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Aim: To understand experiences of using second‐generation advanced hybrid closed‐loop (AHCL) therapy in adolescents and young adults with chronically elevated glucose levels who were previously using multiple daily injections (MDI) therapy. Method: Semi‐structured interviews with participants aged 13–25 years, on AHCL therapy for 3 months as part of a single‐arm prospective study. Key inclusions: HbA1c ≥69 mmol/mol (8.5%); diabetes duration ≥1 year; and using MDI therapy prior to the study. Qualitative content analysis was used to identify themes and subthemes. Results: Interviews were conducted among 14 participants with mean age 19.4 ± 4.3 years and mean baseline HbA1c 90 ± 25 mmol/mol (10.4 ± 4.5%). Three themes were identified: (1) substantially improved glucose levels improved perceptions of overall health; (2) features of AHCL aid in adoption and ongoing self‐management; and (3) burden of care was reduced through automation of insulin delivery. Overall, there were positive impacts on physical, mental and social well‐being. Participants were willing to overlook minor frustrations with AHCL because of the vast benefits that they had experienced. Four participants reported transient pseudo‐hypoglycaemia: symptoms of hypoglycaemia when objectively measured glucose was in the clinically recommended range (3.9–10 mmol/L, 70–180 mg/dL). Conclusion: Transition to AHCL therapy positively impacted diabetes management in adolescents and youth with chronically elevated glucose levels. It appears to create a window of opportunity in which youth may re‐engage with diabetes management. Pseudo‐hypoglycaemia can occur during the transition to AHCL. This could be a barrier to AHCL uptake and is likely to require individualised support. [ABSTRACT FROM AUTHOR]

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]

OBJECTIVE: Technology use in type 1 diabetes (T1D) is impacted by socioeconomic status (SES). This analysis explored relationships between SES, glycemic outcomes, and technology use. RESEARCH DESIGN AND METHODS: A cross-sectional analysis of HbA1c data from 2,822 Australian youth with T1D was undertaken. Residential postcodes were used to assign SES based on the Index of Relative Socio-Economic Disadvantage (IRSD). Linear regression models were used to evaluate associations among IRSD quintile, HbA1c, and management regimen. RESULTS: Insulin pump therapy, continuous glucose monitoring, and their concurrent use were associated with lower mean HbA1c across all IRSD quintiles (P < 0.001). There was no interaction between technology use and IRSD quintile on HbA1c (P = 0.624), reflecting a similar association of lower HbA1c with technology use across all IRSD quintiles. CONCLUSIONS: Technology use was associated with lower HbA1c across all socioeconomic backgrounds. Socioeconomic disadvantage does not preclude glycemic benefits of diabetes technologies, highlighting the need to remove barriers to technology access. [ABSTRACT FROM AUTHOR]

Background: Technology use, including continuous glucose monitoring (CGM) and insulin pump therapy, is associated with improved outcomes in youth with type 1 diabetes (T1D). In 2017 CGM was universally funded for youth with T1D in Australia. In contrast, pump access is primarily accessed through private health insurance, self-funding or philanthropy. The study aim was to investigate the use of diabetes technology across different socioeconomic groups in Australian youth with T1D, in the setting of two contrasting funding models. Methods: A cross-sectional evaluation of 4957 youth with T1D aged <18 years in the national registry was performed to determine technology use. The Index of Relative Socio-Economic Disadvantage (IRSD) derived from Australian census data is an area-based measure of socioeconomic status (SES). Lower quintiles represent greater disadvantage. IRSD based on most recent postcode of residence was used as a marker of SES. A multivariable generalised linear model adjusting for age, diabetes duration, sex, remoteness classification, and location within Australia was used to determine the association between SES and device use. Results: CGM use was lower in IRSD quintile 1 in comparison to quintiles 2 to 5 (p<0.001) where uptake across the quintiles was similar. A higher percentage of pump use was observed in the least disadvantaged IRSD quintiles. Compared to the most disadvantaged quintile 1, pump use progressively increased by 16% (95% CI: 4% to 31%) in quintile 2, 19% (6% to 33%) in quintile 3, 35% (21% to 50%) in quintile 4 and 51% (36% to 67%) in the least disadvantaged quintile 5. Conclusion: In this large national dataset, use of diabetes technologies was found to differ across socioeconomic groups. For nationally subsidised CGM, use was similar across socioeconomic groups with the exception of the most disadvantaged quintile, an important finding requiring further investigation into barriers to CGM use within a nationally subsidised model. User pays funding models for pump therapy result in lower use with socioeconomic disadvantage, highlighting inequities in this funding approach. For the full benefits of diabetes technology to be realised, equitable access to pump therapy needs to be a health policy priority. [ABSTRACT FROM AUTHOR]

