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

Burnside, Mercedes; Lewis, Dana; Crocket, Hamish; Meier, Renee; Williman, Jonathan; Sanders, Olivia J.; Jefferies, Craig; Faherty, Ann; Paul, Ryan; Lever, Claire; Price, Sarah Kye; Frewen, Carla; Jones, Stephanie; Gunn, Tim; Lampey, Christina; Wheeler, Benjamin J; Bock, Martin

doi:10.1089/dia.2022.0484

Cited by 13 publications

(11 citation statements)

References 20 publications

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“…Preliminary data from the follow-up study of users who continued using the AID system beyond the trial supports these findings 8 . 18% of the participants were from non-White ethnic groups and 28% were from the lower 2 quintiles of New Zealand's deprivation index.…”

mentioning

confidence: 74%

Open-source automated insulin delivery in type 1 diabetes—the evidence is out there

Hussain

Lal

Braune

2022

The Lancet Diabetes & Endocrinology

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mentioning

confidence: 74%

Open-source automated insulin delivery in type 1 diabetes—the evidence is out there

Hussain

Lal

Braune

2022

The Lancet Diabetes & Endocrinology

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“…These factors may have contributed to the poorer average outcomes in AAPS users compared with our study. [5][6][7] Our study also has limitations. Because this was a non-randomized study, it is possible that some unmeasured factors could affect our findings.…”

Section: Discussionmentioning

confidence: 91%

“…However, in contrast to our study, their trial compared the use of AAPS with SAPs. 6,7 Additionally, similar design was also used in other studies. [5][6][7][8] However, we believe that comparing the AID system with SAP will not provide many new insights and there is a need to focus on studies with different AID systems as these are considered the standard of care for type 1 diabetes.…”

Section: Discussionmentioning

confidence: 99%

“…6,7 Additionally, similar design was also used in other studies. [5][6][7][8] However, we believe that comparing the AID system with SAP will not provide many new insights and there is a need to focus on studies with different AID systems as these are considered the standard of care for type 1 diabetes. 27,28 Although dramatic differences between AID systems are not generally expected, 28 our study suggests that there may be differences that can be considered clinically relevant.…”

Section: Discussionmentioning

confidence: 99%

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

Do,

Hásková,

Radovnická

et al. 2023

Diabetes Obesity Metabolism

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AimTo 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.MethodsAdults 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).ResultsTwenty‐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.ConclusionsThe 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.

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“…101 Reports on open-source AID systems have documented the efficacy of these do-it-yourself (DIY) systems both in the primary trial 102 and with continued use during an extension phase. 103 Two studies have investigated whether attaining strict glucose control through the use of an AID system could preserve residual betacell function as measured by C-peptide secretion, both failing to show a difference compared with those receiving standard of care. 104,105 Continued exploration regarding use of AID systems in subgroups of individuals living with diabetes, like very young children, 106 echo the findings regarding the beneficial impact of AID use.…”

Section: Automated Insulin Deliverymentioning

confidence: 99%

Utility of Technology in the Treatment of Type 1 Diabetes: Current State of the Art and Precision Evidence

Jacobsen

Sherr

Consindine

et al. 2023

Preprint

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The greatest change in the treatment of people living with type 1 diabetes in the last decade has been the explosion of technology assisting in all aspects of diabetes therapy, from glucose monitoring to insulin delivery and decision making. Through screening of 835 peer-reviewed articles followed by systematic review of 70 of them (focusing on randomized trials and extension studies with ≥50 participants from the past 10 years), we conclude that novel technologies, ranging from continuous glucose monitoring systems, insulin pumps and decision support tools to the most advanced hybrid closed loop systems, improve important measures like HbA1c, time in range, and glycemic variability, while reducing hypoglycemia risk. Several studies included person-reported outcomes, allowing assessment of the burden or benefit of the technology in the lives of those with type 1 diabetes, demonstrating positive results or, at a minimum, no increase in self-care burden compared with standard care. Important limitations of the trials to date are their small size, the scarcity of pre-planned or powered analyses in sub-populations such as children, racial/ethnic minorities, people with advanced complications, and variations in baseline glycemic levels. In addition, confounders including education with device initiation, concomitant behavioral modifications, and frequent contact with the healthcare team are rarely described in enough detail to assess their impact. Our review highlights the potential of technology in the treatment of people living with type 1 diabetes and provides suggestions for optimization of outcomes and areas of further study for precision medicine-directed technology use in type 1 diabetes.

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

Cited by 13 publications

References 20 publications

Open-source automated insulin delivery in type 1 diabetes—the evidence is out there

Open-source automated insulin delivery in type 1 diabetes—the evidence is out there

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

Utility of Technology in the Treatment of Type 1 Diabetes: Current State of the Art and Precision Evidence

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