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Aims: To investigate the impact of real‐time continuous glucose monitoring (rtCGM) on glycaemia in a predominantly indigenous (Māori) population of adults with insulin‐requiring type 2 diabetes (T2D) in New Zealand. Methods: Twelve‐week, multicentre randomised controlled trial (RCT) of adults with T2D using ≥0.2 units/kg/day of insulin and elevated glycated haemoglobin (HbA1c) ≥64 mmol/mol (8.0%). Following a 2‐week blinded CGM run‐in phase, participants were randomised to rtCGM or control (self‐monitoring blood glucose [SMBG]). The primary outcome was time in the target glucose range (3.9–10 mmol/L; TIR) during weeks 10–12, with data collected by blinded rtCGM in the control group. Results: Sixty‐seven participants entered the RCT phase (54% Māori, 57% female), median age 53 (range 16–70 years), HbA1c 85 (IQR 74, 94) mmol/mol (9.9 [IQR 8.9, 10.8]%), body mass index (36.7 ± 7.7 kg/m2). Mean (±SD) TIR increased from 37 (24)% to 53 (24)% [Δ 13%; 95% CI 4.2 to 22; P = 0.007] in the rtCGM group but did not change in the SMBG group [45 (21)% to 45 (25)%, Δ 2.5%, 95% CI −6.1 to 11, P = 0.84]. Baseline‐adjusted between‐group difference in TIR was 10.4% [95% CI −0.9 to 21.7; P = 0.070]. Mean HbA1c (±SD) decreased in both groups from 85 (18) mmol/mol (10.0 [1.7]%) to 64 (16) mmol/mol (8.0 [1.4]%) in the rtCGM arm and from 81 (12) mmol/mol (9.6 [1.1]%) to 65 (13) mmol/mol (8.1 [1.2]%) in the SMBG arm (P < 0.001 for both). There were no severe hypoglycaemic or ketoacidosis events in either group. Conclusions: Real‐time CGM use in a supportive treat‐to‐target model of care likely improves glycaemia in a population with insulin‐treated T2D and elevated HbA1c. [ABSTRACT FROM AUTHOR]

Purpose: Advanced hybrid closed loop (AHCL) systems have the potential to improve glycemia and reduce burden for people with type 1 diabetes (T1D). Children and youth, who are at particular risk for out-of-target glycemia, may have the most to gain from AHCL. However, no randomized controlled trial (RCT) specifically targeting this age group with very high HbA1c has previously been attempted. Therefore, the CO-PILOT trial (Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control) aims to evaluate the efficacy and safety of AHCL in this group. Methods: A prospective, multicenter, parallel-group, open-label RCT, comparing MiniMed™ 780G AHCL to standard care (multiple daily injections or continuous subcutaneous insulin infusion). Eighty participants aged 7–25 years with T1D, a current HbA1c ≥ 8.5% (69 mmol/mol), and naïve to automated insulin delivery will be randomly allocated to AHCL or control (standard care) for 13 weeks. The primary outcome is change in HbA1c between baseline and 13 weeks. Secondary outcomes include standard continuous glucose monitor glycemic metrics, psychosocial factors, sleep, platform performance, safety, and user experience. This RCT will be followed by a continuation phase where the control arm crosses over to AHCL and all participants use AHCL for a further 39 weeks to assess longer term outcomes. Conclusion: This study will evaluate the efficacy and safety of AHCL in this population and has the potential to demonstrate that AHCL is the gold standard for children and youth with T1D experiencing out-of-target glucose control and considerable diabetes burden. Trial registration: This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 14 November 2022 (ACTRN12622001454763) and the World Health Organization International Clinical Trials Registry Platform (Universal Trial Number U1111-1284-8452). [ABSTRACT FROM AUTHOR]