Aim. To assess children's subsequent device usage and caregiver attitudes to do-it-yourself real-time continuous glucose monitoring (DIY-rtCGM) at least 3 months after completing a randomized controlled trial (RCT). Methods. A brief online questionnaire or telephone call was used to collect the subsequent device usage and caregivers' attitudes from a total of 55 families at least 3 months after their completion of an RCT investigating DIY-rtCGM adapted from their preexisting intermittently scanned glucose sensors plus education on using DIY-rtCGM system. To be eligible for the RCT, children had to be aged 2–13 years, have type 1 diabetes ≥6 months, and be rtCGM naïve. Data collected investigated current CGM use post-RCT and attitudes/user experiences to DIY-rtCGM in the months since RCT study support ended. Results. Overall, responses from 81.8% (45/55) of caregivers were received. Mean age of children was 9.0 ± 2.7 years, and 31 (68.9%) children used insulin pumps. After 3 months, 44.4% (20/45) of responding caregivers reported ongoing DIY-rtCGM use, and of these, only 13 used DIY-rtCGM as the primary glucose monitoring method 100% of time. Of the 25 (55.6%) families who ceased DIY-rtCGM, 40% (10/25) had transitioned to commercial rtCGM. More than half of families (60%, 12/20) who continued DIY-rtCGM use had a very or extremely positive attitude toward the technology and 75% (15/20) of these families planned to continue DIY-rtCGM use. However, signal loss and sensor inaccuracy remained the major reasons among all responders both for decreased DIY-rtCGM wear time and eventual cessation. Burden of use primarily related to technical errors that could not be solved, and alarms, both of which were reported to contribute to discontinuation. Conclusions. This study highlights that, among families voluntarily using DIY-rtCGM at least 3 months following support from a trial, more than half have ceased using DIY-rtCGM, with 40% of those discontinuing switching to commercial rtCGM. While overall perceptions of DIY-rtCGM remain largely positive, burdens of use are high and contribute to discontinuation. [ABSTRACT FROM AUTHOR]

