare providers will benefit from assessing and better understanding all available AID system options to enable them to best support each individual.

Barriers to Uptake of Open-Source Automated Insulin Delivery Systems: Analysis of Socioeconomic Factors and Perceived Challenges of Caregivers of Children and Adolescents With Type 1 Diabetes From the OPEN Survey

Background

As a treatment option for people living with diabetes, automated insulin delivery (AID) systems are becoming increasingly popular. The #WeAreNotWaiting community plays a crucial role in the provision and distribution of open-source AID technology. However, while a large percentage of children were early adopters of open-source AID, there are regional differences in adoption, which has prompted an investigation into the barriers perceived by caregivers of children with diabetes to creating open-source systems.

Methods

This is a retrospective, cross-sectional and multinational study conducted with caregivers of children and adolescents with diabetes, distributed across the online #WeAreNotWaiting online peer-support groups. Participants—specifically caregivers of children not using AID—responded to a web-based questionnaire concerning their perceived barriers to building and maintaining an open-source AID system.

Results

56 caregivers of children with diabetes, who were not using open-source AID at the time of data collection responded to the questionnaire. Respondents indicated that their major perceived barriers to building an open-source AID system were their limited technical skills (50%), a lack of support by medical professionals (39%), and therefore the concern with not being able to maintain an AID system (43%). However, barriers relating to confidence in open-source technologies/unapproved products and fear of digital technology taking control of diabetes were not perceived as significant enough to prevent non-users from initiating the use of an open-source AID system.

Conclusions

The results of this study elucidate some of the perceived barriers to uptake of open-source AID experienced by caregivers of children with diabetes. Reducing these barriers may improve the uptake of open-source AID technology for children and adolescents with diabetes. With the continuous development and wider dissemination of educational resources and guidance—for both aspiring users and their healthcare professionals—the adoption of open-source AID systems could be improved.

Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems

Open-source automated insulin delivery (AID) technologies use the latest continuous glucose monitors (CGM), insulin pumps, and algorithms to automate insulin delivery for effective diabetes management. Early community-wide adoption of open-source AID, such as OpenAPS, has motivated clinical and research communities to understand and evaluate glucose-related outcomes of such user-driven innovation. Initial OpenAPS studies include retrospective studies assessing high-level outcomes of average glucose levels and HbA1c, without in-depth analysis of glucose variability (GV). The OpenAPS Data Commons dataset, donated to by open-source AID users with insulin-requiring diabetes, is the largest freely available diabetes-related dataset with over 46,070 days’ worth of data and over 10 million CGM data points, alongside insulin dosing and algorithmic decision data. This paper first reviews the development toward the latest open-source AID and the performance of clinically approved GV metrics. We evaluate the GV outcomes using large-scale data analytics for the n = 122 version of the OpenAPS Data Commons. We describe the data cleaning processes, methods for measuring GV, and the results of data analysis based on individual self-reported demographics. Furthermore, we highlight the lessons learned from the GV outcomes and the analysis of a rich and complex diabetes dataset and additional research questions that emerged from this work to guide future research. This paper affirms previous studies’ findings of the efficacy of open-source AID.

Errors of commission or omission: The net risk safety analysis conversation we should be having around automated insulin delivery systems

The question of safety often arises when discussing automated insulin delivery systems, but discussion of safety is often anchored on a comparison to the risk to a person without diabetes, overlooking the risks of living with insulin-requiring diabetes. We should use a net risk safety perspective for evaluating diabetes technology that takes into account the ongoing risks of insulin management for people living with diabetes.

Real-world evidence on clinical outcomes of people with type 1 diabetes using open-source and commercial automated insulin dosing systems: A systematic review

AIMS

Several commercial and open-source automated insulin dosing (AID) systems have recently been developed and are now used by an increasing number of people with diabetes (PwD). This systematic review explored the current status of real-world evidence on the latest available AID systems in helping to understand their safety and effectiveness.

METHODS

A systematic review of real-world studies on the effect of commercial and open-source AID system use on clinical outcomes was conducted employing a devised protocol (PROSPERO ID 257354).

