Australasian Diabetes Data Network: Building a Collaborative Resource

Demographic, Clinical, Management, and Outcome Characteristics of 8,004 Young Children With Type 1 Diabetes

OBJECTIVE

To compare demographic, clinical, and therapeutic characteristics of children with type 1 diabetes age <6 years across three international registries: Diabetes Prospective Follow-Up Registry (DPV; Europe), T1D Exchange Quality Improvement Network (T1DX-QI; U.S.), and Australasian Diabetes Data Network (ADDN; Australasia).

RESEARCH DESIGN AND METHODS

An analysis was conducted comparing 2019-2021 prospective registry data from 8,004 children.

RESULTS

Mean ± SD ages at diabetes diagnosis were 3.2 ± 1.4 (DPV and ADDN) and 3.7 ± 1.8 years (T1DX-QI). Mean ± SD diabetes durations were 1.4 ± 1.3 (DPV), 1.4 ± 1.6 (T1DX-QI), and 1.5 ± 1.3 years (ADDN). BMI z scores were in the overweight range in 36.2% (DPV), 41.8% (T1DX-QI), and 50.0% (ADDN) of participants. Mean ± SD HbA1c varied among registries: DPV 7.3 ± 0.9% (56 ± 10 mmol/mol), T1DX-QI 8.0 ± 1.4% (64 ± 16 mmol/mol), and ADDN 7.7 ± 1.2% (61 ± 13 mmol/mol). Overall, 37.5% of children achieved the target HbA1c of <7.0% (53 mmol/mol): 43.6% in DPV, 25.5% in T1DX-QI, and 27.5% in ADDN. Use of diabetes technologies such as insulin pump (DPV 86.6%, T1DX 46.6%, and ADDN 39.2%) and continuous glucose monitoring (CGM; DPV 85.1%, T1DX-QI 57.6%, and ADDN 70.5%) varied among registries. Use of hybrid closed-loop (HCL) systems was uncommon (from 0.5% [ADDN] to 6.9% [DPV]).

CONCLUSIONS

Across three major registries, more than half of children age <6 years did not achieve the target HbA1c of <7.0% (53 mmol/mol). CGM was used by most participants, whereas insulin pump use varied across registries, and HCL system use was rare. The differences seen in glycemia and use of diabetes technologies among registries require further investigation to determine potential contributing factors and areas to target to improve the care of this vulnerable group.

Correlation between centre size, metabolic variation and mean HbA1c in major paediatric diabetes centres

AIM

To exploit a relatively homogeneous national health care context and a national diabetes database to address the questions: Is there an optimal clinic/centre size in determining outcomes?; and Can improvement in median centre outcomes be driven by reducing variability in outcome?

METHODS

Using the Australasian Diabetes Database Network, data from seven tertiary hospital paediatric diabetes clinics for patients with type one diabetes from Australia were recorded from 6-month uploads: September 2017, March 2018, September 2018 and March 2019. Data from 25 244 patient visits included demographic variables, HbA1C, number of patient visits and insulin regimens.

RESULTS

There was no association between centre size and median HbA1C. On the other hand, there was a significant association between or median absolute deviation of HbA1C outcomes and the median HbA1C result between centres. On average every two thirds of a median absolute deviation increase in clinic HbA1C was associated with a 1.0% (10.9 mmol/mol) increase in median clinic HbA1C.

CONCLUSIONS

Our data have shown that it is likely difficult for centres to have a low median HbA1C if there is high variance of HbA1C's within centres or within centre treatment groups. This appears to be true regardless of centre size. These findings need to be carefully considered by teams who wish to lower their clinic median HbA1C.

Improved Glycemic Outcomes With Diabetes Technology Use Independent of Socioeconomic Status in Youth With Type 1 Diabetes

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.

Socioeconomic status and diabetes technology use in youth with type 1 diabetes: a comparison of two funding models

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.

Blood pressure in adolescents and young adults with type 1 diabetes: data from the Australasian Diabetes Data Network registry

AIM

Hypertension increases complication risk in type 1 diabetes (T1D). We examined blood pressure (BP) in adolescents and young adults with T1D from the Australasian Diabetes Data Network, a prospective clinical diabetes registry in Australia and New Zealand.

METHODS

This was a longitudinal study of prospectively collected registry data.

INCLUSION CRITERIA

T1D (duration ≥ 1 year) and age 16-25 years at last visit (2011-2020). Hypertension was defined as (on ≥ 3 occasions) systolic BP and/or diastolic BP > 95^th percentile for age < 18 years, and systolic BP > 130 and/or diastolic BP > 80 mmHg for age ≥ 18 years. Multivariable Generalised Estimating Equations were used to examine demographic and clinical factors associated with BP in the hypertensive range across all visits.

RESULTS

Data from 6338 young people (male 52.6%) attending 24 participating centres across 36,655 T1D healthcare visits were included; 2812 (44.4%) had BP recorded at last visit. Across all visits, 19.4% of youth aged < 18 years and 21.7% of those aged ≥ 18 years met criteria for hypertension. In both age groups, BP in the hypertensive range was associated with male sex, injection (vs. pump) therapy, higher HbA1c, and higher body mass index.

