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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]

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]

Background: Stimulated C‐peptide measurement after a mixed meal tolerance test (MMTT) is the accepted gold standard for assessing residual beta‐cell function in type 1 diabetes (T1D); however, this approach is impractical outside of clinical trials. Objective: To develop an improved estimate of residual beta‐cell function in children with T1D using commonly measured clinical variables. Subjects/Methods: A clinical model to predict 90‐minute MMTT stimulated C‐peptide in children with recent‐onset T1D was developed from the combined AbATE, START, and TIDAL placebo subjects (n = 46) 6 months post‐recruitment using multiple linear regression. This model was then validated in a clinical cohort (Hvidoere study group, n = 262). Results: A model of estimated C‐peptide at 6 months post‐diagnosis, which included age, gender, body mass index (BMI), hemoglobin A1c (HbA1c), and insulin dose predicted 90‐minute stimulated C‐peptide measurements (adjusted R2 = 0.63, P < 0.0001). The predictive value of insulin dose and HbA1c alone (IDAA1c) for 90‐minute stimulated C‐peptide was significantly lower (R2 = 0.37, P < 0.0001). The slopes of linear regression lines of the estimated and stimulated 90‐minute C‐peptide levels obtained at 6 and 12 months post diagnosis in the Hvidoere clinical cohort were R2 = 0.36, P < 0.0001 at 6 months and R2 = 0.37, P < 0.0001 at 12 months. Conclusions: A clinical model including age, gender, BMI, HbA1c, and insulin dose predicts stimulated C‐peptide levels in children with recent‐onset T1D. Estimated C‐peptide is an improved surrogate to monitor residual beta‐cell function outside clinical trial settings. [ABSTRACT FROM AUTHOR]

Correction to: Acta Diabetologica https://doi.org/10.1007/s00592-023-02113-z "Australasian Diabetes Data Network Study Group" should be listed as named authors in the author group. In B Australasian Diabetes Data Network (ADDN) Study Group members: b Jenny Batch should be Professor Jenny Batch. [Extracted from the article]

Objectives: Glycaemic control in children and adolescents with type 1 diabetes mellitus can be challenging, complex and influenced by many factors. This study aimed to identify patient characteristics that were predictive of satisfactory glycaemic control in the paediatric population using a logistic regression mixed-effects (population) modelling approach. Methods: The data were obtained from 288 patients aged between 1 and 22 years old recorded retrospectively over 3 years (1852 HbA1c observations). HbA1c status was categorised as ‘satisfactory’ or ‘unsatisfactory’ glycaemic control, using an a priori cut-off value of HbA1c ≥ 9% (75 mmol/mol), as used routinely by the hospital’s endocrine paediatricians. Patients’ characteristics were tested as covariates in the model as potential predictors of glycaemic control. Results: There were three patient characteristics identified as having a significant influence on glycaemic control: HbA1c measurement at the beginning of the observation period (Odds Ratio (OR) = 0.30 per 1% HbA1c increase, 95% confidence interval (CI) = 0.20–0.41); Age (OR = 0.88 per year increase, 95% CI = 0.80–0.94), and fractional disease duration (disease duration/age, OR = 0.80 per 0.10 increase, 95% CI = 0.66–0.93) were collectively identified as factors contributing significantly to lower the probability of satisfactory glycaemic control. Conclusions: The study outcomes may prove useful for identifying paediatric patients at risk of having unsatisfactory glycaemic control, and who could require more extensive monitoring, support, or targeted interventions. [ABSTRACT FROM AUTHOR]

The authors discuss the need for adult and paediatric diabetologists to strive to assist patients to exert effort to improve glycaemic control. The authors note the response of the paediatric diabetology community in Australasia which calls for children and adolescents with diabetes to be treated with intensive management, with the goal to better long-term outcomes. Also investigated is the survey made to specialised centres which manage children and adolescents in Australia.