Background: Automated insulin delivery is the treatment of choice in adults with type 1 diabetes. Data are needed on the efficacy and safety of automated insulin delivery for children and youth with diabetes and elevated glycated hemoglobin levels. Methods: In this multicenter, open-label randomized controlled trial, we assigned patients with type 1 diabetes in a 1:1 ratio either to use an automated insulin delivery system (MiniMed 780G) or to receive usual diabetes care of multiple daily injections or non-automated pump therapy (control). The patients were children and youth (defined as 7 to 25 years of age) with elevated glycemia (glycated hemoglobin ≥8.5% with no upper limit). The primary outcome was the baseline-adjusted between-group difference in glycated hemoglobin at 13 weeks. Results: A total of 80 patients underwent randomization (37 to automated insulin delivery and 43 to control) and all patients completed the trial. At 13 weeks, the mean (±SD) glycated hemoglobin decreased from 10.5±1.9% to 8.1±1.8% in the automated insulin delivery group but remained relatively consistent in the control group, changing from 10.4±1.6% to 10.6±1.8% (baseline-adjusted between-group difference, -2.5 percentage points; 95% confidence interval [CI], -3.1 to -1.8; P<0.001). Patients in the automated insulin delivery group spent on average 8.4 hours more in the target glucose range of 70 to 180 mg/dl than those in the control group. One severe hypoglycemia event and two diabetic ketoacidosis events occurred in the control group, with no such events in the automated insulin delivery group. Conclusions: In this trial of 80 children and youth with elevated glycated hemoglobin, automated insulin delivery significantly reduced glycated hemoglobin compared with usual diabetes care, without resulting in severe hypoglycemia or diabetic ketoacidosis events. (Funded by Lions Clubs New Zealand District 202F and others; Australian New Zealand Clinical Trials Registry number, ACTRN12622001454763.) [ABSTRACT FROM AUTHOR]

Purpose: The OPTIMISE study uses a Multiphase Optimisation Strategy (MOST) to identify the best combination of four interventions targeting key diabetes self-care behaviours for use in clinical practice to improve short-term glycaemic outcomes. Methods: This 4-week intervention trial will recruit 80 young people (aged 13–20 years) with type 1 diabetes ≥ 6 months duration), and pre-enrolment HbA1c ≥ 58 mmol/mol (7.5%) in the prior 6 months. Both main intervention and interaction effects will be estimated using a linear regression model with change in glucose time-in-range (TIR; 3.9–10.0 mmol/L) as the primary outcome. Participants will be randomised to one of 16 conditions in a factorial design using four intervention components: (1) real-time continuous glucose monitoring (CGM), (2) targeted snacking education, (3) individualised sleep extension, and (4) values-guided self-care goal setting. Baseline and post-intervention glucose TIR will be assessed with blinded CGM. Changes in self-care (snacking behaviours, sleep habits and duration, and psychosocial outcomes) will be assessed at baseline and post-intervention to determine if these interventions impacted behaviour change. Discussion: The study outcomes will enable the selection of effective and efficient intervention components that increase glucose TIR in young people who struggle to achieve targets for glycaemic control. The optimised intervention will be evaluated in a future randomised controlled trial and guide the planning of effective clinical interventions in adolescents and young adults living with type 1 diabetes. Trial registration: This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 7 October 2020 (ACTRN12620001017910) and the World Health Organisation International Clinical Trails Registry Platform on 26 July 2020 (Universal Trial Number WHO U1111-1256-1248). [ABSTRACT FROM AUTHOR]

Background: Continuous glucose monitoring (CGM) decreases fear of hypoglycemia (FOH) and improves glycemic control among those affected by type 1 diabetes (T1D). No studies to date have examined the impact of using do‐it‐yourself real‐time continuous glucose monitoring (DIY RT‐CGM) on psychological and glycemic outcomes. Methods: Child–parent dyads were recruited for a multicentre randomized crossover trial. Children with T1D were current intermittently scanned CGM (isCGM) users and aged 2–13 years. Families received either 6 weeks of DIY RT‐CGM with parental remote monitoring (intervention) or 6 weeks of isCGM plus usual diabetes care (control), followed by a 4‐week washout period, then crossed over. The primary outcome was parental FOH. Secondary outcomes were glycemic control using traditional CGM metrics, as well as a range of other psychosocial measures. Findings: Fifty five child–parent dyads were recruited. The child mean age was 9.1 ± 2.8 years. Although, there was no effect on parental FOH, −0.1 (95%CI: −0.3, 0.1, p = 0.4), time‐in‐range (TIR) (%3.9‐10 mmol/L) was significantly higher with DIY RT‐CGM over isCGM (54.3% ± 13.7 vs. 48.1% ± 13.6), mean difference, 5.7% (95%CI 1.8, 9.6, p <0.004). There was no difference for time spent in hypoglycemia. Parent diabetes treatment satisfaction was significantly higher following DIY RT‐CGM compared to isCGM, mean difference 5.3 (95%CI: 2.3, 8.2, p <0.001). Conclusion: The use of DIY RT‐CGM versus isCGM did not improve parental FOH; however, TIR and parental satisfaction with diabetes treatment were significantly improved. This suggests in the short term, DIY RT‐CGM appears safe and may offer families some clinically important advantages over isCGM. [ABSTRACT FROM AUTHOR]