CONCLUSIONS

There is a high proportion of adolescents and young adults reported with BP persistently in hypertensive ranges. Findings flag the additive contribution of hypertension to the well-established body of evidence indicating a need to review healthcare models for adolescents and young adults with T1D.

A GDPR-Compliant Dynamic Consent Mobile Application for the Australasian Type-1 Diabetes Data Network

Australia has a high prevalence of diabetes, with approximately 1.2 million Australians diagnosed with the disease. In 2012, the Australasian Diabetes Data Network (ADDN) was established with funding from the Juvenile Diabetes Research Foundation (JDRF). ADDN is a national diabetes registry which captures longitudinal information about patients with type-1 diabetes (T1D). Currently, the ADDN data are directly contributed from 42 paediatric and 17 adult diabetes centres across Australia and New Zealand, i.e., where the data are pre-existing in hospital systems and not manually entered into ADDN. The historical data in ADDN have been de-identified, and patients are initially afforded the opportunity to opt-out of being involved in the registry; however, moving forward, there is an increased demand from the clinical research community to utilise fully identifying data. This raises additional demands on the registry in terms of security, privacy, and the nature of patient consent. General Data Protection Regulation (GDPR) is an increasingly important mechanism allowing individuals to have the right to know about their health data and what those data are being used for. This paper presents a mobile application being designed to support the ADDN data collection and usage processes and aligning them with GDPR. The app utilises Dynamic Consent-an informed specific consent model, which allows participants to view and modify their research-driven consent decisions through an interactive interface. It focuses specifically on supporting dynamic opt-in consent to both the registry and to associated sub-projects requesting access to and use of the patient data for research purposes.

Glycaemic outcomes in Australasian children and adults with type 1 diabetes: failure to meet targets across the age spectrum

BACKGROUND

The goal of therapy in type 1 diabetes (T1D) is to achieve optimal glycaemic targets and reduce complications. Robust data representing glycaemic outcomes across the lifespan are lacking in Australasia.

AIMS

To examine contemporary glycaemic outcomes and rate of use of diabetes technologies in Australasian people with T1D.

METHODS

Cross-sectional analysis of de-identified data from 18 diabetes centres maintained in the Australasian Diabetes Data Network registry during 2019. Glycaemia was measured using glycated haemoglobin (HbA1c). The proportion of people with T1D achieving the international HbA1c target of <53 mmol/mol (7%) was calculated. Rates of continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) use were determined.

RESULTS

A total of 7988 individuals with T1D with 30 575 visits were recorded in the registry. The median (interquartile range) age was 15.3 (10.0) years and diabetes duration was 5.7 (9.4) years with 49% on multiple daily injections (MDI) and 36% on CSII. The mean HbA1c for the whole cohort was 66 mmol/mol (8.2%). HbA1c increased with age, from 60 mmol/mol (7.6%) in children <10 years, increasing during adolescence and peaking at 73 mmol/mol (8.8%) in the 20-25 years age group. The HbA1c target of <53 mmol/mol (7%) was met in 18% of children and 13% of adults. HbA1c was lower on CSII as compared with those on MDI (P < 0.0001).

CONCLUSIONS

Only a minority of children and adults achieve the recommended glycaemic goals despite access to specialist care in major diabetes centres. There is a need to identify factors that improve glycaemic outcomes.

Diabetic Ketoacidosis at Onset of Type 1 Diabetes and Long-term HbA1c in 7,961 Children and Young Adults in the Australasian Diabetes Data Network

OBJECTIVE

The relationship between diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes and long-term glycemic control varies between studies. We aimed, firstly, to characterize the association of DKA and its severity with long-term HbA1c in a large contemporary cohort, and secondly, to identify other independent determinants of long-term HbA1c.

RESEARCH DESIGN AND METHODS

Participants were 7,961 children and young adults diagnosed with type 1 diabetes by age 30 years from 2000 to 2019 and followed prospectively in the Australasian Diabetes Data Network (ADDN) until 31 December 2020. Linear mixed-effect models related variables to HbA1c.

RESULTS

DKA at diagnosis was present in 2,647 participants (33.2%). Over a median 5.6 (interquartile range 3.2, 9.4) years of follow-up, participants with severe, but not moderate or mild, DKA at diagnosis had a higher mean HbA1c (+0.23%, 95% CI 0.11,0.28; [+2.5 mmol/mol, 95% CI 1.4,3.6]; P < 0.001) compared with those without DKA. Use of continuous subcutaneous insulin infusion (CSII) was independently associated with a lower HbA1c (-0.28%, 95% CI -0.31, -0.25; [-3.1 mmol/mol, 95% CI -3.4, -2.8]; P < 0.001) than multiple daily injections, and CSII use interacted with severe DKA to lower predicted HbA1c. Indigenous status was associated with higher HbA1c (+1.37%, 95% CI 1.15, 1.59; [+15.0 mmol/mol, 95% CI 12.6, 17.4]; P < 0.001), as was residing in postcodes of lower socioeconomic status (most vs. least disadvantaged quintile +0.43%, 95% CI 0.34, 0.52; [+4.7 mmol/mol, 95% CI 3.4, 5.6]; P < 0.001).

