INTRODUCTION:Recently, our clinical trial of youth randomized shortly after type 1 diabetes (T1D) diagnosis to intensive diabetes management with automated insulin delivery (AID) reported mean time in range (TIR) of 78% at 52 weeks. This analysis investigated whether high TIR persisted over 104 weeks. METHODS:Participants were initially randomly assigned to intensive care or a control group receiving standard care through 52 weeks. During this randomized period, the intensive care group was intensively managed with AID and frequent contacts and the control group used continuous glucose monitoring (CGM) with injections or pumps without AID. At 52 weeks, all participants could select their insulin delivery modality, and diabetes management returned to clinical teams. This secondary analysis compared TIR between groups in this observational extension phase (52- to 104-week post-diagnosis). RESULTS:Thirty-nine of 61 RCT intensive care and 30 of 52 control participants enrolled in the extension and provided 104-week CGM data. Three RCT intensive care participants discontinued AID and 25 control participants initiated AID. From 52 to 104 weeks, mean %TIR remained stable (65% ± 21% to 65 ± 15%) in the RCT control group and declined in the RCT intensive care (79 ± 13% to 67 ± 15%) with no significant between-group difference at 104 weeks (mean difference 4% [95% CI: -5%, 13%], p = 0.72). Forty-nine percent of RCT intensive care and 40% of control participants had TIR >70% at 104 weeks (p = 0.73). Mean %time <54 mg/dL remained very low (<0.4%) in both groups at 104 weeks. Mean hemoglobin A1c was 6.7% ± 0.7 in the RCT intensive care group and 7.2% ± 1.5 in the controls at 104 weeks (mean difference -0.4 [-1.1, 0.4], p = 0.72). CONCLUSION:Very high mean TIR at 52 weeks in youth randomized to intensive care with AID soon after T1D diagnosis waned during the 52-week observation period after the randomized trial.

The development of automated insulin delivery systems has seen tremendous improvements from individual components to interoperable system combinations of devices and new drugs besides insulin. The components have become progressively smaller, more accurate, and more user friendly. This article summarizes the history of the artificial pancreas from the earliest concepts to fully functional systems to research into further improvements in the future. The authors include many of the developers of this technology who received research support from the National Institute of Diabetes and Digestive and Kidney Diseases at various stages to develop these systems.

Type 1 diabetes has detrimental effects in white matter microstructure. In a longitudinal study, we investigated whether these reported findings change as children grow and enter puberty. At study entry, there were 143 children with type 1 diabetes and 71 control participants without diabetes, 4-9 years old. Brain MRI using diffusion tensor imaging, neurocognitive, and glycemic assessments were performed four times across 6-8 years of follow-up. Longitudinal mixed-effects modeling was used to examine changes in fractional anisotropy (FA), axial diffusivity (AD) (measures of myelination and fiber integrity), radial diffusivity (RD) (axonal leakage), and mean diffusivity (MD) (average diffusion). Associations with glycemic and cognitive measures were assessed. We observed in 182 children (121 type 1 diabetes vs. 61 control participants) who had testing at time 4 that FA increased, and RD, AD, and MD decreased significantly in both groups, with no differences between groups for FA, RD and MD over time. However, children with diabetes had lower AD than control participants at 6-10 years. Differences were not detected at 12 years (age imputed from data), when in puberty. Higher blood glucose levels are associated with lower FA and higher RD and MD. Higher glucose percentage time-in-range was associated with higher FA, reflecting better fiber integrity and myelination and higher cognitive metrics. Within the diabetes group, AD and MD showed no association with neurocognitive outcomes. In summary, white matter AD was decreased in children with diabetes, less so during puberty, and FA was reciprocally related to hyperglycemia. These data suggest continued negative impact of chronic hyperglycemia in the developing brain. ARTICLE HIGHLIGHTS:Type 1 diabetes has detrimental effects in white matter in young children. We performed a longitudinal study using brain MRI (diffusion tensor imaging) and cognitive assessments in 4- to 9-year-old children, control participants without diabetes (n = 71) and with type 1 diabetes (n = 143), plus continuous glucose monitoring, to assess changes at four time points as children grow over 6-8 years. White matter myelination and fiber integrity were assessed using axial diffusivity, which was decreased in the diabetes versus control group, less so during puberty, and fractional anisotropy was reciprocally related to hyperglycemia. Data suggest continued negative impact of chronic hyperglycemia in the developing brain.

