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.

OBJECTIVE To analyze whether the coronavirus disease 2019 (COVID-19) pandemic increased the number of cases or impacted seasonality of new-onset type 1 diabetes (T1D) in large pediatric diabetes centers globally. RESEARCH DESIGN AND METHODS We analyzed data on 17,280 cases of T1D diagnosed during 2018–2021 from 92 worldwide centers participating in the SWEET registry using hierarchic linear regression models. RESULTS The average number of new-onset T1D cases per center adjusted for the total number of patients treated at the center per year and stratified by age-groups increased from 11.2 (95% CI 10.1–12.2) in 2018 to 21.7 (20.6–22.8) in 2021 for the youngest age-group, <6 years; from 13.1 (12.2–14.0) in 2018 to 26.7 (25.7–27.7) in 2021 for children ages 6 to <12 years; and from 12.2 (11.5–12.9) to 24.7 (24.0–25.5) for adolescents ages 12–18 years (all P < 0.001). These increases remained within the expected increase with the 95% CI of the regression line. However, in Europe and North America following the lockdown early in 2020, the typical seasonality of more cases during winter season was delayed, with a peak during the summer and autumn months. While the seasonal pattern in Europe returned to prepandemic times in 2021, this was not the case in North America. Compared with 2018–2019 (HbA1c 7.7%), higher average HbA1c levels (2020, 8.1%; 2021, 8.6%; P < 0.001) were present within the first year of T1D during the pandemic. CONCLUSIONS The slope of the rise in pediatric new-onset T1D in SWEET centers remained unchanged during the COVID-19 pandemic, but a change in the seasonality at onset became apparent.

To investigate temporal trends in glycemic control and severe hypoglycemia rates for pediatric patients with type 1 diabetes from 1995 to 2016 by analyzing data from the longitudinal, prospective, population-based German/Austrian (Diabetes Patient History Documentation [DPV]) and Western Australian (Western Australian Children's Diabetes Database [WACDD]) diabetes registries. RESEARCH DESIGN AND METHODS Patients diagnosed with type 1 diabetes aged <15 years were identified from the DPV (N = 59,883) and WACDD (N = 2,595) registries and data extracted for all clinic visits occurring between 1995 and 2016, inclusive. Mean HbA 1c and severe hypoglycemia (self-reported loss of consciousness/convulsion) rates were calculated per 100 patient-years. RESULTS Between 1995 and 2016, the annual mean HbA 1c decreased from 8.3 to 7.8% in the DPV cohort and from 9.2 to 8.3% in the WACDD cohort. Over the same period, the severe hypoglycemia rate decreased by an annual average of 2% (relative risk 0.983 [95% CI 0.981, 0.986]) in the DPV cohort and 6% (relative risk 0.935 [95% CI 0.934, 0.937]) in the WACDD cohort. Concomitant decreasing trends in both HbA 1c and severe hypoglycemia rates were observed in boys and girls, all age-groups, and injection therapy/pump regimen groups. CONCLUSIONS Over the past two decades, there have been concurrent improvements in HbA 1c and decreasing severe hypoglycemia rates in two contemporary, longitudinal, population-based pediatric cohorts of type 1 diabetes. Translation of these data into clinical practice and patient education may reduce fear of hypoglycemia and enable better glycemic control.

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Following changes in newborn screening protocols and earlier collection of blood samples, the WHO criteria appear inappropriate. We recommend that WHO revise current guidelines regarding use of neonatal TSH for monitoring population iodine status.

With adequate support, children newly diagnosed with T1D can be safely managed at home following practical skills training.

