Pre-school and school-aged children benefit from the switch from a sensor-augmented pump to an AndroidAPS hybrid closed loop: A retrospective analysis

A comparison of the usage of an open-source automated insulin delivery system and the MiniMed™ 780 G system in children and adolescents with type 1 diabetes in real-world settings: the AWeSoMe study group

PURPOSE

In recent years there has been a noticeable increase in the use of advanced hybrid closed-loop systems (AHCLs) for managing type 1 diabetes (T1D) among youth. However, there is a lack of comparison between the open-source automated insulin delivery (AID) system and the MiniMed™ 780 G system (780 G).

METHODS

In this multi-center study, we retrospectively compared selected glycemic ranges of 26 individuals who used open-source AID and 20 individuals who used 780 G (age 11.3 years [IQR 9.3, 12.9] and 13.4 years [IQR 10.9, 16.5], respectively, p = 0.069) from system initiation to the most recent visit.

RESULTS

At baseline, the median HbA1c was significantly lower and the time below range (TBR)<54mg/dL was significantly higher in the open-source AID group compared to the 780 G group (6.8% [IQR 6.4, 7.1] vs. 7.4% [IQR 6.9, 8.6], p = 0.006 and (1.0% [IQR 0.5, 2.8] vs. 0.0% [0.0, 1.0], p = 0.014), respectively; the median time in range (TIR70-180mg/dL) was similar (p = 0.068). After a median duration of 10.9 months on AHCLs the reduction of HbA1c was similar ( ~ 0.3%). The time spent in the hypoglycemic ranges was longer among users of the open-source AID compared to 780 G (TBR54-70mg/dL 4.2% [IQR 2.6, 7.3] vs. 2.0% [1.0, 4.0], p = 0.005) and TBR<54mg/dL 1.1% [IQR 0.4, 2.3] vs. 0.0 [0.0, 1.0], p = 0.001).

CONCLUSIONS

Both AHCLs similarly improved HbA1c and TIR70-180mg/dL. The open-source AID youth had better glycemic control but spent longer time in the hypoglycemic range. These findings must be considered when choosing the use of AHCL technologies.

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.

Muscle-to-fat ratio in children and adolescents with type 1 diabetes in predicting glycaemic control and partial clinical remission

BACKGROUND

Advances in treatment could mitigate the expected adverse changes in the body composition of children and adolescents with type 1 diabetes (T1D).

OBJECTIVES

To examine the evolution of weight status and body composition and their association with glycaemic control and partial clinical remission in youth with T1D.

METHODS

Ninety-nine participants with T1D (median age 9.5 years [interquartile range 7.3, 12.9], 59.6% boys) were longitudinally followed for 3 years since diagnosis. Data at seven pre-determined time points were extracted from medical files. Outcome measures included body mass index (BMI) z-scores, muscle-to-fat ratio (MFR) z-scores, haemoglobin A1c (HbA1c) levels, continuous glucose monitoring metrics, and insulin dose-adjusted HbA1c (IDAA1c) levels.

RESULTS

The BMI z-scores increased significantly (p < 0.001) for both sexes, with no significant change in MFR z-scores over time. The girls had higher BMI z-scores (p < 0.001) and lower MFR z-scores than the boys (p = 0.016). The mean HbA1c levels decreased during the first month and at 3 months since diagnosis (p < 0.001), then plateaued and achieved a median overall HbA1c of 7.1% for the entire cohort. At 12 months, 37 participants (37.6%) were in partial clinical remission, as evidenced by IDAA1c ≤ 9. The odds of partial clinical remission at 2 years increased by 2.1-fold for each standard deviation increase in the MFR z-score (p < 0.001). Higher MFR z-scores were associated with better metabolic control.

CONCLUSIONS

Integration of body composition assessments could mitigate adverse body changes in paediatric patients with T1D.

