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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]

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]

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]

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]

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]

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.)

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.)