RESULTS

Of 441 initially identified studies, 21 published 2018-2021 were included: 12 for Medtronic 670G; one for Tandem Control-IQ; one for Diabeloop DBLG1; two for AndroidAPS; one for OpenAPS; one for Loop; three comparing various types of AID systems. These studies found that several types of AID systems improve Time-in-Range and haemoglobin A_1c (HbA_1c ) with minimal concerns around severe hypoglycaemia. These improvements were observed in open-source and commercially developed AID systems alike.

CONCLUSIONS

Commercially developed and open-source AID systems represent effective and safe treatment options for PwD of several age groups and genders. Alongside evidence from randomized clinical trials, real-world studies on AID systems and their effects on glycaemic outcomes are a helpful method for evaluating their safety and effectiveness.

Association of British Clinical Diabetologists, Diabetes Technology Network UK and Association of Children's Diabetes Clinicians Survey of UK Healthcare Professional Attitudes Towards Open-Source Automated Insulin Delivery Systems

INTRODUCTION

Automated insulin delivery (AID) systems can enable improved glycaemic outcomes with reduced mental burden. Open-source AID (OS-AID) systems overcome some of the developmental and access barriers enabling a wider use of these systems. Limited data are available on healthcare professional (HCP) opinions and current practice regarding these systems. The aim of this survey was to gain insight into HCP perceptions and practices around OS-AID.

METHODS

This survey was developed collaboratively with OS-AID users and distributed to adult and children's teams, using an online survey tool. Results were received between February and April 2019. Responses were assessed using simple descriptive statistics with analyses stratified by respondent characteristics.

RESULTS

317 responses were obtained from a range of HCPs in both adult and paediatric services. Key results include: HCP perception of OS-AID as "risky in the wrong hands" (43%); 91% felt uncomfortable initiating discussions around OS-AID because of lack of regulation (67%) and/or their own lack of knowledge (63%). Half of HCPs (47%) reported that they would choose OS-AID if they themselves had type 1 diabetes.

CONCLUSIONS

HCPs are generally supportive of OS-AID users but many feel uncomfortable with the technicalities of the systems given the lack of approval. Knowledge around the use of these systems was limited. Re-assessment of HCP perceptions should be performed in the future given the evolving landscape of diabetes technology, recent consensus statements and emerging ethical and legal perspectives.

Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems

BACKGROUND

Numerical simulations, also referred to as in silico trials, are nowadays the first step toward approval of new artificial pancreas (AP) systems. One suitable tool to run such simulations is the UVA/Padova Type 1 Diabetes Metabolic Simulator (T1DMS). It was used by Toffanin et al. to provide data about safety and efficacy of AndroidAPS, one of the most wide-spread do-it-yourself AP systems. However, the setup suffered from slow simulation speed. The objective of this work is to speed up simulation by implementing the algorithm directly in MATLAB^®/Simulink^®.

METHOD

Firstly, AndroidAPS is re-implemented in MATLAB^® and verified. Then, the function is incorporated into T1DMS. To evaluate the new setup, a scenario covering 2 days in real time is run for 30 virtual patients. The results are compared to those presented in the literature.

RESULTS

Unit tests and integration tests proved the equivalence of the new implementation and the original AndroidAPS code. Simulation of the scenario required approximately 15 minutes, corresponding to a speed-up factor of roughly 1000 with respect to real time. The results closely resemble those presented by Toffanin et al. Discrepancies were to be expected because a different virtual population was considered. Also, some parameters could not be extracted from and harmonized with the original setup.

CONCLUSIONS

The new implementation facilitates extensive in silico trials of AndroidAPS due to the significant reduction of runtime. This provides a cheap and fast means to test new versions of the algorithm before they are shared with the community.

Technological Developments and Quality of Life in Type 1 Diabetes Mellitus Patients: A Review of the Modern Insulin Analogues, Continuous Glucose Monitoring and Insulin Pump Therapy

BACKGROUND

Type 1 Diabetes Mellitus (T1DM) is a chronic autoimmune disease, which is characterized by an increased prevalence worldwide, which, in fact, tends to take extensive dimensions. The recent rapid development of science and technology has significantly contributed to the improvement of the management of type 1 diabetes mellitus, both in achieving the required euglycaemic regulation and reducing the psychological burden associated with the disease, consequently improving the quality of life of the patients with type 1 diabetes mellitus.