Introduction: Glucose regulation in young children is complicated by higher glycemic variability, unpredictable behaviors, and low insulin needs. While the benefits of automated insulin delivery (AID) for this population are established, how to initiate and adjust pump settings still represents a challenging task for health care providers. In this study, we investigate the safety and efficacy of using algorithm-driven initiation and adjustments of AID parameters in children aged 2-6 years. Methods: Participants used AID at home for 8 weeks. Initial settings and periodic adjustments of therapy profiles (basal rates, insulin-to-carbohydrate ratios, insulin-correction factors, and sleep schedules) were provided through a cloud-based investigational software. Investigators reviewed therapy recommendations and could adjust if necessary. Primary safety endpoints included the percentage of time <54 mg/dL and >250 mg/dL, tested for noninferiority with respect to baseline. Primary efficacy endpoints (tested in a hierarchical manner) were the percentage of time in 70-180 mg/dL, mean glucose, the percentage of time >250 mg/dL, <70 mg/dL, and <54 mg/dL. Results: Thirty-two participants (age range: 2.0-5.9 years) were recruited for the study; 29 had sufficient data for the analysis. Investigators overrode 15% of software recommendations. The percentage of time <54 mg/dL and >250 mg/dL was noninferior in the 8-week follow-up with respect to baseline (P < 0.001). Statistically significant improvements were observed in the percentage of time in 70-180 mg/dL (P = 0.005), >250 mg/dL (P = 0.003), and mean glucose (P = 0.02). No difference was observed in the percentage of time <70 mg/dL (P = 0.34). Furthermore, no difference was observed with respect to a similar study cohort (same age range, n = 86) with expert pediatric endocrinologists modifying pump settings. Conclusions: Findings from this pilot study suggest that the use of AID with algorithm-driven initiation and adjustment of pump parameters is safe and effective in young children with type 1 diabetes. Further study of the algorithm in a larger cohort is indicated. Clinical Trials Registration number: NCT06017089.

Artificial pancreas (AP) systems, also called automated insulin delivery systems, have improved the time in range of glucose levels, reduced the daily burden of the user for glucose regulation, and improved their quality of life. Several commercially available AP systems operate in hybrid closed-loop mode that requires manual information from the user for meals and exercise. This article summarizes the progress on mathematical models of glucose-insulin dynamics, continuous glucose monitoring systems, and insulin pumps that form the building blocks of AP systems, the shift from animal studies to in silico clinical trials that accelerated the rate of progress in AP technologies and the efforts for developing the next-generation AP systems, and the fully automated AP that eliminates manual inputs and mitigates the effects of disturbances to glucose homeostasis-meals, physical activities, acute stress, and variations in sleep characteristics. A section is devoted to discuss the unique glycemic management challenges faced by women with diabetes across the lifespan (menstrual cycle, menopause, pregnancy) and summarize progress made to reduce their impact on glycemic management.

Disclosure: T. Akcan: None. R.S. Kingman: None. B. Suh: None. K. Kingston: None. Y. Liu: None. M. Morgan: None. M. Lee: None. B. Buckingham: None. M.S. Hughes: None. R.A. Lal: None. Background: Verapamil, a calcium channel blocker, has emerged as a potential beta-cell preservation therapy for Type 1 Diabetes (T1D). Real-world data on the implementation of verapamil remains limited. This study evaluates the clinical use of verapamil at a single academic medical center. Methods: A retrospective chart review was conducted on individuals with T1D who were considered for verapamil therapy. Those included were categorized into two groups: individuals who initiated verapamil and those who discussed but did not proceed with treatment. Data collected included demographics, adherence to monitoring protocols (creatinine, AST, ALT, and ECGs), ability to reach the recommended maximum dose (weight-based to a maxiumum of 360 mg/day for individuals ≥50 kg), adverse events and barriers to therapy. Results: A total of 75 individuals with T1D, age 2-76 years, were considered for verapamil therapy. Among the 33 (44%) who initiated treatment (age 26.1±18.0 years), screening labs were completed in 90.9% (30/33), and ECGs were performed in 66.7% (22/33) prior to therapy initiation. The mean PR interval on screening ECG were normal (143 ± 22 msec). A total of 72.7% (24/33) reached the recommended maximum dose. Among these, 58.3% (14/24) completed follow-up labs. Another 58.3% (14/24) had repeat ECGs two weeks after reaching maximum dose, with a normal mean PR interval at follow-up of 147 ± 24 msec. Adverse events attributed to verapamil were reported in four individuals. These included one case of mild constipation and two cases of temporary PR prolongation over 200 msec, both of which resolved, allowing them to continue on the maximum recommended dose. One adolescent missed doses, took extra to compensate (at least 720 mg) and developed symptomatic heart block requiring hospitalization in the Cardiac ICU. The family elected to stop verapamil. Notably, four individuals weighing <30 kg were treated with 60 mg/day, maintained normal ECGs on this dose and have successfully continued treatment. In contrast, 42 individuals (56%) discussed verapamil, with documentation in the chart, but did not initiate therapy (mean age 20.7 ± 17.5 years). Reasons for non-initiation were recorded in 16 (38.1%) cases. Among these, 62.5% (10/16) cited personal preference, the need for more time to consider therapy, or verapamil was prescribed but not started; 18.8% (3/16) were ineligible due to screening lab results, and 18.8% (3/16) were deemed too young and/or with a weight below 30 kg. Conclusion: Despite being among the simplest beta-cell preservation therapies, real-world implementation of verapamil in T1D under current protocols presents challenges. Modifiable barriers to initiation include individual/provider preferences, protocol and logistical constraints. Education around missed doses is imperative. Simplified approaches to dosing and monitoring may improve accessibility for a broader population. Presentation: Saturday, July 12, 2025