CONCLUSIONS

Severe, but not mild or moderate, DKA at diagnosis was associated with a marginally higher HbA1c over time, an effect that was modified by use of CSII. Indigenous status and lower socioeconomic status were independently associated with higher long-term HbA1c.

Decreased occurrence of ketoacidosis and preservation of beta cell function in relatives screened and monitored for type 1 diabetes in Australia and New Zealand

AIMS

Islet autoantibody screening of infants and young children in the Northern Hemisphere, together with semi-annual metabolic monitoring, is associated with a lower risk of ketoacidosis (DKA) and improved glucose control after diagnosis of clinical (stage 3) type 1 diabetes (T1D). We aimed to determine if similar benefits applied to older Australians and New Zealanders monitored less rigorously.

METHODS

DKA occurrence and metabolic control were compared between T1D relatives screened and monitored for T1D and unscreened individuals diagnosed in the general population, ascertained from the Australasian Diabetes Data Network.

RESULTS

Between 2005 and 2019, 17,105 relatives (mean (SD) age 15.7 (10.8) years; 52% female) were screened for autoantibodies against insulin, glutamic acid decarboxylase, and insulinoma-associated protein 2. Of these, 652 screened positive to a single and 306 to multiple autoantibody specificities, of whom 201 and 215, respectively, underwent metabolic monitoring. Of 178 relatives diagnosed with stage 3 T1D, 9 (5%) had DKA, 7 of whom had not undertaken metabolic monitoring. The frequency of DKA in the general population was 31%. After correction for age, sex and T1D family history, the frequency of DKA in screened relatives was >80% lower than in the general population. HbA1c and insulin requirements following diagnosis were also lower in screened relatives, consistent with greater beta cell reserve.

CONCLUSIONS

T1D autoantibody screening and metabolic monitoring of older children and young adults in Australia and New Zealand, by enabling pre-clinical diagnosis when beta cell reserve is greater, confers protection from DKA. These clinical benefits support ongoing efforts to increase screening activity in the region and should facilitate the application of emerging immunotherapies.

A collaborative comparison of international pediatric diabetes registries

BACKGROUND

An estimated 1.1 million children and adolescents aged under 20 years have type 1 diabetes worldwide. Principal investigators from seven well-established longitudinal pediatric diabetes registries and the SWEET initiative have come together to provide an international collaborative perspective and comparison of the registries.

WORK FLOW

Information and data including registry characteristics, pediatric participant clinical characteristics, data availability and data completeness from the Australasian Diabetes Data Network (ADDN), Danish Registry of Childhood and Adolescent Diabetes (DanDiabKids), Diabetes prospective follow-up registry (DPV), Norwegian Childhood Diabetes Registry (NCDR), National Paediatric Diabetes Audit (NPDA), Swedish Childhood Diabetes Registry (Swediabkids), T1D Exchange Quality Improvement Collaborative (T1DX-QI), and the SWEET initiative was extracted up until 31 December 2020.

REGISTRY OBJECTIVES AND OUTCOMES

The seven diabetes registries and the SWEET initiative collectively show data of more than 900 centers and around 100,000 pediatric patients, the majority with type 1 diabetes. All share the common objectives of monitoring treatment and longitudinal outcomes, promoting quality improvement and equality in diabetes care and enabling clinical research. All generate regular benchmark reports. Main differences were observed in the definition of the pediatric population, the inclusion of adults, documentation of CGM metrics and collection of raw data files as well as linkage to other data sources. The open benchmarking and access to regularly updated data may prove to be the most important contribution from registries. This study describes aspects of the registries to enable future collaborations and to encourage the development of new registries where they do not exist.

Suboptimal glycemic control in adolescents and young adults with type 1 diabetes from 2011 to 2020 across Australia and New Zealand: Data from the Australasian Diabetes Data Network registry

BACKGROUND

Competing challenges in adolescence and young adulthood can distract from optimal type 1 diabetes (T1D) self-management, and increase risks of premature morbidity and mortality. There are limited data mapping the glycemic control of people with T1D in this age group, across Australasia.

RESEARCH DESIGN AND METHODS

Clinical data were extracted from the Australasian Diabetes Data Network, a prospective clinical diabetes registry. Inclusion criteria were individuals with T1D aged 16-25 years at their last recorded T1D healthcare visit (from 1st January 2011 to 31st December 2020), with T1D duration of at least 1 year. Data were stratified by two last recorded T1D healthcare visit ranges, while generalized estimated equation (GEE) modeling was used to examine factors associated with HbA1c across visits during the 10 year period.

RESULTS

Data from 6329 young people (52.6% male) attending 24 diabetes centers across Australasia were included. At the last visit within the most recent 5 years, mean ± SD age was 18.5 ± 2.3 years, T1D duration was 8.8 ± 4.7 years and HbA1c was 8.8 ± 1.8% (72.2 ± 19.9 mmol/mol); only 12.3% had an HbA1c below the international target of <7.0% (53 mmol/mol). Across all T1D healthcare visits, in GEE modeling, higher HbA1c was associated with female sex (B = 0.20; 95% CI 0.12 to 0.29, p < 0.001), longer T1D duration (B = 0.04, 0.03 to 0.05, p < 0.001). Lower HbA1c was associated with attendance at a pediatric T1D healthcare setting (B = -0.33, -0.45 to -0.21, p < 0.001) and use of CSII versus BD/MDI therapy (B = -0.49, -0.59 to 0.40, p < 0.001).