Aims: To describe the impact of a 12‐month intervention using intermittently scanned continuous glucose monitoring (isCGM) on glycaemic control and glucose test frequency in adolescents and young adults with type 1 diabetes (T1D) and high‐risk glycaemic control (HbA1c ≥75 mmol/mol [≥9.0%]). Methods: In total, 64 young people (aged 13–20 years, 16.6 ± 2.1 years; 48% female; 41% Māori or Pacific ethnicity; mean diabetes duration 7.5 ± 3.8 years) with T1D were enrolled in a 6‐month, randomized, parallel‐group study comparing glycaemic outcomes from the isCGM intervention (n = 33) to self monitoring blood glucose (SMBG) controls (n = 31). In this 6‐month extension phase, both groups received isCGM; HbA1c, glucose time‐in‐range (TIR), and combined glucose test frequency were assessed at 9 and 12 months. Results: At 12 months, the mean difference in HbA1c from baseline was −4 mmol/mol [−0.4%] (95% confidence interval, CI: −8, 1 mmol/mol [−0.8, 0.1%]; p = 0.14) in the isCGM intervention group, and −7 mmol/mol [−0.7%] (95% CI: −16, 1 mmol/mol [−1.5, 0.1%]; p = 0.08) in the SMBG control group. No participants achieved ≥70% glucose TIR (3.9–10.0 mmol/L). The isCGM intervention group mean rate of daily glucose testing was highest at 9 months, 2.4 times baseline rates (p < 0.001), then returned to baseline by 12 months (incidence rate ratio = 1.4; 95% CI: 0.9, 2.1; p = 0.091). Conclusions: The use of isCGM in young people with high‐risk T1D resulted in transient improvements in HbA1c and glucose monitoring over a 9‐month time frame; however, benefits were not sustained to 12 months. [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]