Background. The bidirectional relationship between sleep and blood glucose levels may particularly affect adolescents and young adults (AYA), who are more likely to experience less healthy glycemic outcomes and more disrupted sleep patterns. To date, few data exist describing the impact of intermittently scanned continuous glucose monitoring (isCGM) on habitual sleep patterns and sleep quality in AYA with type 1 diabetes (T1D). Objective. To evaluate the impact of 6-month use of isCGM on habitual sleep and wake timing, sleep duration, frequency, and duration of night-time awakenings, sleep efficiency, and perceived sleep quality in young people with T1D and HbA1c ≥ 75 mmol/mol. Participants. The study recruited 64 participants aged 13–20 years (mean 16.6 ± 2.1), 48% female, diabetes duration 7.5 ± 3.8 years, 41% Māori or Pasifika, and a mean HbA1c 96.0 ± 18.0 mmol/mol [10.9 ± 3.8%]; 33 were allocated to an isCGM plus self-monitoring blood glucose [SMBG] intervention, and 31 were allocated to the SMBG control group. Methods. Participants completed 7-day actigraphy measures and the Pittsburgh Sleep Quality Index questionnaire at the baseline and at 6 months. Regression analyses were used to model between-group comparisons, adjusted for baseline sleep measures. Results. At 6 months, subjective measures for overall sleep quality, latency, duration, efficiency, night-time disturbances, use of sleep medications, and daytime dysfunction were similar between the groups. Regression analyses of actigraphy found no significant differences in objectively measured sleep timing and duration across the week after adjusting for age, the period of the school year, and baseline sleep values. Conclusions. The use of first-generation isCGM in addition to finger-prick testing did not impact objective or subjective sleep measures in AYA with T1D, elevated HbA1c, and highly variable sleep patterns. Research using alternative interventions for improving glycemic outcomes and habitual sleep-wake timing, duration, and perceived sleep quality is warranted in this population group. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To evaluate glycemic outcomes in youth (aged 13–25 years) with type 1 diabetes and high-risk glycemic control (HbA1c ≥8.5% [69 mmol/mol]) on multiple daily injection (MDI) therapy after transitioning to advanced hybrid closed loop (AHCL) therapy. RESEARCH DESIGN AND METHODS: This prospective, 3-month, single-arm, dual-center study enrolled 20 participants, and all completed the study. RESULTS: HbA1c decreased from 10.5 ± 2.1% (91.2 ± 22.8 mmol/mol) at baseline to 7.6 ± 1.1% (59.7 ± 11.9 mmol/mol), and time spent in target range 70–180 mg/dL (3.9–10.0 mmol/L) increased from 27.6 ± 13.2% at baseline to 66.5 ± 9.8% after 3 months of AHCL. Two episodes of diabetic ketoacidosis attributed to infusion set failure occurred. CONCLUSIONS: AHCL has the potential to improve suboptimal glycemia in youth with type 1 diabetes previously on MDI therapy. [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]

Aims: We aimed to conduct a systematic review and meta‐analysis of randomised controlled clinical trials (RCTs) assessing separately and together the effect of the three distinct categories of continuous glucose monitoring (CGM) systems (adjunctive, non‐adjunctive and intermittently‐scanned CGM [isCGM]), compared with traditional capillary glucose monitoring, on HbA1c and CGM metrics. Methods: PubMed, Web of Science, Scopus and Cochrane Central register of clinical trials were searched. Inclusion criteria were as follows: randomised controlled trials; participants with type 1 diabetes of any age and insulin regimen; investigating CGM and isCGM compared with traditional capillary glucose monitoring; and reporting glycaemic outcomes of HbA1c and/or time‐in‐range (TIR). Glycaemic outcomes were extracted post‐intervention and expressed as mean differences and 95%CIs between treatment and comparator groups. Results were pooled using a random‐effects meta‐analysis. Risk of bias was assessed using the Cochrane Rob2 tool. Results: This systematic review was conducted between January and April 2021; it included 22 RCTs (15 adjunctive, 5 non‐adjunctive, and 2 isCGM)). The overall analysis of the pooled three categories showed a statistically significant absolute improvement in HbA1c percentage points (mean difference (95% CI): −0.22% [−0.31 to −0.14], I2 = 79%) for intervention compared with comparator and was strongest for adjunctive CGM (−0.26% [−0.36, −0.16]). Overall TIR (absolute change) increased by 5.4% (3.5 to 7.2), I2 = 71% for CGM intervention compared with comparator and was strongest with non‐adjunctive CGM (6.0% [2.3, 9.7]). Conclusions: For individuals with T1D, use of CGM was beneficial for impacting glycaemic outcomes including HbA1c, TIR and time‐below‐range (TBR). Glycaemic improvement appeared greater for TIR for newer non‐adjunctive CGM technology. [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]