Approach to the Hypoglycemic Patient

Hypoglycemia is commonly encountered in the emergency department. Patients can present with a myriad of symptoms and its presentation can mimic other more serious diagnoses. Despite the relative ease of its management, clinicians often miss the diagnosis or mismanage it even when discovered. Glucose is an important energy source for the brain and failing to recognize hypoglycemia or mismanaging it can lead to permanent neurologic disability or death. Although it is important to replenish glucose in a rapid fashion, it is equally important to discover and manage the underlying etiology to prevent further episodes of hypoglycemia.

Are all HCL systems the same? long term outcomes of three HCL systems in children with type 1 diabetes: real-life registry-based study

Objective

To compare parameters of glycemic control among three types of hybrid closed loop (HCL) systems in children with T1D (CwD) using population-wide data from the national pediatric diabetes registry ČENDA.

Methods

CwD aged <19 years treated with Medtronic MiniMed 780G (780G), Tandem t:slim X2 (Control-IQ) or do-it-yourself AndroidAPS (AAPS) systems for >12 months and monitored by CGM >70% of the time were included. HbA1c, times in glycemic ranges, and Glycemia Risk Index (GRI) were used for cross-sectional comparison between the HCL systems.

Results

Data from 512 CwD were analyzed. 780G, Control-IQ and AAPS were used by 217 (42.4%), 211 (41.2%), and 84 (16.4%) CwD, respectively. The lowest HbA1c value was observed in the AAPS group (44 mmol/mol; IQR 8.0, p<0.0001 vs any other group), followed by Control-IQ and 780G groups (48 (IQR 11) and 52 (IQR 10) mmol/mol, respectively). All of the systems met the recommended criteria for time in range (78% in AAPS, 76% in 780G, and 75% in Control-IQ users). CwD using AAPS spent significantly more time in hypoglycemia (5% vs 2% in 780G and 3% in Control-IQ) and scored the highest GRI (32, IQR 17). The lowest GRI (27, IQR 15) was seen in 780G users.

Conclusion

Although all HCL systems proved effective in maintaining recommended long-term glycemic control, we observed differences that illustrate strengths and weaknesses of particular systems. Our findings could help in individualizing the choice of HCL systems.

Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review

In people with type 1 diabetes, Automated Insulin Delivery (AID) systems adjust insulin delivery in response to sensor glucose data and consist of three components: an insulin pump, a continuous glucose sensor, and an algorithm that determines insulin delivery. To date, all the available AID systems require users to announce carbohydrate intake and deliver meal boluses, as well as respond to system alarms. The use of AID devices both initially and over time may be influenced by a variety of psychological factors. Analysis of patient-related outcomes should be taken into account, while recruiting applicants for the systems who are motivated and have realistic expectations in order to prevent AID dropout. We report an up-to-date summary of the available measures and semi-structured interview content to assess AID expectations, acceptance, and satisfaction using the AID systems. In conclusion, we suggest, before and after starting using AID systems, performing a specific evaluation of the related psychological implications, using validated measures and semi-structured interviews, that allows diabetes care providers to tailor their education approach to the factors that concern the patient at that time; they can teach problem-solving skills and other behavioral strategies to support sustained use of the AID system.

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.

Glycemic Control by Treatment Modalities: National Registry-Based Population Data in Children and Adolescents with Type 1 Diabetes

INTRODUCTION

The aim of the study was to assess the differences in key parameters of type 1 diabetes (T1D) control associated with treatment and monitoring modalities including newly introduced hybrid closed-loop (HCL) algorithm in children and adolescents with T1D (CwD) using the data from the population-wide pediatric diabetes registry ČENDA.

METHODS

CwD younger than 19 years with T1D duration >1 year were included and divided according to the treatment modality and type of CGM used: multiple daily injection (MDI), insulin pump without (CSII) and with HCL function, intermittently scanned continuous glucose monitoring (isCGM), real-time CGM (rtCGM), and intermittent or no CGM (noCGM). HbA1c, times in glycemic ranges, and glucose risk index (GRI) were compared between the groups.