CONCLUSIONS

This Australasian study demonstrates widespread and persistent sub-optimal glycemic control in young people with T1D, highlighting the urgent need to better understand how healthcare services can support improved glycemic control in this population.

Evaluation of real-life clinical outcomes in Australian youth with type 1 diabetes on hybrid closed-loop therapy: A retrospective study

AIM

To determine the clinical outcomes and evaluate the perspectives of children with Type 1 diabetes (T1D) and their parents managing their child on hybrid closed-loop (HCL) therapy.

METHODS

Children with T1D on HCL attending a tertiary diabetes centre between April 2019 and July 2021 were included. A retrospective analysis of glycaemic data was conducted to determine the clinical outcomes. Time spent in closed loop, time in target glucose range (TIR 3.9-10 mmol/L), hypoglycaemia and hyperglycaemia were collected at baseline, 4 weeks, 3 and 6 months post-HCL. User experience was assessed by questionnaires administered to parents of children with T1D.

RESULTS

Seventy-one children, mean (SD) age of 12.2 (3.2) years were commenced on HCL. Ten (14%) discontinued HCL use, with 60% discontinuing within the first 6 months. Glycaemic outcomes were analysed in 52 children. Time spent in closed loop was 78 (21) % at 4 weeks, declined to 69 (28) % at 3 months (P = 0.037) and 63 (34) % at 6 months (P = 0.001). The mean %TIR increased from 59.8 at baseline to 67.6 at 3 months and 65.6 at 6 months with a mean adjusted difference of 7.8% points [95% CI 3.6, 11.9] and 5.5% points [95% CI 1.4, 9.5], respectively. There was a reduction in time > 10 mmol/L and time < 3.9 mmol/L from baseline to 6 months. Although families faced challenges with technology, better glucose control with reduced glycaemic fluctuations were reported.

CONCLUSIONS

HCL therapy is associated with improved glycaemia; however, adequate support and education are required for best outcomes.

Universal Subsidized Continuous Glucose Monitoring Funding for Young People With Type 1 Diabetes: Uptake and Outcomes Over 2 Years, a Population-Based Study

OBJECTIVE

Continuous glucose monitoring (CGM) is increasingly used in type 1 diabetes management; however, funding models vary. This study determined the uptake rate and glycemic outcomes following a change in national health policy to introduce universal subsidized CGM funding for people with type 1 diabetes aged <21 years.

RESEARCH DESIGN AND METHODS

Longitudinal data from 12 months before the subsidy until 24 months after were analyzed. Measures and outcomes included age, diabetes duration, HbA1c, episodes of diabetic ketoacidosis and severe hypoglycemia, insulin regimen, CGM uptake, and percentage CGM use. Two data sources were used: the Australasian Diabetes Database Network (ADDN) registry (a prospective diabetes database) and the National Diabetes Service Scheme (NDSS) registry that includes almost all individuals with type 1 diabetes nationally.

RESULTS

CGM uptake increased from 5% presubsidy to 79% after 2 years. After CGM introduction, the odds ratio (OR) of achieving the HbA1c target of <7.0% improved at 12 months (OR 2.5, P < 0.001) and was maintained at 24 months (OR 2.3, P < 0.001). The OR for suboptimal glycemic control (HbA1c ≥9.0%) decreased to 0.34 (P < 0.001) at 24 months. Of CGM users, 65% used CGM >75% of time, and had a lower HbA1c at 24 months compared with those with usage <25% (7.8 ± 1.3% vs. 8.6 ± 1.8%, respectively, P < 0.001). Diabetic ketoacidosis was also reduced in this group (incidence rate ratio 0.49, 95% CI 0.33-0.74, P < 0.001).

CONCLUSIONS

Following the national subsidy, CGM use was high and associated with sustained improvement in glycemic control. This information will inform economic analyses and future policy and serve as a model of evaluation diabetes technologies.

Benchmarking care outcomes for young adults with type 1 diabetes in Australia after transition to adult care

AIM

To determine advantages conferred by a youth-specific transition clinic model for young adults with type 1 diabetes (T1D) at Westmead Hospital (WH) as compared with Australian registry data.

METHODS

Prospectively collected data included age, diabetes duration, visit frequency, post code, BMI, mode of insulin delivery, continuous glucose monitoring, HbA1c, albumin creatinine ratio, BP, retinopathy and diabetic ketoacidosis (DKA) for all WH T1D clinic attendees aged 16-25 between January 2017 and June 2018 (n = 269). Results were compared with data collected during the same time period from 2 separate Australian data registries, one longitudinal (Australasian Diabetes Data Network, ADDN) and one a spot survey (the Australian National Diabetes Audit, ANDA).