Objective: Continuous glucose monitoring (CGM) measures could be a surrogate for stimulated C-peptide outcomes in type 1 diabetes trials. Research Design and Methods: CGM and mixed-meal tolerance test-derived C-peptide measures at time points out to 52-weeks post diagnosis were compared in 103 children. Results: At 52 weeks, CGM metrics moderately correlated with C-peptide area under the curve. The highest Spearman correlations were for time-in-range 70-180mg/dl, time <70mg/dl, and glucose coefficient of variation (0.45, -0.33, -0.58, respectively); the multivariate model using these 3 metrics had a slightly higher correlation of 0.63). For predicting peak C-peptide ≥0.2 pmol/mL, this combination had a sensitivity of 68.4% and specificity of 75%. Conclusion: CGM measures correlated with stimulated C-peptide measures, however, the strength of the correlations and sensitivity and specificity of CGM-derived measures were not high enough to replace C-peptide measures in clinical trials.

Introduction: Outpatient use of diabetes devices, including continuous glucose monitors (CGM), insulin pumps, and automated insulin delivery (AID) is increasing, and guidelines suggest continuation during hospitalization, despite off label use and limited guidance. We conducted an online survey to understand current real world diabetes technology continuation and use in hospital. Methods: From May-Nov 2023, a survey was distributed via diabetes-related networks and social media. Eligible participants were living with or caring for someone with diabetes who experienced a hospitalization in the prior year and used a CGM and/or insulin pump at that time. Results: Of 540 responses, 283 were excluded for ineligibility, incompleteness, or duplication. The remaining cohort (N=258) was mostly ≥18 years (92%), female (69%), white (94%), privately insured (62%), and had type 1 diabetes (93%). Hospitalizations occurred in 45 US states, commonly for surgery (32%), glycemia (20%), or infection (12%). A majority used their devices for ≥90% of their stay (fig). Among inpatient AID users (n=133), 74% felt glucoses were well-controlled vs. 49% of those who discontinued AID (n=33) (p=0.005). Conclusion: Outpatient diabetes technology is commonly used in hospital glucose management, with users reporting more in target glycemic control. Further research should explore hospital implementation and how effectiveness and operational demands compare to traditional methods. Disclosure M.S. Hughes: Consultant; Dexcom, Inc. M. Morgan: None. L. Hsu: None. Y. Liu: None. M. Lee: None. S. Hanes: None. V. Fielding-Singh: None. K.K. Hood: Consultant; Cecelia Health, Sanofi. B.A. Buckingham: Advisory Panel; Medtronic. Research Support; Medtronic. Advisory Panel; Arecor. R. Lal: Consultant; Abbott, Adaptyx Biosciences, Biolinq, Capillary Biomedical, Inc., Deep Valley Labs, Gluroo, PhysioLogic Devices, Portal Insulin, Tidepool. Advisory Panel; Lilly Diabetes. Funding National Institutes of Health (5K12DK122550, 1K23DK122017, T32DK007217, P30DK116074)