Aims: To investigate the experiences of parents caring for young children with type 1 diabetes type 1 diabetes using a do‐it‐yourself continuous glucose monitor (DIYrtCGM) in a supported setting. Methods: Exit interviews were conducted with parents from 11 families at the end of the MiaoMiao study: a randomised cross‐over trial focusing on parental fear of hypoglycaemia. Technical support was provided to participants while using DIYrtCGM during the trial. A convenience sampling approach was used to recruit parents. An in‐depth, semi‐structured interview approach was used. Thematic analysis was used to identify key themes and subthemes. Results: Parents identified that remote monitoring enabled proactive management and that overall alarms/glucose alerts were useful. Some parents reported reductions in anxiety, increased independence for their child, and improvements in the child–parent relationship. However, parents also reported regular signal loss with DIYrtCGM, along with complicated apps and challenges troubleshooting technical problems. Despite this, nine of the 11 families continued to use the system after the end of the trial. Conclusions: Do‐it‐yourself continuous glucose monitoring (CGM) was on balance beneficial for the parents interviewed. However, while access to CGM shifted the burden of care experienced by parents, burden did not significantly reduce for all parents, as the improved glycaemic control that they achieved was accompanied with the responsibility for continually monitoring their child's data. Supported use of do‐it‐yourself CGM may be an achievable, cost‐effective option for parents caring for children with type 1 diabetes in countries without funded access to CGM. [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]

Introduction Manual determination of insulin dosing largely fails to optimise glucose control in type 1 diabetes. Automated insulin delivery via closed-loop systems has improved glucose control in short-term studies. The objective of the present study is to determine the effectiveness of 6 months' closed-loop compared with manually determined insulin dosing on time-in-target glucose range in adults with type 1 diabetes. Methods and analysis This open-label, seven-centre, randomised controlled parallel group clinical trial will compare home-based hybrid closed-loop versus standard diabetes therapy in Australia. Adults aged ≥25 years with type 1 diabetes using intensive insulin therapy (via multiple daily injections or insulin pump, total enrolment target n=120) will undertake a run-in period including diabetes and carbohydrate-counting education, clinical optimisation and baseline data collection. Participants will then be randomised 1:1 either to 26 weeks of MiniMed 670G hybrid closed-loop system therapy (Medtronic, Northridge, CA, USA) or continuation of their current diabetes therapy. The hybrid closed-loop system delivers insulin automatically to address basal requirements and correct to target glucose level, while bolus doses for meals require user initiation and carbohydrate estimation. Analysis will be intention to treat, with the primary outcome time in continuous glucose monitoring (CGM) target range (3.9-10.0 mmol/L) during the final 3 weeks of intervention. Secondary outcomes include: other CGM parameters, HbA1c, severe hypoglycaemia, psychosocial well-being, sleep, cognition, electrocardiography, costs, quality of life, biomarkers of vascular health and hybrid closed-loop system performance. Semistructured interviews will assess the expectations and experiences of a subgroup of hybrid closed-loop users. Ethics and dissemination The study has Human Research Ethics Committee approval. The study will be conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. Results will be disseminated at scientific conferences and via peer-reviewed publications. Trial registration number ACTRN12617000520336; Pre-results. [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]

Aims Methods Results Conclusions To identify from a parental perspective facilitators and barriers of effective implementation of advanced hybrid closed‐loop (AHCL) therapy in children and adolescents with type 1 diabetes (T1D) with elevated glycaemia.Semi‐structured interviews were conducted with parents of participants while in a post‐trial extension phase of the CO‐PILOT randomized controlled trial. The Capability, Opportunity, Motivation, Behaviour Model and Theoretical Domain Framework informed the interviews and framework analysis.Eleven parents of 9 children and adolescents were interviewed. The median age of their children and adolescents was 14.2 years (IQR 13.3–14.7) with median HbA1c 78 mmol/mol (IQR 75–86) (9.3% IQR 9–10) before starting AHCL. Facilitators of implementing AHCL therapy included the following: (1) knowledge acquired from training, (2) establishing routines and action plans, (3) remote glucose monitoring, (4) achievement of glycaemic goals through automation, (5) children/adolescents' capability to use AHCL independently, (6) improved outcomes incentivized continued AHCL, (7) optimism about sustained improvements and (8) social support from healthcare providers, school staff, peers and parents. Barriers to AHCL implementation included the following: (1) challenges with device usability, (2) need for technical support, (3) forgotten knowledge and skills, (4) non‐adherence to best practices, (5) negative social influences, (6) physical and psychosocial burden and (7) negative emotions.This study provides comprehensive insights into parental perspectives of influences on implementing AHCL therapy in children and adolescents with elevated glycaemia. As parents remain key partners in diabetes care, these findings inform successful implementation of AHCL and development of future diabetes technology. [ABSTRACT FROM AUTHOR]