RESULTS

Across the three cohorts, HbA1c was similar (respectively, WH, ADDN, ANDA; 8.7%[72mmol/mol], 8.7%[72mmol/mol], 8.5%[69mmol/mol]) and HbA1c was significantly higher in young adults <21 years (8.7-8.9%[73-75mmol/mol]) as compared with ≥21 years (8.5%[69mmol/mol], p < .002). In the WH cohort, median interval between visits was shorter than in ADDN (4.5 vs. 9.0 months) and DKA was lower (respectively, 3.6 and 9.2/100 patient years; p < .001).

CONCLUSIONS

While suboptimal HbA1c was recorded in all centres, the WH model of care saw increased attendance and reduced admissions with DKA as compared with other Australian adult centres.

Hemoglobin A1c Patterns of Youth With Type 1 Diabetes 10 Years Post Diagnosis From 3 Continents

OBJECTIVES

Distinct hemoglobin A1c (HbA1c) trajectories during puberty are identified in youth with established type 1 diabetes (T1D). We used data from 3 international registries to evaluate whether distinct HbA1c trajectories occur from T1D onset.

METHODS

Participants were <18 years old at diagnosis with at least 1 HbA1c measured within 12 months post diagnosis, along with ≥3 duration-year-aggregated HbA1c values over 10 years of follow-up. Participants from the Australasian Diabetes Data Network (n = 7292), the German-Austrian-Luxembourgian-Swiss diabetes prospective follow-up initiative (Diabetes Patienten Verlaufsdokumentation) (n = 39 226) and the US-based Type 1 Diabetes Exchange Clinic Registry (n = 3704) were included. With group-based trajectory modeling, we identified unique HbA1c patterns from the onset of T1D.

RESULTS

Five distinct trajectories occurred in all 3 registries, with similar patterns of proportions by group. More than 50% had stable HbA1c categorized as being either low stable or intermediate stable. Conversely, ∼15% in each registry were characterized by stable HbA1c >8.0% (high stable), and ∼11% had values that began at or near the target but then increased (target increase). Only ∼5% of youth were above the target from diagnosis, with an increasing HbA1c trajectory over time (high increase). This group differed from others, with higher rates of minority status and an older age at diagnosis across all 3 registries (P ≤ .001).

CONCLUSIONS

Similar postdiagnostic HbA1c patterns were observed across 3 international registries. Identifying the youth at the greatest risk for deterioration in HbA1c over time may allow clinicians to intervene early, and more aggressively, to avert increasing HbA1c.

Type 2 diabetes in children and adolescents across Australia and New Zealand: A 6-year audit from The Australasian Diabetes Data Network (ADDN)

OBJECTIVES

To assess the clinical and demographic characteristics of children and adolescents across Australia and New Zealand (NZ) with type 2 diabetes.

METHODS

We performed a descriptive audit of data prospectively reported to the Australasian Diabetes Data Network (ADDN) registry. Data were collected from six tertiary pediatric diabetes centers across Australia (New South Wales, Queensland, South Australia, Western Australia, and Victoria) and NZ (Auckland). Children and adolescents diagnosed with type 2 diabetes aged ≤ 18 years with data reported to ADDN between 2012 and 2017 were included. Age, sex, ethnicity, HbA1c, blood pressure, BMI, waist circumference and lipid profile at first visit were assessed.

RESULTS

There were 269 cases of type 2 diabetes in youth reported to ADDN between 2012 and 2017. The most common ethnicities were Indigenous Australian in 56/243 (23%) and NZ Maori or Pacifica in 47 (19%). Median age at diagnosis was 13.7 years and 94% of participants were overweight or obese. Indigenous Australian and Maori/Pacifica children were younger at diagnosis compared with nonindigenous children: median 13.3 years (indigenous Australian); 13.1 years (Maori/Pacifica); 14.1 years (nonindigenous), p = 0.005. HbA1c was higher in indigenous Australian (9.4%) and Maori/Pacifica youth (7.8%) compared with nonindigenous (6.7%) p < 0.001. BMI-SDS was higher in Maori/Pacifica youth (2.3) compared with indigenous Australian (2.1) and nonindigenous (2.2) p = 0.011.

CONCLUSIONS

Indigenous Australian and Maori/Pacifica youth in ADDN were younger and had worse glycaemic control at diagnosis of type 2 diabetes. Our findings underscore the need to consider targeted and earlier screening in these "high-risk" populations.

Determinants of Cardiovascular Risk in 7000 Youth With Type 1 Diabetes in the Australasian Diabetes Data Network

CONTEXT

Cardiovascular disease occurs prematurely in type 1 diabetes. The additional risk of overweight is not well characterized.

OBJECTIVE

The primary aim was to measure the impact of body mass index (BMI) in youth with type 1 diabetes on cardiovascular risk factors. The secondary aim was to identify other determinants of cardiovascular risk.

DESIGN

Observational longitudinal study of 7061 youth with type 1 diabetes followed for median 7.3 (interquartile range [IQR] 4-11) years over 41 (IQR 29-56) visits until March 2019.

SETTING

15 tertiary care diabetes centers in the Australasian Diabetes Data Network.Participants were aged 2 to 25 years at baseline, with at least 2 measurements of BMI and blood pressure.

MAIN OUTCOME MEASURE

Standardized systolic and diastolic blood pressure scores and non-high-density lipoprotein (HDL) cholesterol were co-primary outcomes. Urinary albumin/creatinine ratio was the secondary outcome.