METHODS

A literature review from 2010, related to the contribution of the modern insulin analogues, continuous glucose monitoring and the insulin pump, was performed using Scopus, ScienceDirect and PubMed databases.

RESULTS

Studies included in the review support a direct and indirect association of technological innovations with the quality of life. The use of type 1 diabetes mellitus technology was negatively associated with the frequency of the hypoglycaemias and the value of the glycosylated hemoglobin, while at the same time, the development and use of the related technology were highly associated with an improvement in the quality of life.

CONCLUSION

Patients' quality of life is an indicator of the management of type 1 diabetes mellitus, and it is just as important as glycaemic regulation. Through this review, it was concluded that a better quality of life of T1DM patients was associated with the improvement of glycosylated hemoglobin and hypoglycemic episodes.

Open-source automated insulin delivery: international consensus statement and practical guidance for health-care professionals

Open-source automated insulin delivery systems, commonly referred to as do-it-yourself automated insulin delivery systems, are examples of user-driven innovations that were co-created and supported by an online community who were directly affected by diabetes. Their uptake continues to increase globally, with current estimates suggesting several thousand active users worldwide. Real-world user-driven evidence is growing and provides insights into safety and effectiveness of these systems. The aim of this consensus statement is two-fold. Firstly, it provides a review of the current evidence, description of the technologies, and discusses the ethics and legal considerations for these systems from an international perspective. Secondly, it provides a much-needed international health-care consensus supporting the implementation of open-source systems in clinical settings, with detailed clinical guidance. This consensus also provides important recommendations for key stakeholders that are involved in diabetes technologies, including developers, regulators, and industry, and provides medico-legal and ethical support for patient-driven, open-source innovations.

How It Started, How It Is Going: The Future of Artificial Pancreas Systems (Automated Insulin Delivery Systems)

Originally, the future of automated insulin delivery (AID) systems, or artificial pancreas systems (APS), was having them at all, in any form. We've learned in the last half dozen years that the future of all artificial pancreas systems holds higher time in range, less work required to manage automated insulin delivery systems to improve quality of life, and the ability to input critical information back into the system itself. The data and user experience stories make it clear: APS works. APS are an improvement over other diabetes therapy methods when they are made available, accessible, and affordable. Understanding the unmet expectations of current users of first generation APS technology may also aid in the development of improved technology and user experiences for the future of APS.

Glycemic control in children and teenagers with type 1 diabetes around lockdown for COVID-19: A continuous glucose monitoring-based observational study

AIMS/INTRODUCTION

The coronavirus disease 2019 (COVID-19) pandemic urged authorities to impose rigorous quarantines and brought considerable changes to people's lifestyles. The impact of these changes on glycemic control has remained unclear, especially the long-term effect. We aimed to investigate the impact of COVID-19 lockdown on glycemic control in children and adolescents with type 1 diabetes.

MATERIALS AND METHODS

This observational study enrolled children with type 1 diabetes using continuous glucose monitoring. Continuous glucose monitoring data were extracted from the cloud-based platform before, during and after lockdown. Demographics and lifestyle change-related information were collected from the database or questionnaires. We compared these data before, during and after lockdown.

RESULTS

A total of 43 children with type 1 diabetes were recruited (20 girls; mean age 7.45 years; median diabetes duration 1.05 years). We collected 41,784 h of continuous glucose monitoring data. Although time in range (3.9-10.0 mmol/L) was similar before, during and after lockdown, the median time below range <3.9 mmol/L decreased from 3.70% (interquartile range [IQR] 2.25-9.53%) before lockdown to 2.91% (IQR 1.43-5.95%) during lockdown, but reversed to 4.95% (IQR 2.11-9.42%) after lockdown (P = 0.004). Time below range <3.0 mmol/L was 0.59% (IQR 0.14-2.21%), 0.38% (IQR 0.05-1.35%) and 0.82% (IQR 0.22-1.69%), respectively (P = 0.008). The amelioration of hypoglycemia during lockdown was more prominent among those who had less time spent <3.9 mmol/L at baseline. During lockdown, individuals reduced their physical activity, received longer sleep duration and spent more time on diabetes management. In addition, they attended outpatient clinics less and turned to telemedicine more frequently.