RESULTS

Data of a total of 3,251 children (mean age 13.4 ± 3.8 years) were analyzed. 2,187 (67.3%) were treated with MDI, 1,064 (32.7%) with insulin pump, 585/1,064 (55%) with HCL. The HCL users achieved the highest median TIR 75.4% (IQR 6.3) and lowest GRI 29.1 (7.8), both p < 0.001 compared to other groups, followed by MDI rtCGM and CSII groups with TIR 68.8% (IQR 9.0) and 69.0% (7.5), GRI 38.8 (12.5) and 40.1 (8.5), respectively (nonsignificant to each other). These three groups did not significantly differ in their HbA1c medians (51.8 [IQR 4.5], 50.7 [4.5], and 52.7 [5.7] mmol/mol, respectively). NoCGM groups had the highest HbA1c and GRI and lowest TIR regardless of the treatment modality.

CONCLUSION

This population-based study shows that the HCL technology is superior to other treatment modalities in CGM-derived parameters and should be considered as a treatment of choice in all CwD fulfilling the indication criteria.

First Use of Open-Source Automated Insulin Delivery AndroidAPS in Full Closed-Loop Scenario; Pancreas4ALL Randomized Pilot Study

Objective: We evaluated the safety and feasibility of open-source automated insulin delivery AndroidAPS in adolescents and young adults with type 1 diabetes (T1D) and compared its efficacy in three different scenarios: hybrid closed loop (HCL) with meal boluses, meal announcement only (MA), and full closed loop (FCL). Research Design and Methods: In an open-label, prospective, randomized crossover trial (clinicaltrials.gov NCT04835350), 16 adolescents with T1D (10 females) with mean age of 17 years (range 15-20), glycated hemoglobin 56 mmol/mol (range 43-75), and mean duration of diabetes 5.9 years (9-15) underwent three distinct 3-day periods of camp living, comparing the above-mentioned scenarios of AndroidAPS. We used modified and locked version of AndroidAPS 3.1.03, which was called Pancreas4ALL for study purposes. The order of MA and FCL periods was assigned randomly. The primary endpoints were feasibility and safety of the system represented by percentage of time of glucose control by the system and time in hypoglycemia below 3 mmol/L. Results: The glycemia was controlled by the system 95% time of the study and the proportion of time below 3 mmol/L did not exceed 1% over the whole study period (0.72%). The HCL scenario reached significantly higher percentage of time below 3 mmol/L (HCL 1.05% vs. MA 0.0% vs. FCL 0.0%; P = 0.05) compared to other scenarios. No difference was observed among the scenarios in the percentage of time between 3.9 and 10 mmol/L (HCL 83.3% vs. MA 79.85% vs. FCL 81.03%, P = 0.58) corresponding to mean glycemia (HCL 6.65 mmol/L vs. MA 7.34 mmol/L vs. FCL 7.05 mmol/L, P = 0.28). No difference was observed in the mean daily dose of insulin or in the daily carbohydrate intake. No serious adverse event occurred during the study period. Conclusions: Our pilot study showed that FCL might be a realistic mode of treatment for people with T1D.

Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice

The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.

Barriers to uptake of Open-Source automated insulin delivery Systems: Analysis of socioeconomic factors and perceived challenges of adults with type 1 diabetes from the OPEN survey

AIMS

Social and technical trends are empowering people with diabetes to co-create or self-develop medical devices and treatments to address their unmet healthcare needs, for example, open-source automated insulin delivery (AID) systems. This study aims to investigate the perceived barriers towards adoption and maintaining of open-source AID systems.

METHODS

This is a multinational study based on a cross-sectional, retrospective web-based survey of non-users of open-source AID. Participants (n = 129) with type 1 diabetes from 31 countries were recruited online to elicit their perceived barriers towards building and maintaining of an open-source AID system.