RESULTS

BMI z-score related independently to standardized blood pressure z- scores and non-HDL cholesterol. An increase in 1 BMI z-score related to an average increase in systolic/diastolic blood pressure of 3.8/1.4 mmHg and an increase in non-HDL cholesterol (coefficient + 0.16 mmol/L, 95% confidence interval [CI], 0.13-0.18; P < 0.001) and in low-density lipoprotein (LDL) cholesterol. Females had higher blood pressure z-scores, higher non-HDL and LDL cholesterol, and higher urinary albumin/creatinine than males. Indigenous youth had markedly higher urinary albumin/creatinine (coefficient + 2.15 mg/mmol, 95% CI, 1.27-3.03; P < 0.001) and higher non-HDL cholesterol than non-Indigenous youth. Continuous subcutaneous insulin infusion was associated independently with lower non-HDL cholesterol and lower urinary albumin/creatinine.

CONCLUSIONS

BMI had a modest independent effect on cardiovascular risk. Females and Indigenous Australians in particular had a more adverse risk profile.

Glycaemia and utilisation of technology across the lifespan of adults with type 1 diabetes: Results of the Australian National Diabetes Audit (ANDA)

AIMS

To evaluate the utilisation of technologies and associated glycaemia among adults with type 1 diabetes.

METHODS

De-identified data from adults with type 1 diabetes (≥18 years old) in the Australian National Diabetes Audit (ANDA)-2019 were analysed. Proportions using insulin pumps or injections with continuous glucose monitoring (CGM) or capillary-glucose testing were compared. Technology use among adults was compared to young people (<21 years old) with subsidised CGM. Glycaemia and complication-burden were assessed across management strategies.

RESULTS

1,693 adults were analysed. Mean(±SD) age, diabetes duration, and HbA1c were 43.3 ± 17.0 years, 20.3 ± 14.3 years and 8.4% ± 1.7 [68 ± 19 mmol/mol], respectively. Among adults, 40% used at least one device, 27% used insulin pumps, and 23% used CGM. CGM was used by 62% of young people with subsidised access. Mean HbA1c was consistently lower among adults using CGM, insulin pumps, or combined insulin pump and CGM compared to standard care (8.3% ± 1.6 [67 ± 18 mmol/mol], 8.2% ± 1.4 [66 ± 15 mmol/mol], and 7.8% ± 1.4 [62 ± 15 mmol/mol] respectively compared to 8.6% ± 1.8 [70 ± 20 mmol/mol], p < 0.001). Technology use was not associated with diabetic ketoacidosis but CGM was associated with more hypoglycaemia.

CONCLUSIONS

Government subsidy is an important consideration for utilisation of technologies among adults with type 1 diabetes. Technology use across the adult lifespan was associated with lower HbA1c than insulin injections and capillary-glucose testing.

Has subsidized continuous glucose monitoring improved outcomes in pediatric diabetes?

INTRODUCTION

In 2017, the Australian Federal Government fully subsidized continuous glucose monitoring (CGM) devices for patients under 21 years of age with T1D with the aim of reducing rates of severe hypoglycaemia (SH) and improving metabolic control. The aim of this study was to reports on metabolic outcomes in youth from a single tertiary centre.

METHODS

The study design was observational. Data were obtained on youth who commenced CGM between May 2017 and December 2019.

RESULTS

Three hundred and forty one youth who commenced CGM and had clinical outcome data for a minimum of 4 months. 301, 261, 216, 172, and 125 had outcome data out to 8, 12, 16, 20, and 24 months, respectively. Cessation occurred between 27.9% and 32.8% of patients 12 to 24 months after CGM commencement. HbA1c did not change in patients who continued to use CGM. In the 12 months prior to starting CGM the rate of severe hypoglycaemia events were 5.0 per 100 patient years. The rates of severe hypoglycaemia in those continuing to use CGM at 4, 8, 12, 16, 20, and 24 months, were 5.2, 5.1, 1.6, 6.1, 2.4, and 0 per 100 patient years, respectively.

DISCUSSION

Our experience of patients either ceasing or underusing CGM is less than reported in other cohorts but is nonetheless still high. There may have been a reduction in rates of severe hypoglycaemia over the 24 months follow up period; however, the absolute numbers of events were so low as to preclude meaningful statistical analysis.

Temporal trends in diabetic ketoacidosis at diagnosis of paediatric type 1 diabetes between 2006 and 2016: results from 13 countries in three continents

AIMS/HYPOTHESIS

The aim of this work was to evaluate geographical variability and trends in the prevalence of diabetic ketoacidosis (DKA), between 2006 and 2016, at the diagnosis of childhood-onset type 1 diabetes in 13 countries over three continents.

METHODS

An international retrospective study on DKA at diagnosis of diabetes was conducted. Data on age, sex, date of diabetes diagnosis, ethnic minority status and presence of DKA at diabetes onset were obtained from Australia, Austria, Czechia, Denmark, Germany, Italy, Luxembourg, New Zealand, Norway, Slovenia, Sweden, USA and the UK (Wales). Mean prevalence was estimated for the entire period, both overall and by country, adjusted for sex and age group. Temporal trends in annual prevalence of DKA were estimated using logistic regression analysis for each country, before and after adjustment for sex, age group and ethnic minority status.