Objective: To investigate glycemic and psychosocial outcomes with hybrid closed-loop (HCL) versus user-determined insulin dosing with multiple daily injections (MDI) or insulin pump (i.e., standard therapy for most adults with type 1 diabetes).Research Design and Methods: Adults with type 1 diabetes using MDI or insulin pump without continuous glucose monitoring (CGM) were randomized to 26 weeks of HCL (Medtronic 670G) or continuation of current therapy. The primary outcome was masked CGM time in range (TIR; 70-180 mg/dL) during the final 3 weeks.Results: Participants were randomized to HCL (n = 61) or control (n = 59). Baseline mean (SD) age was 44.2 (11.7) years, HbA1c was 7.4% (0.9%) (57 [10] mmol/mol), 53% were women, and 51% used MDI. HCL TIR increased from (baseline) 55% (13%) to (26 weeks) 70% (10%) with the control group unchanged: (baseline) 55% (12%) and (26 weeks) 55% (13%) (difference 15% [95% CI 11, 19]; P < 0.0001). For HCL, HbA1c was lower (median [95% CI] difference -0.4% [-0.6, -0.2]; -4 mmol/mol [-7, -2]; P < 0.0001) and diabetes-specific positive well-being was higher (difference 1.2 [95% CI 0.4, 1.9]; P < 0.0048) without a deterioration in diabetes distress, perceived sleep quality, or cognition. Seventeen (9 device-related) versus 13 serious adverse events occurred in the HCL and control groups, respectively.Conclusions: In adults with type 1 diabetes, 26 weeks of HCL improved TIR, HbA1c, and their sense of satisfaction from managing their diabetes compared with those continuing with user-determined insulin dosing and self-monitoring of blood glucose. For most people living with type 1 diabetes globally, this trial demonstrates that HCL is feasible, acceptable, and advantageous. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether intermittently scanned continuous glucose monitoring (isCGM) significantly improves glycemic control compared with capillary self-monitored blood glucose (SMBG) in youth with type 1 diabetes and high-risk glycemic control.Research Design and Methods: This multicenter 6-month randomized, controlled, parallel-arm trial included 64 participants aged 13-20 years with established type 1 diabetes and glycated hemoglobin (HbA1c) ≥9% (≥75 mmol/mol). Participants were allocated to 6-month intervention (isCGM; FreeStyle Libre; Abbott Diabetes Care, Witney, U.K.) (n = 33) or control (SMBG; n = 31) using minimization. The primary outcome was the difference in change in HbA1c from baseline to 6 months.Results: There was no evidence of a difference between groups for changes in HbA1c at 6 months (adjusted mean 0.2% greater improvement for isCGM [95% CI -0.9 to 0.5] [-2.1 mmol/mol (95% CI -9.6 to 5.4)]; P = 0.576). However, glucose-monitoring frequency was 2.83 (95% CI 1.72-4.65; P < 0.001) times higher in the isCGM group compared with that in the SMBG group at 6 months. The change in the Diabetes Treatment Satisfaction Questionnaire mean item score also favored isCGM at 6 months (P = 0.048), with no significant differences between groups for fear of hypoglycemia and quality of life (both general and diabetes specific) (all P > 0.1).Conclusions: For youth with high-risk glycemic control, isCGM led to improvements in glucose testing frequency and diabetes treatment satisfaction. However, these did not translate to greater improvement in glycemic control over usual care with SMBG at 6 months. [ABSTRACT FROM AUTHOR]

Background: We compared glycemia, treatment satisfaction, sleep quality, and cognition using a nighttime Android-based hybrid closed-loop system (Android-HCLS) with sensor-augmented pump with low-glucose suspend function (SAP-LGS) in people with type 1 diabetes.Materials and Methods: An open-label, prospective, randomized crossover study of 16 adults (mean [SD] age 42.1 [9.6] years) and 12 adolescents (15.2 [1.6] years) was conducted. All participants completed four consecutive nights at home with Android-HCLS (proportional integral derivative with insulin feedback algorithm; Medtronic) and SAP-LGS.Primary Outcome: percent continuous glucose monitoring (CGM) time (00:00-08:00 h) within target range (72-144 mg/dL). Secondary endpoints: percent CGM time above target (>144 mg/dL); below target (<72 mg/dL); glycemic variability (SD); symptomatic hypoglycemia; adult treatment satisfaction; sleep quality; and cognitive function.Results: The primary outcome for all participants was not statistically different between Android-HCLS and SAP-LGS (mean [SD] 59.4 [17.9]% vs. 53.1 [18]%; p = 0.14). Adults had greater percent time within target range (57.7 [18.6]% vs. 44.5 [14.5]%; p < 0.006); less time above target (42.0 [18.7]% vs. 52.6 [16.5]%; p = 0.034); lower glycemic variability (35 [10.7] mg/dL vs. 46 [10.7] mg/dL; p = 0.003); and less (median [IQR]) time below target (0.0 [0.0-0.4]% vs. 0.80 [0.0-3.9]%; p = 0.025). In adolescents, time below target was lower with Android-HCLS vs. SAP-LGS (0.0 [0.0-0.0]% vs. 1.8 [0.1-7.9]%; p = 0.011). Nocturnal symptomatic hypoglycemia was less (1 vs. 10; p = 0.007) in adolescents, but not adults (5 vs. 13; p = 0.059). In adults, treatment satisfaction increased by 10 points (p < 0.02). Sleep quality and cognition did not differ.Conclusions: Android-HCLS in both adults and adolescents reduced nocturnal hypoglycemia and, in adults, improved overnight time in target range and treatment satisfaction compared with SAP-LGS. [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]

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.). [ABSTRACT FROM AUTHOR]