RESULTS

Sourcing the necessary components, lack of confidence in one's own technology knowledge and skills, perceived time and energy required to build a system, and fear of losing healthcare provider support appear to be major barriers towards the uptake of open-source AID.

CONCLUSIONS

This study identified a range of structural and individual-level barriers to uptake of open-source AID. Some of these individual-level barriers may be overcome over time through the peer support of the DIY online community as well as greater acceptance of open-source innovation among healthcare professionals. The findings have important implications for understanding the possible wider diffusion of open-source diabetes technology solutions in the future.

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.

DKA Prevention and Insulin Pumps: Lessons Learned From a Large Pediatric Pump Practice

PURPOSE

This purpose of the study was to describe recent diabetic ketoacidosis (DKA) incidence data in youth with type 1 diabetes using insulin pumps and the impact of continuous glucose monitors (CGMs) on DKA rates.

METHODS

DKA data were obtained through a retrospective chart review of insulin pump users (ages <26 years) between December 2019 and June 2021 in an academic pediatric endocrinology practice where 68% of patients were pump users.

RESULTS

Among 591 pump patients, 28 events occurred (3.16 events per 100 patient-years). Mean age was 13.6±3.4 years; 85.7% ranged from 12 to 19 years. Mean A1C was 10.2±2.3%, diabetes duration was 6.1±4.0 years, and 57.1% used CGM. Admission pH levels ranged between 7.0 and 7.31, with 28.6% of events classified as "moderate" and 46.4% "severe." There was no significant difference in the DKA severity between those who wore a CGM and those who did not (ie, pH, serum bicarbonate, mentation alteration, length of stay, intensive care unit admission, and hospital admission). DKA events were attributed to concurrent illness (10.7%), insulin omission (14.3%), pump site failure (57.1%), or other pump malfunctions (14.3%).

CONCLUSION

DKA events in pump-treated patients were relatively uncommon; most episodes occurred in adolescents with higher A1C levels, and notably, most events could have been avoided if users followed standard troubleshooting guidelines. Thus, DKA prevention education should be reinforced at each encounter, particularly for teens with higher A1C levels. Moreover, more than 50% of those with DKA episodes wore a CGM, suggesting that pump users using CGM require frequent reinforcement of this education and that the development of such educational materials is critical.

A scoping review of Do-It-Yourself Automated Insulin Delivery system (DIY AID) use in people with type 1 diabetes

Introduction

User designed Automated Insulin Delivery systems (AID), termed Do-It-Yourself (DIY) AID include; AndroidAPS, OpenAPS and Loop. These unregulated systems provide challenges for healthcare providers worldwide, with potential legal and ethical barriers to supporting their use. We performed a scoping review of the currently available literature surrounding DIY AID systems, specifically to highlight the evidence available to facilitate healthcare providers to support persons with diabetes who may benefit from DIY AID.

Methods

Studies relating to DIY AID systems were searched in Embase, Medline, Web of Science, Scopus, Proquest and Cochrane library until 31^st December 2021. Publications were screened through title and abstract to identify study type and AID system type described. A thematic synthesis methodology was used for analysis of studies of DIY AID use due to the heterogeneity in study designs (case reports, qualitative, cross-sectional and cohort studies), with similarity in outcome themes.

Results

Following implementation of the search strategy, 38 relevant full texts were identified; comprising 12 case reports, 9 qualitative studies and 17 cohort studies, and data was also available from 24 relevant conference abstracts. No randomized studies were identified. Common themes were identified in the outcomes across the studies; glycemic variability, safety, quality of life, healthcare provider attitudes and social media.

Conclusion

There is extensive real-world data, but a lack of randomized control trial evidence supporting DIY AID system use, due to the user-driven, unregulated nature of these systems. Healthcare providers report a lack of understanding surrounding, and confidence in supporting, DIY AID despite impressive observational and user self-reported improvements in glycemic variability, without any reported safety compromises.

