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Background: Multiple clinician adjustable parameters impact upon glycemia in people with type 1 diabetes (T1D) using Medtronic Mini Med 780G (MM780G) AHCL. These include glucose targets, carbohydrate ratios (CR), and active insulin time (AIT). Algorithm-based decision support advising upon potential settings adjustments may enhance clinical decision-making., Methods: Single-arm, two-phase exploratory study developing decision support to commence and sustain AHCL. Participants commenced investigational MM780G, then 8 weeks Phase 1-initial optimization tool evaluation, involving algorithm-based decision support with weekly AIT and CR recommendations. Clinicians approved or rejected CR and AIT recommendations based on perceived safety per protocol. Co-design resulted in a refined algorithm evaluated in a further identically configured Phase 2. Phase 2 participants also transitioned to commercial MM780G following "Quick Start" (algorithm-derived tool determining initial AHCL settings using daily insulin dose and weight). We assessed efficacy, safety, and acceptability of decision support using glycemic metrics, and the proportion of accepted CR and AIT settings per phase., Results: Fifty three participants commenced Phase 1 (mean age 24.4; Hba1c 61.5mmol/7.7%). The proportion of CR and AIT accepted by clinicians increased between Phases 1 and 2 respectively: CR 89.2% vs. 98.6%, p < 0.01; AIT 95.2% vs. 99.3%, p < 0.01. Between Phases, mean glucose percentage time < 3.9mmol (< 70mg/dl) reduced (2.1% vs. 1.4%, p = 0.04); change in mean TIR 3.9-10mmol/L (70-180mg/dl) was not statistically significant: 72.9% ± 7.8 and 73.5% ± 8.6. Quick start resulted in stable TIR, and glycemic metrics compared to international guidelines., Conclusion: The co-designed decision support tools were able to deliver safe and effective therapy. They can potentially reduce the burden of diabetes management related decision making for both health care practitioners and patients., Trial Registration: Prospectively registered with Australia/New Zealand Clinical Trials Registry(ANZCTR) on 30th March 2021 as study ACTRN12621000360819., (© 2024. The Author(s).)

Introduction: To evaluate the experiences of patients with type 1 diabetes following transition from a calibration-requiring to a calibration-free sensor and remote monitoring in the context of using automated insulin delivery (AID)., Research Design and Methods: Fifteen participants aged 7-65 years with type 1 diabetes participating in a longitudinal study used a Medtronic® advanced hybrid closed loop (AHCL) device with initially calibration-requiring then calibration-free sensors. Qualitative interviews were conducted ≥20 weeks following use of the calibration-requiring and ≥4 weeks after use of the calibration-free sensors/remote monitoring. Thematic analysis was used to identify key themes and subthemes., Results: At baseline, mean diabetes duration was 14.5 years ( ± 10.9), mean Hba1c 54.8 mmol/mol ( ± 10.2) (7.2 ± 0.9%) and Time in range 75.4% ( ± 11.6). Participants reported a progressive improvement in digital and lifestyle integration, and device trust following transition to calibration-free sensors with remote monitoring potential. They also reported a reduced need for capillary glucose, increased device satisfaction and trust, and reduced burden of diabetes care. Negative aspects reported included periodic early sensor loss, and for some, impaired integration with mobile devices., Conclusion: Transitioning to calibration-free sensors with remote monitoring while using AHCL was associated with better user experience, including perceptions of improved quality of life and a reduced burden of diabetes care. Appropriate expectation setting, training, and ongoing support allow for the optimal user experience while using AHCL., Clinical Trial Registration: https://www.anzctr.org.au, identifier ACTRN12621000360819., Competing Interests: Author BW has previously received research funding from Dexcom, Medtronic and iSENS. Author MD received Research funding from: Novo Nordisk, Medtronic, Dexcom, Pfizer and Research support from Medtronic, Dexcom, SOOIL, Honoraria from Medtronic. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Sehgal, De Bock, Jones, Frewen and Wheeler.)