CONCLUSION

Glycemic control did not deteriorate in children and teenagers with type 1 diabetes around the COVID-19 pandemic. Hypoglycemia declined during lockdown, but reversed after lockdown, and the changes related to lifestyle might not provide a long-term effect.

Good enough? Parental decisions to use DIY looping technology to manage type 1 diabetes in children

People are using innovative internet of things technologies to gain individualised management of their type 1 diabetes. The #WeAreNotWaiting movement supports them to build their own hybrid closed loop systems and access their real time blood sugar data via any web connected device. A small number of parents in Australia use such DIY looping systems to manage their child's type 1 diabetes, but these systems have not been approved by the Therapeutic Goods Administration in Australia, creating ethical dilemmas for clinicians about how to respond to the use of medical devices that are not registered on the Australian Register of Therapeutic Goods. This article considers whether the use of DIY looping is in the best interests of the child and, if not, whether intervention in parental decision making is justified to prevent harm to the child. It addresses the ongoing duty of healthcare professionals to provide care to children who are 'looping.' Reference is made to findings from a study, Personalised Closed Loop Systems for Childhood Diabetes, to illustrate stakeholders' perceptions of benefits and harms of DIY looping systems. I conclude that the decision of parents to use DIY looping technology could be considered to be in a child's best interests, broadly defined, and falls within the Zone of Parental Discretion, however healthcare practitioners who support parents may have professional concerns in doing so.

Parents' experiences on the combined use of continuous subcutaneous insulin infusion and real-time continuous glucose monitoring to manage Type 1 diabetes in their children: A systematic review and meta-synthesis of qualitative studies

AIM

To explore the experiences and perspectives of the combined use of continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) on parents of children with TIDM on their daily life.

DESIGN

A systematic review and meta-synthesis of qualitative studies.

METHODS

A systematic literature search of English studies published in seven databases between 2006-2021: CINAHL, MEDLINE, EMBASE, PubMed, PsycINFO, Cochrane Library and Scopus. All included studies underwent the process of thematic interpretive integration by the author team.

RESULTS

Nine studies met the inclusion criteria. Six derived themes were generated which contained interacting with devices, interacting with glycaemic information, improving quality of life for parents of children with T1DM, burden of living with CSII therapy and CGM, impact on the parent-child relationship, requirement and expectation to advanced diabetes technology. Advanced diabetes technologies affect physical, emotional and relationship between the daily life of parents and their children with T1DM.

DIY artificial pancreas: A narrative of the first patient and the physicians' experiences from India

BACKGROUND AIMS

Frustrated with the slow-pace of innovations in diabetes technologies, the type 1 diabetes community have started closing the loop by themselves to automate insulin delivery. While the regulatory and ethical concerns over the systems are still high, these have contributed to enhanced glycemic control characterized by improved estimated HbA1c and time-in-range above 90% as for many users. Our objective is to provide the real-world experience of the first successful patient from India on the Do-It-Yourself Artificial Pancreas (DIYAP) and the perspective of her physicians.

METHODS

A narrative recounting of a personal experience on DIYAP. The patient completed a Hypoglycemia Fear Survey II and Diabetes Quality of Life instrument before and after looping.

RESULTS

The patient emphasized the personal/social benefits and the concerns of using the system. Looping has produced a clinically meaningful difference in the quality of life, better sleep patterns, and reduced the disease management burden. We also highlighted the relevant perspectives of the physicians to give deeper insights into the aspect.

CONCLUSION

The patient highlighted better time-in-range, negligible time spent in hypoglycemia, and superior Quality of Life. Globally, more and more patients are adopting this technology; therefore, real-life patient stories will enlighten the medical community.

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

Background

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

Methods

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