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.

Very low birth weight newborn with diabetes mellitus due to pancreas agenesis managed with insulin pump reservoir filled with undiluted insulin: 16-month follow-up

BACKGROUND

When very low doses of insulin are used insulin dilution, a procedure prone to errors, is recommended.

CASE PRESENTATION

We managed a neonate with pancreas agenesis with insulin pump therapy from the first days of life to 16 months of age without insulin dilution. Predictive low glucose suspend mode first and then closed loop control were used. No episodes of severe hypoglycemia were observed.

CONCLUSIONS

Though limited to a single patient with pancreas agenesis we believe that the use of pump should be warranted in patients with permanent neonatal diabetes mellitus and intestinal malabsorption, even with undiluted insulin.

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.

Emotional and Physical Health Impact in Children and Adolescents and their Caregivers Using Open-Source Automated Insulin Delivery: Qualitative Analysis of Lived Experiences. (Preprint)

Background

Given the limitations in the access and license status of commercially developed automated insulin delivery (AID) systems, open-source AID systems are becoming increasingly popular among people with diabetes, including children and adolescents.

Objective

This study aimed to investigate the lived experiences and physical and emotional health implications of children and their caregivers following the initiation of open-source AID, their perceived challenges, and sources of support, which have not been explored in the existing literature.

Methods

Data were collected through 2 sets of open-ended questions from a web-based multinational survey of 60 families from 16 countries. The narratives were thematically analyzed, and a coding framework was identified through iterative alignment.

Results

A range of emotions and improvements in quality of life and physical health were reported, as open-source AID enabled families to shift their focus away from diabetes therapy. Caregivers were less worried about hypoglycemia at night and outside their family homes, leading to increased autonomy for the child. Simultaneously, the glycemic outcomes and sleep quality of both the children and caregivers improved. Nonetheless, the acquisition of suitable hardware and technical setup could be challenging. The #WeAreNotWaiting community was the primary source of practical and emotional support.

Conclusions

Our findings show the benefits and transformative impact of open-source AID and peer support on children with diabetes and their caregivers and families, where commercial AID systems are not available or suitable. Further efforts are required to improve the effectiveness and usability and facilitate access for children with diabetes, worldwide, to benefit from this innovative treatment.

International Registered Report Identifier (IRRID)

RR2-10.2196/15368

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.

An In Silico Head-to-Head Comparison of the Do-It-Yourself Artificial Pancreas Loop and Bio-Inspired Artificial Pancreas Control Algorithms

BACKGROUND

User-developed automated insulin delivery systems, also referred to as do-it-yourself artificial pancreas systems (DIY APS), are in use by people living with type 1 diabetes. In this work, we evaluate, in silico, the DIY APS Loop control algorithm and compare it head-to-head with the bio-inspired artificial pancreas (BiAP) controller for which clinical data are available.

METHODS

The Python version of the Loop control algorithm called PyLoopKit was employed for evaluation purposes. A Python-MATLAB interface was created to integrate PyLoopKit with the UVa-Padova simulator. Two configurations of BiAP (non-adaptive and adaptive) were evaluated. In addition, the Tandem Basal-IQ predictive low-glucose suspend was used as a baseline algorithm. Two scenarios with different levels of variability were used to challenge the algorithms on the adult (n = 10) and adolescent (n = 10) virtual cohorts of the simulator.

RESULTS

Both BiAP and Loop improve, or maintain, glycemic control when compared with Basal-IQ. Under the scenario with lower variability, BiAP and Loop perform relatively similarly. However, BiAP, and in particular its adaptive configuration, outperformed Loop in the scenario with higher variability by increasing the percentage time in glucose target range 70-180 mg/dL (BiAP-Adaptive vs Loop vs Basal-IQ) (adults: 89.9% ± 3.2%* vs 79.5% ± 5.3%* vs 67.9% ± 8.3%; adolescents: 74.6 ± 9.5%* vs 53.0% ± 7.7% vs 55.4% ± 12.0%, where * indicates the significance of P < .05 calculated in sequential order) while maintaining the percentage time below range (adults: 0.89% ± 0.37% vs 1.72% ± 1.26% vs 3.41 ± 1.92%; adolescents: 2.87% ± 2.77% vs 4.90% ± 1.92% vs 4.17% ± 2.74%).