RESULTS

During the study period, new-onset type 1 diabetes was diagnosed in 59,000 children (median age [interquartile range], 9.0 years [5.5-11.7]; male sex, 52.9%). The overall adjusted DKA prevalence was 29.9%, with the lowest prevalence in Sweden and Denmark and the highest in Luxembourg and Italy. The adjusted DKA prevalence significantly increased over time in Australia, Germany and the USA while it decreased in Italy. Preschool children, adolescents and children from ethnic minority groups were at highest risk of DKA at diabetes diagnosis in most countries. A significantly higher risk was also found for females in Denmark, Germany and Slovenia.

CONCLUSIONS/INTERPRETATION

DKA prevalence at type 1 diabetes diagnosis varied considerably across countries, albeit it was generally high and showed a slight increase between 2006 and 2016. Increased awareness of symptoms to prevent delay in diagnosis is warranted, especially in preschool children, adolescents and children from ethnic minority groups.

Assessing guideline adherence in the management of type 1 diabetes mellitus in Australian children: a population-based sample survey

INTRODUCTION

To estimate adherence to clinical practice guidelines in selected settings at a population level for Australian children with type 1 diabetes mellitus.

RESEARCH DESIGN AND METHODS

Medical records of children with type 1 diabetes mellitus aged 0-15 years in 2012-2013 were targeted for sampling across inpatient, emergency department and community visits with specialist pediatricians in regional and metropolitan areas and tertiary pediatric hospitals in three states where approximately 60% of Australian children reside. Clinical recommendations extracted from two clinical practice guidelines were used to audit adherence. Results were aggregated across types of care (diagnosis, routine care, emergency care).

RESULTS

Surveyors conducted 6346 indicator assessments from an audit of 539 healthcare visits by 251 children. Average adherence across all indicators was estimated at 79.9% (95% CI 69.5 to 88.0). Children with type 1 diabetes mellitus have higher rates of behavioral and psychological disorders, but only a third of children (37.9%; 95% CI 11.7 to 70.7) with suboptimal glycemic control (eg, hemoglobin A1c >10% or 86 mmol/mol) were screened for psychological disorders using a validated tool; this was the only indicator with <50% estimated adherence. Adherence by care type was: 86.1% for diagnosis (95% CI 76.7 to 92.7); 78.8% for routine care (95% CI 65.4 to 88.9) and 83.9% for emergency care (95% CI 78.4 to 88.5).

CONCLUSIONS

Most indicators for care of children with type 1 diabetes mellitus were adhered to. However, there remains room to improve adherence to guidelines for optimization of practice consistency and minimization of future disease burden.

Establishment of the T1D Exchange Quality Improvement Collaborative (T1DX-QI)

The T1D Exchange established a learning platform by evaluating the current state of care and engaging 10 diabetes clinics in collaborative quality improvement (QI) activities. Participating clinics are sharing data and best practices to improve care delivery for people with type 1 diabetes. This article describes the design and initial implementation of this platform, known as the T1D Exchange Quality Improvement Collaborative. This effort has laid a foundation for learning from variation in type 1 diabetes care delivery via QI methodology and has demonstrated success in improving processes through iterative testing cycles and transparent sharing of data.

Longitudinal trajectories of BMI z-score: an international comparison of 11,513 Australian, American and German/Austrian/Luxembourgian youth with type 1 diabetes

BACKGROUND

BMI fluctuations during puberty are common. Data on individual change in BMI from childhood to young adulthood are limited in youth with type 1 diabetes.

OBJECTIVES

To compare longitudinal trajectories of body mass index z score (BMIz) from childhood to adolescence across three registries spanning five countries.

METHODS

Data sources: T1DX (USA), DPV (Germany/Austria/Luxembourg) and ADDN (Australia). The analysis included 11,513 youth with type 1 diabetes, duration >1 year, at least one BMI measure at baseline (age 8-10 years) and >5 aggregated BMI measures by year of age during follow-up until age 17 years. BMIz was calculated based on WHO charts. Latent class growth modelling was used to identify subgroups following a similar trajectory of BMIz over time.

RESULTS

Five distinct trajectories of BMIz were present in the T1DX and ADDN cohorts, while six trajectories were identified in the DPV cohort. Boys followed more often a low/near-normal pattern while elevated BMIz curves were more likely in girls (ADDN; DPV). For T1DX cohort, no sex differences were observed. Comparing the reference group (BMIz ~0) with the other groups during puberty, higher BMIz was significantly associated with older age at T1D onset, racial/ethnic minority and elevated HbA1c (all p<0.05).

CONCLUSION

This multinational study presents unique BMIz trajectories in youth with T1D across three continents. The prevalence of overweight and the longitudinal persistence of overweight support the need for close monitoring of weight and nutrition in this population. The international and individual differences likely result from diverse genetic, environmental and therapeutic factors.

