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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]

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: Although strategies to prevent premature sensor loss for flash glucose monitoring (FGM) systems may have substantial benefit, limited data are available. This study among youth with high-risk type 1 diabetes evaluated whether an additional adhesive patch over FGM sensors would reduce premature sensor loss frequency and not cause additional cutaneous adverse events (AEs). Methods: This is a six-month, open-label, randomized crossover trial. Participants were recruited at completion of prior 'Managing Diabetes in a Flash' randomized controlled trial and allocated to three months of Freestyle Libre FGM sensors with either standard adhesive (control) or additional adhesive patches (RockaDex, New Zealand) (intervention), before crossing over to the opposite study arm. Participants self-reported patch use or non-use, premature sensor loss and cutaneous AEs fortnightly via an electronic questionnaire. Results: Thirty-four participants were enrolled: mean age (± SD) 17.0 (± 2.2) years; mean HbA1c (± SD) 89 (± 16) mmol/mol (10.3% ± 1.4%). The response rate of questionnaires was 77% (314/408). Premature sensor loss was reported in 18% (58/314) of questionnaires: 20% (32/162) from intervention and 17% (26/152) from control (p = 0.56). Thirty-eight percent (118/314) of questionnaires were non-compliant to protocol allocation. However, per-protocol analysis showed similar findings. No significant difference in AEs was reported between compliant adhesive patch use and non-use (6% [5/78] and 3% [3/118], respectively, p = 0.27). Conclusions: The adhesive patch investigated in this study does not appear to prevent premature FGM sensor loss. However, the low risk of AEs and low cost of an adhesive patch suggest an individualized approach to their use may still be warranted. Further research is needed to explore alternative strategies to prevent sensor loss. [ABSTRACT FROM AUTHOR]

Background: In type 1 diabetes mellitus (T1D), glycemic control and sleep have a bidirectional relationship, with unhealthy glycemic control impacting sleep, and inadequate sleep impacting diabetes management. Youth are at risk for poor quality sleep; however, little is known about sleep among youth with high-risk glycemic control., Objective: To assess differences in habitual sleep timing, duration, and quality among youth with T1D and controls., Subjects: Two-hundred-thirty youth (13-20 years): 64 with T1D (mean age 16.6 ± 2.1 years, 48% female, diabetes duration 7.5 ± 3.8 years, HbA1c 96 ± 18.0 mmol/mol [10.9 ± 1.7%]), and 166 controls (mean age 15.3 ± 1.5, 58% female)., Methods: Comparison of data from two concurrent studies (from the same community) using subjective and objective methods to assess sleep in youth: Pittsburgh Sleep Quality Index evaluating sleep timing and quality; 7-day actigraphy measuring habitual sleep patterns. Regression analyses were used to compare groups., Results: When adjusted for various confounding factors, youth with T1D reported later bedtimes (+36 min; p < 0.05) and shorter sleep duration (-53 min; p < 0.05) than controls, and were more likely to rate subjective sleep duration (OR 3.57; 95% CI 1.41-9.01), efficiency (OR 4.03; 95% CI 1.43-11.40), and quality (OR 2.59; 95% CI 1.16-5.76) as "poor" (p < 0.05). However, objectively measured sleep patterns were similar between the two groups., Conclusions: Youth with high-risk T1D experience sleep difficulties, with later bedtimes contributing to sleep deficit. Despite a lack of objective differences, they perceive their sleep quality to be worse than peers without diabetes., (© 2021 John Wiley & Sons A/S . Published by John Wiley & Sons Ltd.)

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 (HbA 1c ) ≥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 HbA 1c from baseline to 6 months., Results: There was no evidence of a difference between groups for changes in HbA 1c 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., (© 2020 by the American Diabetes Association.)