CONCLUSIONS

Both Loop and BiAP algorithms are safe and improve glycemic control when compared, in silico, with Basal-IQ. However, BiAP appears significantly more robust to real-world challenges by outperforming Loop and Basal-IQ in the more challenging scenario.

Empfehlungen zur Diabetes-Behandlung mit automatischen Insulin-Dosierungssystemen

Das Prinzip der automatischen Insulindosierung, kurz „AID“ genannt, zeigt in Zulassungsstudien und Real-World-Erfahrungen ausgezeichnete Behandlungsergebnisse. Beim AID wird eine Insulinpumpe mit einem System zur kontinuierlichen Glukosemessung zusammengeschaltet, während ein Rechenprogramm, der sogenannte Algorithmus, die Steuerung der Insulingabe nach Bedarf übernimmt. Idealerweise wäre das System ein geschlossener Kreis, bei dem die Menschen mit Diabetes keine Eingabe mehr machen müssten. Jedoch sind bei den heute verfügbaren Systemen verschiedene Grundeinstellungen und Eingaben erforderlich (insbesondere von Kohlenhydratmengen der Mahlzeiten oder körperlicher Aktivität), die sich von den bisherigen Empfehlungen der sensorunterstützten Pumpentherapie in einzelnen Aspekten unterscheiden. So werden die traditionellen Konzepte von „Basal“ und „Bolus“ mit AID weniger nützlich, da der Algorithmus beide Arten der Insulinabgabe verwendet, um die Glukosewerte dem eingestellten Zielwert zu nähern. Daher sollte bei diesen Systemen statt der Erfassung von „Basal“ und „Bolus“, zwischen einer „nutzerinitiierten“ und einer „automatischen“ Insulindosis unterschieden werden. Gemeinsame Therapieprinzipien der verschiedenen AID-Systeme umfassen die passgenaue Einstellung des Kohlenhydratverhältnisses, die Bedeutung des Timings der vom Anwender initiierten Insulinbolusgaben vor der Mahlzeit, den korrekten Umgang mit einem verzögerten oder versäumten Mahlzeitenbolus, neue Prinzipien im Umgang mit Sport oder Alkoholgenuss sowie den rechtzeitigen Umstieg von AID zu manuellem Modus bei Auftreten erhöhter Ketonwerte. Das Team vom Diabetes-Zentrum AUF DER BULT in Hannover hat aus eigenen Studienerfahrungen und der zugrunde liegenden internationalen Literatur praktische Empfehlungen zur Anwendung und Schulung der gegenwärtig und demnächst in Deutschland kommerziell erhältlichen Systeme zusammengestellt. Für den Erfolg der AID-Behandlung scheint das richtige Erwartungsmanagement sowohl beim Behandlungsteam und als auch beim Anwender von großer Bedeutung zu sein.

Newest Diabetes-Related Technologies for Pediatric Type 1 Diabetes and Its Impact on Routine Care: a Narrative Synthesis of the Literature

Purpose of Review

This review aims to address the actual state of the most advanced diabetes devices, as follows: continuous subcutaneous insulin infusions (CSII), continuous glucose monitoring systems (CGM), hybrid-closed loop (HCL) systems, and “Do-it-yourself” Artificial Pancreas Systems (DIYAPS) in children, adolescents, and young adults. This review has also the objective to assess the use of telemedicine for diabetes care across three different areas: education, social media, and daily care.

