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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]

Aims: To survey the national workforce that manages children and adolescents with type 1 diabetes (T1D) in Aotearoa New Zealand and compare with glycaemic outcomes for 2021. Methods: A representative from each tertiary and regional diabetes service in Aotearoa New Zealand was asked to participate in an online survey assessing health‐care professional (HCP) workforce numbers operating for the 2021 calendar year. Regional full‐time‐equivalent (FTE), glycaemic outcomes and population demographics were compared to a previously reported workforce surveys (2015 and 2019). Results: Seventeen sites responded – including all four large tertiary centres – serving >99% of children and adolescents with T1D in Aotearoa New Zealand. HCP resourcing varied across sites, with median (range) HCP/100 patient ratios of: doctors: 0.40 (0.16–1.11), nurses: 1.19 (0.29–5.56), dietitians: 0.25 (0–1.11) and psychologist/social workers: 0 (0–0.26). No site met all of the International Society of Paediatric and Adolescent Diabetes (ISPAD) recommendations of HCP/100 patient ratios. Measures of socio‐economic deprivation predicted HbA1c, rather than the diabetes clinic attended. Overall, only 15.1% (240/1585) of patients had an HbA1c less than the recommended 53 mmol/mol. Conclusions: The Aotearoa New Zealand workforce for children and adolescents with T1D is under‐resourced and no site meets the ISPAD recommendations. There has been no significant increase in HCP/100 patient ratios compared to previous workforce surveys over the last decade. Few children and adolescents with T1D meet the recommended HbA1c. Resourcing according to recommended clinical need is required if equity in outcomes for young people with T1D is to be addressed. [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]

Aims: In many countries, real‐time continuous glucose monitoring (rt‐CGM) is not funded, and cost presents a barrier to access. A do‐it‐yourself conversion of intermittently scanned CGM (DIY‐CGM) is a cheaper alternative. This qualitative study aimed to explore user experiences with DIY‐CGM in people aged 16 to 69 years with type 1 diabetes (T1D). Methods: Convenience sampling was used to recruit participants for semi‐structured virtual interviews exploring experiences of DIY‐CGM use. Participants were recruited after completing the intervention arm of a crossover randomised controlled trial that evaluated DIY‐CGM versus intermittently scanned CGM (isCGM). Participants were previously naive to DIY‐CGM and rt‐CGM but not isCGM. The DIY‐CGM intervention consisted of a Bluetooth bridge connected to isCGM, adding rt‐CGM functionality over 8 weeks. Interviews were transcribed, then thematic analysis was performed. Results: Interviews were with 12 people aged 16 to 65 years, with T1D: mean age ± SD 43 ± 14 years; baseline mean HbA1c ± SD 60 mmol/mol ± 9.9 (7.6 ± 0.9%) and time in range 59.8% ± 14.8%. Participants perceived that using DIY‐CGM improved both glycaemic control and aspects of quality of life. Alarm and trend functionality allowed participants to perceive reduced glycaemic variability overnight and following meals. The addition of a smartwatch increased discrete access to glucose information. There was a high degree of trust in DIY‐CGM. Challenges while using DIY‐CGM included signal loss during vigorous exercise, alarm fatigue and short battery life. Conclusions: This study suggests that for users, DIY‐CGM appears to be an acceptable alternative method of rt‐CGM. [ABSTRACT FROM AUTHOR]

Aim: To determine low‐density lipoprotein cholesterol (LDL‐C) screening frequency and levels, and factors associated with elevated LDL‐C, in Australasian youth with type 1 diabetes (T1D). Methods: Data were extracted from the Australasian Diabetes Data Network (ADDN), a prospective clinical quality registry, on all T1D healthcare visits attended by young people aged 16–25 years (with T1D duration of >1 year) between January 2011 and December 2020. The primary outcomes were elevated LDL‐C > 2.6 mmol/L (100 mg/dL) and threshold for treatment: >3.4 mmol/L (130 mg/dL), according to consensus guidelines. Multivariable Generalised Estimated Equations (GEE) were used to examine factors associated with elevated LDL‐C across all visits. Results: A cohort of 6338 young people (52.6% men) were identified, of whom 1603 (25.3%) had ≥1 LDL‐C measurement documented. At last measurement, mean age, age at T1D diagnosis and T1D duration were 18.3 ± 2.4, 8.8 ± 4.5 and 8.9 ± 4.8 years, respectively. LDL‐C was elevated in 737 (46.0%) and at the treatment threshold in 250 (15.6%). In multivariable GEE elevated LDL‐C continuously was associated with older age (OR = 0.07; 0.01–0.13, p = 0.02), female sex (OR = 0.31; 0.18–0.43; p < 0.001), higher HbA1c (OR = 0.04; 0.01–0.08; p = 0.01) and having an elevated BMI (OR = 0.17, 0.06–0.39, p < 0.001). Conclusions: LDL‐C screening and levels are suboptimal in this cohort, increasing future cardiovascular complication risk. There is an urgent need to understand how healthcare services can support improved screening and management of dyslipidaemia in this population. [ABSTRACT FROM AUTHOR]

Aim: To compare HbA1c and clinical outcomes in adolescents and young adults with type 1 diabetes (T1D), with or without celiac disease (CD). Methods: Longitudinal data were extracted from ADDN, a prospective clinical diabetes registry. Inclusion criteria were T1D (with or without CD), ≥ 1 HbA1c measurement, age 16–25 years and diabetes duration ≥ 1 year at last measurement. Multivariable Generalised Estimated Equation models were used for longitudinal analysis of variables associated with HbA1c. Results: Across all measurements, those with coexisting T1D and CD had lower HbA1c when compared to those with T1D alone (8.5 ± 1.5% (69.4 ± 16.8 mmol/mol) vs. 8.7 ± 1.8% (71.4 ± 19.8 mmol/mol); p < 0.001); lower HbA1c was associated with shorter diabetes duration (B = − 0.06; 95% CI − 0.07 to − 0.05; p < 0.001), male sex (B = − 0.24; − 0.36 to − 0.11; p < 0.001), insulin pump therapy use (B = − 0.46; − 0.58 to − 0.34; p < 0.001), coexistence of T1D and CD (B = − 0.28; − 0.48 to − 0.07; p = 0.01), blood pressure (B = − 0.16; − 0.23 to − 0.09; p < 0.001) and body mass index (B = -− 0.03; − 0.02 to − 0.04; p = 0.01) in the normal range. At last measurement, 11.7% of the total population had a HbA1c < 7.0% (53.0 mmol/mol). Conclusions: Across all measurements, coexisting T1D and CD is associated with lower HbA1c when compared to T1D alone. However, HbA1c is above target in both groups. [ABSTRACT FROM AUTHOR]