Background: Open-source automated insulin delivery (AID) systems are used by many patients with type 1 diabetes. Data are needed on the efficacy and safety of an open-source AID system., Methods: In this multicenter, open-label, randomized, controlled trial, we assigned patients with type 1 diabetes in a 1:1 ratio to use an open-source AID system or a sensor-augmented insulin pump (control). The patients included both children (defined as 7 to 15 years of age) and adults (defined as 16 to 70 years of age). The AID system was a modified version of AndroidAPS 2.8 (with a standard OpenAPS 0.7.0 algorithm) paired with a preproduction DANA-i insulin pump and Dexcom G6 CGM, which has an Android smartphone application as the user interface. The primary outcome was the percentage of time in the target glucose range of 70 to 180 mg per deciliter (3.9 to 10.0 mmol per liter) between days 155 and 168 (the final 2 weeks of the trial)., Results: A total of 97 patients (48 children and 49 adults) underwent randomization (44 to open-source AID and 53 to the control group). At 24 weeks, the mean (±SD) time in the target range increased from 61.2±12.3% to 71.2±12.1% in the AID group and decreased from 57.7±14.3% to 54.5±16.0% in the control group (adjusted difference, 14 percentage points; 95% confidence interval, 9.2 to 18.8; P<0.001), with no treatment effect according to age (P = 0.56). Patients in the AID group spent 3 hours 21 minutes more in the target range per day than those in the control group. No severe hypoglycemia or diabetic ketoacidosis occurred in either group. Two patients in the AID group withdrew from the trial owing to connectivity issues., Conclusions: In children and adults with type 1 diabetes, the use of an open-source AID system resulted in a significantly higher percentage of time in the target glucose range than the use of a sensor-augmented insulin pump at 24 weeks. (Supported by the Health Research Council of New Zealand; Australian New Zealand Clinical Trials Registry number, ACTRN12620000034932.)., (Copyright © 2022 Massachusetts Medical Society.)

Purpose: Open-source automated insulin delivery (AID) is used by thousands of people with type 1 diabetes (T1D), but has unknown generalisability to marginalised ethnic groups. This study explored experiences of Indigenous Māori participants in the CREATE trial with use of an open-source AID system to identify enablers/barriers to health equity. Methods: The CREATE randomised trial compared open-source AID (OpenAPS algorithm on an Android phone with a Bluetooth-connected pump) to sensor-augmented pump therapy. Kaupapa Māori Research methodology was used in this sub-study. Ten semi-structured interviews with Māori participants (5 children, 5 adults) and whānau (extended family) were completed. Interviews were recorded and transcribed, and data were analysed thematically. NVivo was used for descriptive and pattern coding. Results: Enablers/barriers to equity aligned with four themes: access (to diabetes technologies), training/support, operation (of open-source AID), and outcomes. Participants described a sense of empowerment, and improved quality of life, wellbeing, and glycaemia. Parents felt reassured by the system's ability to control glucose, and children were granted greater independence. Participants were able to use the open-source AID system with ease to suit whānau needs, and technical problems were manageable with healthcare professional support. All participants identified structures in the health system precluding equitable utilisation of diabetes technologies for Māori. Conclusion: Māori experienced open-source AID positively, and aspired to use this therapy; however, structural and socio-economic barriers to equity were identified. This research proposes strength-based solutions which should be considered in the redesign of diabetes services to improve health outcomes for Māori with T1D. Trial Registration: The CREATE trial, encompassing this qualitative sub-study, was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12620000034932p) on the 20th January 2020. [ABSTRACT FROM AUTHOR]

