Objectives: There are limited glucose profile data in very young children with type 1 diabetes.In this analysis we used masked, continuous glucose monitoring (CGM) data from youth 2 to < 8 years to assess associations between demographic and clinical characteristics and sensor glucose metrics.Research Design/Methods: The analysis included 143 children across 14 sites in the United States enrolled in a separate clinical trial. Eligibility criteria: age 2-<8 years, type1 diabetes duration ≥3 months, no CGM use for past 30 days and hemoglobin A1c (HbA1c) 7.0-<10.0% (53-<86 mmol/mol). All wore masked CGM up to 14 days. Results:On average, participants spent the majority (13 hours) of the day in a hyperglycemic range >10.0mmol/L and a median of about 1 hour/day in hypoglycemia (<3.9mmol/L).Participants with minority race/ethnicity and higher parent education levels had greater time in target range 3.9-10.0 mmol/L and less time in hyperglycemia. More time in hypoglycemia was associated with minority race/ethnicity and younger age at diagnosis. CGM metrics were similar in pump and injection users. Conclusions:Given that both hypo-and hyperglycemia negatively impact neurocognitive development, strategies to increase time in target glucose range are needed.

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Context Continuous glucose monitoring (CGM) is increasingly being used for both day-to-day management in patients with diabetes and in clinical research. While data on glycemic profiles of healthy, non-diabetic individuals exists, data on non-diabetic very young children are lacking. Objective To establish reference sensor glucose ranges in healthy, non-diabetic young children, using a current generation CGM sensor. Design Prospective observational study Setting Institutional practice Participants Healthy, non-diabetic children 1-6 years old; with normal body mass index Intervention A blinded Dexcom G6 Pro CGM was worn for approximately 10 days by each participant. Main Outcome Measure CGM metrics of mean glucose, hyperglycemia, hypoglycemia, and glycemic variability Results 39 participants were included in the analyses. Mean average glucose was 103 mg/dL (5.7 mmol/L). Median % time between 70-140 mg/dL (3.9-7.8 mmol/L) was 96% (IQR 92%-97%), mean within-individual coefficient of variation was 17±3%, median time spent with glucose levels &gt;140mg/dL was 3.4% (49 min/day), and median time &lt;70 mg/dL (3.9 mmol/L) was 0.4% (6 min/day). Conclusions Collecting normative sensor glucose data and describing glycemic measures for young children fills an important informational gap and will be useful as a benchmark for future clinical studies.

Aims To compare diagnosis characteristics, diabetes management and comorbidities in a population diagnosed with type 1 diabetes in childhood with those in a similar population diagnosed in adulthood to identify disease differences related to the age of diabetes onset. Methods This analysis was performed using the T1D Exchange Clinic Registry, a cross-sectional survivor cohort. Retrospectively collected characteristics were compared across the following age-at-diagnosis groups: <10, 10-17, 18-24, 25-39 and ≥40 years. Results The entire cohort included 20 660 participants [51% female, median (interquartile range) age 18 (14-36) years, 82% non-Hispanic white]. Diabetic ketoacidosis at diagnosis was more common among those with onset in childhood. Participants diagnosed as adults were more likely to be overweight/obese at diagnosis and to have used oral agents preceding type 1 diabetes diagnosis (57%). Current insulin pump use was less frequent in participants diagnosed at older ages. Current glycaemic control, measured by HbA 1c , insulin requirements and use of a continuous glucose monitor were not different by age at diagnosis. Coeliac disease was the only comorbidity that was observed to have a different frequency by age at diagnosis, being more common in the participants diagnosed at a younger age. Conclusions These results show differences and similarities between type 1 diabetes diagnosed in childhood vs adulthood; notably, there was a tendency for there was a higher frequency of diabetic ketoacidosis at onset in children and a higher frequency of use of oral antidiabetes agents in adults. The data indicate that there is little distinction between the clinical characteristics and outcomes of type 1 diabetes diagnosed in childhood vs adulthood. Optimizing glycaemic control remains a challenge in all age groups, with lower use of insulin pumps impacting those diagnosed as adults.

Objectives: Achieving optimal glycemic outcomes in young children with type 1 diabetes (T1D) is challenging. This study examined the durability of continuous glucose monitoring (CGM) coupled with a family behavioral intervention (FBI) to improve glycemia. Study Design: This one-year study included an initial 26-week randomized controlled trial of CGM with FBI ( CGM+FBI) and CGM alone ( Standard-CGM) compared with blood glucose monitoring (BGM), followed by a 26-week extension phase wherein the BGM Group received the CGM+FBI ( BGM-Crossover) and both original CGM groups continued this technology. Results: Time in range (70-180 mg/dL) did not improve with CGM use (CGM+FBI: baseline 37%, 52 weeks 41%; Standard-CGM: baseline 41%, 52 weeks 44%; BGM-Crossover: 26 weeks 38%, 52 weeks 40%). All three groups sustained decreases in hypoglycemia (<70 mg/dL) with CGM use (CGM+FBI: baseline 3.4%, 52 weeks 2.0%; Standard-CGM: baseline 4.1%, 52 weeks 2.1%; BGM-Crossover: 26 weeks 4.5%, 52 weeks 1.7%, P-values <.001). Hemoglobin A1c was unchanged with CGM use (CGM+FBI: baseline 8.3%, 52 weeks 8.2%; Standard-CGM: baseline 8.2%, 52 weeks 8.0%; BGM-Crossover: 26 weeks 8.1%, 52 weeks 8.3%). Sensor use remained high (52-week study visit: CGM+FBI 91%, Standard-CGM 92%, BGM-Crossover 88%). Conclusion: Over 12 months young children with T1D using newer CGM technology sustained reductions in hypoglycemia and, in contrast to prior studies, persistently wore CGM. However, pervasive hyperglycemia remained unmitigated. This indicates an urgent need for further advances in diabetes technology, behavioral support, and diabetes management educational approaches to optimize glycemia in young children.