Australasia is a region with a high incidence of type 1 diabetes (T1D). There are approximately 140 000 individuals with T1D, and of these 10 000 are children. Although the region covers a huge geographical area, most children with T1D are managed by tertiary academic centers in the major capital cities. Local longitudinal data collection has been in place for several decades in most of these centers, however ongoing national data collection had not been attempted. In 2012, with funding from the Juvenile Diabetes Research Foundation (JDRF) Australian Type 1 Clinical Research Network, a national collaboration was formed to provide ongoing longitudinal collection of T1D patient characteristics and outcomes. The initial phase of this collaboration, known as the Australasian Diabetes Data Network or ADDN, was led by the Australasian Paediatric Endocrine Group (APEG) and thus included only children and adolescents. The next phase, commenced in 2016, will see adult sites added through collaboration with the Australian Diabetes Society (ADS). As most of the initial centers had longitudinal data collection in place the model employed was to establish the transfer and collation of data already collected into a central database. This required the definition of a common data dictionary, ethics and governance procedures and the employment of technology to enable efficient and accurate information transfer and accessibility. The ADDN project received widespread support from the diabetes research community with study investigators representing 20 pediatric centers across the region. The first phase focused on the 5 largest centers and at the end of 2015 these centers were uploading patient data to the ADDN database on a quarterly basis resulting in 5271 patients with 83 506 diabetes visits.

ImportanceContinuous glucose monitoring (CGM) devices have demonstrated efficacy in adults and more recently in youths and older adults with type 1 diabetes. In adults with type 1 diabetes, the use of real-time CGM compared with intermittently scanned CGM was associated with improved glycemic control, but there are limited data available for youths.ObjectiveTo assess real-world data on achievement of time in range clinical targets associated with different treatment modalities in youths with type 1 diabetes.Design, Setting, and ParticipantsThis multinational cohort study included children, adolescents, and young adults younger than 21 years (hereinafter referred to collectively as youths) with type 1 diabetes for a duration of at least 6 months who provided CGM data between January 1, 2016, and December 31, 2021. Participants were enrolled from the international Better Control in Pediatric and Adolescent Diabetes: Working to Create Centers of Reference (SWEET) registry. Data from 21 countries were included. Participants were divided into 4 treatment modalities: intermittently scanned CGM with or without insulin pump use and real-time CGM with or without insulin pump use.ExposuresType 1 diabetes and the use of CGM with or without an insulin pump.Main Outcomes and MeasuresProportion of individuals in each treatment modality group achieving recommended CGM clinical targets.ResultsAmong the 5219 participants (2714 [52.0%] male; median age, 14.4 [IQR, 11.2-17.1] years), median duration of diabetes was 5.2 (IQR, 2.7-8.7) years and median hemoglobin A1c level was 7.4% (IQR, 6.8%-8.0%). Treatment modality was associated with the proportion of individuals achieving recommended clinical targets. Adjusted for sex, age, diabetes duration, and body mass index standard deviation score, the proportion achieving the recommended greater than 70% time in range target was highest with real-time CGM plus insulin pump use (36.2% [95% CI, 33.9%-38.4%]), followed by real-time CGM plus injection use (20.9% [95% CI, 18.0%-24.1%]), intermittently scanned CGM plus injection use (12.5% [95% CI, 10.7%-14.4%]), and intermittently scanned CGM plus insulin pump use (11.3% [95% CI, 9.2%-13.8%]) (P &amp;lt; .001). Similar trends were observed for less than 25% time above (real-time CGM plus insulin pump, 32.5% [95% CI, 30.4%-34.7%]; intermittently scanned CGM plus insulin pump, 12.8% [95% CI, 10.6%-15.4%]; P &amp;lt; .001) and less than 4% time below range target (real-time CGM plus insulin pump, 73.1% [95% CI, 71.1%-75.0%]; intermittently scanned CGM plus insulin pump, 47.6% [95% CI, 44.1%-51.1%]; P &amp;lt; .001). Adjusted time in range was highest among real-time CGM plus insulin pump users (64.7% [95% CI, 62.6%-66.7%]). Treatment modality was associated with the proportion of participants experiencing severe hypoglycemia and diabetic ketoacidosis events.Conclusions and RelevanceIn this multinational cohort study of youths with type 1 diabetes, concurrent use of real-time CGM and an insulin pump was associated with increased probability of achieving recommended clinical targets and time in range target as well as lower probability of severe adverse events compared with other treatment modalities.