Less than 20% of Australians with type 1 diabetes (T1D) meet recommended glucose targets. Technology use is associated with better glycaemia, with the most advanced being automated insulin delivery (AID) systems, which are now recommended as gold-standard T1D care. Our Australian AID trial shows a wide spectrum of adults with T1D can achieve recommended targets. Other studies, including lived experience data, are supportive. Insulin pumps are not subsidised for most Australian adults with T1D. We advocate change., (© 2024 Royal Australasian College of Physicians.)

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society.)

Background: Continuous glucose monitoring (CGM) improves glycaemia for people affected by type 1 diabetes (T1D), but is not funded in Aotearoa/New Zealand. This study explores the impact of non-funded CGM on equity of access and associated glycaemic outcomes., Methods: Cross-sectional population-based study collected socio-demographic (age, gender, prioritised ethnicity, socioeconomic status) and clinical data from all regional diabetes centres in New Zealand with children <15 years with T1D as of 1st October 2021. De-identified data were obtained from existing databases or chart review. Outcomes compared socio-demographic characteristics between those using all forms of CGM and self-monitoring of blood glucose (SMBG), and association with HbA1c., Findings: 1209 eligible children were evaluated: 70.2% European, 18.1% Māori, 7.1% Pacific, 4.6% Asian, with even distribution across socioeconomic quintiles. Median HbA1c was 64 mmol/mol (8.0%), 40.2% utilised intermittently scanned (is)CGM, and 27.2% real-time (rt)CGM. CGM utilisation was lowest with Pacific ethnicity (38% lower than Māori) and the most deprived socioeconomic quintiles (quintile 5 vs. 1 adjusted RR 0.69; 95% CI, 0.57 to 0.84). CGM use was associated with regional diabetes centre (P < 0.001). The impact of CGM use on HbA1c differed by ethnicity: Māori children had the greatest difference in HbA1c between SMBG and rtCGM (adjusted difference -15.3 mmol/mol; 95% CI, -21.5 to -9.1), with less pronounced differences seen with other ethnicities., Interpretation: Inequities in CGM use exist based on prioritised ethnicity and socioeconomic status. Importantly, CGM was independently associated with lower HbA1c, suggesting that lack of CGM funding contributes to health disparity in children with T1D., Funding: Australasian Paediatric Endocrine Group (APEG), Canterbury Medical Research Foundation, Starship Foundation., Competing Interests: MB has received research grants from the 10.13039/501100001505Health Research Council of New Zealand and 10.13039/501100020473Australasian Paediatric Endocrine Group. HD has no conflicts of interest to declare. CJ, RP, BW, and EW are named investigators and MdB is a named Principal Investigator on the Australasian Paediatric Endocrine Group grant provided for this study. RP has received research grants from the 10.13039/501100001505Health Research Council of New Zealand, Lotteries, 10.13039/501100001515Cure Kids, 10.13039/100011367Royal New Zealand College of General Practitioners, 10.13039/501100001529Waikato Medical Research Foundation, and 10.13039/100010061University of Waikato. RP has received educational honoraria from Eli Lilly, Boehringer Ingelheim, Novo Nordisk, Astra Zeneca, Sanofi, Novartis, and Blue Horizons. RP is on the Eli Lilly New Zealand Medical Advisory Board. RP is an Executive Member of the New Zealand Society for the Study of Diabetes, Ministry of Health Expert Diabetes Advisory Group Member, Royal Australasian College of Physicians Adult General Medicine Committee member, and Convener of the New Zealand Diabetes Guidance Group. RP was previously president of the New Zealand Society of Endocrinology. BW has received research grants and equipment from Medtronic, 10.13039/100015769Dexcom, and iSENS. JW is a named investigator on research grants received from the 10.13039/501100001505Health Research Council of New Zealand, 10.13039/501100001530Canterbury Medical Research Foundation, 10.13039/100015769Dexcom, 10.13039/501100001563Otago Medical Research Foundation, National Science Challenge, the 10.13039/100014144Rea Charitable Trust. JW has had research contracts with the Ministry of Health, New Zealand, and the Health Quality and Safety Commission, New Zealand with payments made to his employer/institution, the University of Otago. YA is Chairperson of the Tamariki Pakari Child Health and Wellbeing Trust. MdB has received research grants from 10.13039/100015769Dexcom and Medtronic, and research equipment from Dexcom, Medtronic, and Ypsomed. MdB has received honoraria from Medtronic, Ypsomed, and Dexcom., (© 2022 The Authors.)