Objective: To study the MiniMed Advanced Hybrid Closed-Loop (AHCL) system, which includes an algorithm with individualized basal target set points, automated correction bolus function, and improved Auto Mode stability.Research Design and Methods: This dual-center, randomized, open-label, two-sequence crossover study in automated-insulin-delivery-naive participants with type 1 diabetes (aged 7-80 years) compared AHCL to sensor-augmented pump therapy with predictive low glucose management (SAP + PLGM). Each study phase was 4 weeks, preceded by a 2- to 4-week run-in and separated by a 2-week washout.Results: The study was completed by 59 of 60 people (mean age 23.3 ± 14.4 years). Time in target range (TIR) 3.9-10 mmol/L (70-180 mg/dL) favored AHCL over SAP + PLGM (70.4 ± 8.1% vs. 57.9 ± 11.7%) by 12.5 ± 8.5% (P < 0.001), with greater improvement overnight (18.8 ± 12.9%, P < 0.001). All age-groups (children [7-13 years], adolescents [14-21 years], and adults [>22 years]) demonstrated improvement, with adolescents showing the largest improvement (14.4 ± 8.4%). Mean sensor glucose (SG) at run-in was 9.3 ± 0.9 mmol/L (167 ± 16.2 mg/dL) and improved with AHCL (8.5 ± 0.7 mmol/L [153 ± 12.6 mg/dL], P < 0.001), but deteriorated during PLGM (9.5 ± 1.1 mmol/L [17 ± 19.8 mg/dL], P < 0.001). TIR was optimal when the algorithm set point was 5.6 mmol/L (100 mg/dL) compared with 6.7 mmol/L (120 mg/dL), 72.0 ± 7.9% vs. 64.6 ± 6.9%, respectively, with no additional hypoglycemia. Auto Mode was active 96.4 ± 4.0% of the time. The percentage of hypoglycemia at baseline (<3.9 mmol/L [70 mg/dL] and ≤3.0 mmol/L [54 mg/dL]) was 3.1 ± 2.1% and 0.5 ± 0.6%, respectively. During AHCL, the percentage time at <3.9 mmol/L (70 mg/dL) improved to 2.1 ± 1.4% (P = 0.034) and was statistically but not clinically reduced for ≤3.0 mmol/L (54 mg/dL) (0.5 ± 0.5%; P = 0.025). There was one episode of mild diabetic ketoacidosis attributed to an infusion set failure in combination with an intercurrent illness, which occurred during the SAP + PLGM arm.Conclusions: AHCL with automated correction bolus demonstrated significant improvement in glucose control compared with SAP + PLGM. A lower algorithm SG set point during AHCL resulted in greater TIR, with no increase in hypoglycemia. [ABSTRACT FROM AUTHOR]

Aim: To assess long-term efficacy and safety of open-source automated insulin delivery (AID) in children and adults (7–70 years) with type 1 diabetes. Methods: Both arms of a 24-week randomized controlled trial comparing open-source AID (OpenAPS algorithm within a modified version of AndroidAPS, preproduction DANA-i™ insulin pump, Dexcom G6 continuous glucose monitor) with sensor-augmented pump therapy (SAPT), entered a 24-week continuation phase where the SAPT arm (termed SAPT-AID) crossed over to join the open-source AID arm (termed AID-AID). Most participants (69/94) used a preproduction YpsoPump® insulin pump during the continuation phase. Analyses incorporated all 52 weeks of data, and combined between-group and within-subject differences to calculate an overall "treatment effect" of AID versus SAPT. Results: Mean time in range (TIR; 3.9–10 mmol/L [70–180 mg/dL]) was 12.2% higher with AID than SAPT (95% confidence interval [CI] 10.4 to 14.1; P < 0.001). TIR was 56.9% (95% CI 54.2 to 59.6) with SAPT and 69.1% (95% CI 67.1 to 71.1) with AID. The treatment effect did not differ by age (P = 0.39) or insulin pump type (P = 0.37). HbA1c was 5.1 mmol/mol lower [0.5%] with AID (95% CI −6.6 to −3.6; P < 0.001). There were no episodes of diabetic ketoacidosis or severe hypoglycemia with either treatment over the 48 weeks. Six participants (all in SAPT-AID) withdrew: three with hardware issues, two preferred SAPT, and one with infusion-site skin irritation. Conclusion: Further evaluation of the community derived automated insulin delivery (CREATE) trial to 48 weeks confirms that open-source AID is efficacious and safe with different insulin pumps, and demonstrates sustained glycemic improvements without additional safety concerns. [ABSTRACT FROM AUTHOR]