Recent Findings

Recent advances in diabetes technology after integration of CSII with CGM have increased the popularity of this treatment modality in pediatric age and shifted the standard diabetes management in many countries. We found an impressive transition from the use of CSII and/or CGM only to integrative devices with automated delivery systems. Although much has changed over the past 5 years, including a pandemic period that precipitated a broader use of telemedicine in diabetes care, some advances in technology may still be an additional burden of care for providers, patients, and caregivers. The extent of a higher rate of “auto-mode” use in diabetes devices while using the HCL/DIYAPS is essential to reduce the burden of diabetes treatment.

Summary

More studies including higher-risk populations are needed, and efforts should be taken to ensure proper access to cost-effective advanced technology on diabetes care.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40124-021-00248-7.

Efficacy of advanced hybrid closed loop systems for the management of type 1 diabetes in children

Over the last years significant advances have been achieved in the development of technologies for diabetes management. Continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), predictive low glucose management (PLGM), hybrid closed loop (HCL) and advanced hybrid closed loop (AHCL) systems allow better diabetes management, thus reducing the burden of the disease and the risk of chronic complications. This review summarizes the main characteristics of the currently available HCL and AHCL systems and their primary effects in children and adolescents with type 1 diabetes (T1D). The findings of trials assessing the glucose control (time in range, HbA1c values, hypoglycemic events), the health-related quality of life and the existing limits of the use of these technologies are reported. The most recent data clearly confirm the ability of the HCL and AHCL insulin delivery systems to safely achieve a significant improvement of glucose control and quality of life in the pediatric population with T1D. Further studies are underway to overcame current barriers and future improvements in the usability of these technologies are awaited to facilitate their use in the routine clinical practice. The HCL and AHCL algorithms are the key features of today's insulin delivery systems that mark a crucial step towards fully automated closed loop systems.

[Individualization of diabetes treatment by automated insulin delivery]

Insulinpumpen und Glucosesensoren haben sich in Registerdaten als effektiv in der Verbesserung der Diabetestherapie und Reduktion akuter Komplikationen gezeigt. In der pädiatrischen Diabetologie ist die Nutzung mindestens eines technischen Geräts Standard. Durch die Kombination beider Systeme ergibt sich Möglichkeit der automatischen Insulinabgabe („automated insulin delivery“, AID).

Viele AID-Systeme sind in klinischen Studien getestet und haben sich als sicher und effektiv erwiesen. Die Versorgungsituation in Deutschland erlaubt es derzeit nur, Mitgliedern der gesetzlichen Krankenversicherungen ein bestimmtes System zu verordnen; dieses ist für Kinder, die jünger als 7 Jahre sind, nicht geeignet. Gründe liegen in gesetzlichen Hürden und mangelnder Zertifizierung durch die Hersteller. Die CE-Zertifikate können Probleme bei der Insulinverordnung mit sich bringen. „Open-source“-Systeme sind Varianten, mit denen bestehende Regularien umgangen werden können. Daraus ergeben sich sowohl für Nutzer wie auch für Verordner Risiken.

Die dauerhafte Nutzung setzt sowohl auf Anwender- als auch auf Behandlerseite die fundierte Kenntnis der Eigenschaften der einzelnen AID-Systeme voraus. Eine vollständige Automatisierung funktioniert noch nicht. Zur Evaluation der AID-Therapie sind die metrischen Daten der Glucosesensoren, die „Zeit im Zielbereich“ und der „Glucose Management Indicator“ anerkannte und geeignete Parameter, da sie eine Beratung auf Basis der reellen Daten aus dem Alltag der Menschen mit Diabetes zulassen.

Da alle Glucosesensoren über Cloud-basierte Software ausgelesen werden oder die Daten automatisch aus einem telefonverbundenen Empfangsgerät beziehen, ist die ideale technische Grundlage für eine telemedizinische Betreuung geschaffen, die noch der Ausgestaltung bedarf.