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.)

Background: The literature regarding flash glucose monitoring (FGM)-associated cutaneous adverse events (AE) is limited., Objectives: This study among youth participating in a 6 month randomized controlled trial aimed to compare cutaneous AE between FGM and self-monitored blood glucose (SMBG) use and evaluate premature FGM sensor loss., Methods: Patients aged 13 to 20 years with type 1 diabetes were randomized to intervention (FGM and usual care) or control (SMBG and usual care). Participants self-reported cutaneous AEs electronically every 14 days. Reports were analyzed to determine frequency, type, and severity of cutaneous AEs, and evaluate premature sensor loss., Results: Sixty-four participants were recruited; 33 randomized to FGM and 31 to control. In total, 80 cutaneous AEs were reported (40 in each group); however, the proportion of participants experiencing cutaneous AEs was greater in the FGM group compared to control (58% and 23% respectively, P = .004). FGM participants most frequently reported erythema (50% of AEs), while controls most commonly reported skin hardening (60% of AEs). For FGM users, 80.0% of cutaneous AEs were mild, 17.5% moderate, and 2.5% severe. Among controls, 82.5% of cutaneous AEs were mild and 17.5% moderate. One participant ceased using FGM due to recurring cutaneous AEs. Additionally, over 6 months, 82% of FGM participants experienced at least one premature sensor loss, largely unrelated to a cutaneous AE., Conclusions: Cutaneous FGM-associated AEs are common, and mostly rated as mild. However, the majority of users continued FGM despite cutaneous AEs. Awareness of cutaneous complications and mitigation measures may reduce cutaneous AEs and improve the overall experience of FGM., (© 2020 John Wiley & Sons A/S . Published by John Wiley & Sons Ltd.)

Background: MiaoMiao (MM) is a Bluetooth transmitter, which when paired with a smart phone/device, converts the Abbott FreeStyle Libre flash glucose monitoring system into a Do-It-Yourself (DIY) continuous glucose monitor (CGM). Families are increasingly adopting DIY CGM solutions, but little is known about parent and child experiences with these add-on technologies. We aimed to explore experiences of families using MM-CGM including challenges faced and their advice to others who may choose to use the technology., Methods: Between May and July 2019, we conducted 12 semistructured interviews (in person or via video conference) with parents of children (aged ≤16 years) with type 1 diabetes using MM-CGM. Interviews were audio recorded; professionally transcribed and key themes were identified through thematic analysis., Results: Overall, parents used MM-CGM to proactively manage their child's blood glucose. In all participants, this led to a perceived decrease in frequency of hypoglycemia. Participants reported that the visibility and easy access to blood glucose readings, glucose trends, and customized alarms on parent's phones decreased their disease burden and improved their sleep quality. Common barriers to using MM-CGM included difficulty of the setting up process, connectivity issues, and lack of support from medical teams., Conclusion: This study highlights the potential feasibility of using a DIY CGM system like MM-CGM, which could be an empowering and cost-effective tool for enabling remote monitoring of blood glucose in real time.