Type 1 Diabetes TrialNet: A Multifaceted Approach to Bringing Disease-Modifying Therapy to Clinical Use in Type 1 Diabetes

What will it take to bring disease-modifying therapy to clinical use in type 1 diabetes? Coordinated efforts of investigators involved in discovery, translational, and clinical research operating in partnership with funders and industry and in sync with regulatory agencies are needed. This Perspective describes one such effort, Type 1 Diabetes TrialNet, a National Institutes of Health-funded and JDRF-supported international clinical trials network that emerged from the Diabetes Prevention Trial-Type 1 (DPT-1). Through longitudinal natural history studies, as well as trials before and after clinical onset of disease combined with mechanistic and ancillary investigations to enhance scientific understanding and translation to clinical use, TrialNet is working to bring disease-modifying therapies to individuals with type 1 diabetes. Moreover, TrialNet uses its expertise and experience in clinical studies to increase efficiencies in the conduct of trials and to reduce the burden of participation on individuals and families. Herein, we highlight key contributions made by TrialNet toward a revised understanding of the natural history of disease and approaches to alter disease course and outline the consortium's plans for the future.

Prevalence of Celiac Disease in 52,721 Youth With Type 1 Diabetes: International Comparison Across Three Continents

OBJECTIVE

Celiac disease (CD) has a recognized association with type 1 diabetes. We examined international differences in CD prevalence and clinical characteristics of youth with coexisting type 1 diabetes and CD versus type 1 diabetes only.

RESEARCH DESIGN AND METHODS

Data sources were as follows: the Prospective Diabetes Follow-up Registry (DPV) (Germany/Austria); the T1D Exchange Clinic Network (T1DX) (U.S.); the National Paediatric Diabetes Audit (NPDA) (U.K. [England/Wales]); and the Australasian Diabetes Data Network (ADDN) (Australia). The analysis included 52,721 youths <18 years of age with a clinic visit between April 2013 and March 2014. Multivariable linear and logistic regression models were constructed to analyze the relationship between outcomes (HbA_1c, height SD score [SDS], overweight/obesity) and type 1 diabetes/CD versus type 1 diabetes, adjusting for sex, age, and diabetes duration.

RESULTS

Biopsy-confirmed CD was present in 1,835 youths (3.5%) and was diagnosed at a median age of 8.1 years (interquartile range 5.3-11.2 years). Diabetes duration at CD diagnosis was <1 year in 37% of youths, >1-2 years in 18% of youths, >3-5 years in 23% of youths, and >5 years in 17% of youths. CD prevalence ranged from 1.9% in the T1DX to 7.7% in the ADDN and was higher in girls than boys (4.3% vs. 2.7%, P < 0.001). Children with coexisting CD were younger at diabetes diagnosis compared with those with type 1 diabetes only (5.4 vs. 7.0 years of age, P < 0.001) and fewer were nonwhite (15 vs. 18%, P < 0.001). Height SDS was lower in those with CD (0.36 vs. 0.48, adjusted P < 0.001) and fewer were overweight/obese (34 vs. 37%, adjusted P < 0.001), whereas mean HbA_1c values were comparable: 8.3 ± 1.5% (67 ± 17 mmol/mol) versus 8.4 ± 1.6% (68 ± 17 mmol/mol).

CONCLUSIONS

CD is a common comorbidity in youth with type 1 diabetes. Differences in CD prevalence may reflect international variation in screening and diagnostic practices, and/or CD risk. Although glycemic control was not different, the lower height SDS supports close monitoring of growth and nutrition in this population.

The Australasian Diabetes Data Network: first national audit of children and adolescents with type 1 diabetes

OBJECTIVES

To assess glycaemic control, anthropometry and insulin regimens in a national sample of Australian children and adolescents with type 1 diabetes.

DESIGN

Cross-sectional analysis of de-identified, prospectively collected data from the Australasian Diabetes Data Network (ADDN) registry.

SETTING

Five paediatric diabetes centres in New South Wales, Queensland, South Australia, Victoria and Western Australia.

PARTICIPANTS

Children and adolescents (aged 18 years or under) with type 1 diabetes of at least 12 months' duration for whom data were added to the ADDN registry during 2015.

MAIN OUTCOME MEASURES

Glycaemic control was assessed by measuring haemoglobin A1c (HbA1c) levels. Body mass index standard deviation scores (BMI-SDS) were calculated according to the CDC-2000 reference; overweight and obesity were defined by International Obesity Task Force guidelines. Insulin regimens were classified as twice-daily injections (BD), multiple daily injections (MDI; at least three injection times per day), or continuous subcutaneous insulin infusion (CSII).

RESULTS

The mean age of the 3279 participants was 12.8 years (SD, 3.7), mean diabetes duration was 5.7 years (SD, 3.7), and mean HbA1c level 67 mmol/mol (SD, 15); only 27% achieved the national HbA1c target of less than 58 mmol/mol. The mean HbA1c level was lower in children under 6 (63 mmol/mol) than in adolescents (14-18 years; 69 mmol/mol). Mean BMI-SDS for all participants was 0.6 (SD, 0.9); 33% of the participants were overweight or obese. 44% were treated with CSII, 38% with MDI, 18% with BD.

CONCLUSIONS

Most Australian children and adolescents with type 1 diabetes are not meeting the recognised HbA1c target. The prevalence of overweight and obesity is high. There is an urgent need to identify barriers to achieving optimal glycaemic control in this population.