Background/Objective: The main objective of this study is to evaluate the incremental cost-effectiveness (ICER) of the Cambridge hybrid closed-loop automated insulin delivery (AID) algorithm versus usual care for children and adolescents with type 1 diabetes (T1D). Methods: This multicenter, binational, parallel-controlled trial randomized 133 insulin pump using participants aged 6 to 18 years to either AID (n = 65) or usual care (n = 68) for 6 months. Both within-trial and lifetime cost-effectiveness were analyzed. Analysis focused on the treatment subgroup (n = 21) who received the much more reliable CamAPS FX hardware iteration and their contemporaneous control group (n = 24). Lifetime complications and costs were simulated via an updated Sheffield T1D policy model. Results: Within-trial, both groups had indistinguishable and statistically unchanged health-related quality of life, and statistically similar hypoglycemia, severe hypoglycemia, and diabetic ketoacidosis (DKA) event rates. Total health care utilization was higher in the treatment group. Both the overall treatment group and CamAPS FX subgroup exhibited improved HbA1C (−0.32%, 95% CI: −0.59 to −0.04; P = .02, and −1.05%, 95% CI: −1.43 to −0.67; P < .001, respectively). Modeling projected increased expected lifespan of 5.36 years and discounted quality-adjusted life years (QALYs) of 1.16 (U.K. tariffs) and 1.52 (U.S. tariffs) in the CamAPS FX subgroup. Estimated ICERs for the subgroup were £19 324/QALY (United Kingdom) and −$3917/QALY (United States). For subgroup patients already using continuous glucose monitors (CGM), ICERs were £10 096/QALY (United Kingdom) and −$33 616/QALY (United States). Probabilistic sensitivity analysis generated mean ICERs of £19 342/QALY (95% CI: £15 903/QALY to £22 929/QALY) (United Kingdom) and −$28 283/QALY (95% CI: −$59 607/QALY to $1858/QALY) (United States). Conclusions: For children and adolescents with T1D on insulin pump therapy, AID using the Cambridge algorithm appears cost-effective below a £20 000/QALY threshold (United Kingdom) and cost saving (United States).

The introduction of automated insulin delivery (AID) systems represents a significant advancement in diabetes care, offering substantial benefits in outpatient settings. Although clinical studies suggest that these systems can also help improve glycemic control in acutely ill patients, several barriers remain for the actual implementation and use of these technologies in clinical practice. Three main contexts for inpatient use are addressed, including: (a) continuation of personal AID systems, (b) initiation of AID during hospitalization, and (c) initiation of AID systems at discharge. A research road map with immediate to long-term actions is presented. Initially, it calls for clinical studies assessing in-hospital efficacy, safety, and utility, addressing specific patient needs and health care operational impacts. Midterm, it focuses on practical integration, simplifying AID use, ensuring electronic health record compatibility, clarifying regulatory uncertainties, and supporting health care professionals and patients. Long-term goals include system optimizations and policy advocacy for in-hospital AID use.

Objective: Modeling the effect of meal composition on glucose excursion would help in designing decision support systems (DSS) for type 1 diabetes (T1D) management. In fact, macronutrients differently affect post-prandial gastric retention (GR), rate of appearance (R $_\rm{a}$ ), and insulin sensitivity (S $_\rm{I}$ ). Such variables can be estimated, in inpatient settings, from plasma glucose (G) and insulin (I) data using the Oral glucose Minimal Model (OMM) coupled with a physiological model of glucose transit through the gastrointestinal tract (reference OMM, R-OMM). Here, we present a model able to estimate those quantities in daily-life conditions, using minimally-invasive (MI) technologies, and validate it against the R-OMM. Methods: Forty-seven individuals with T1D (weight $=78\pm$ 13kg, age $=42\pm$ 10yr) underwent three 23-hour visits, during which G and I were frequently sampled while wearing continuous glucose monitoring (CGM) and insulin pump (IP). Using a Bayesian Maximum A Posteriori estimator, R-OMM was identified from plasma G and I measurements, and MI-OMM was identified from CGM and IP data. Results: The MI-OMM fitted the CGM data well and provided precise parameter estimates. GR and R $_\rm{a}$ model parameters were not significantly different using the MI-OMM and R-OMM (p $>$ 0.05) and the correlation between the two S $_\rm{I}$ was satisfactory ( $\rho$ $=$ 0.77). Conclusion: The MI-OMM is usable to estimate GR, R $_\rm{a}$ , and S $_\rm{I}$ from data collected in real-life conditions with minimally-invasive technologies. Significance: Applying MI-OMM to datasets where meal compositions are available will allow modeling the effect of each macronutrient on GR, R $_\rm{a}$ , and S $_\rm{I}$ . DSS could finally exploit this information to improve diabetes management.

Objective: To evaluate the impact of missed or late meal boluses (MLBs) on glycemic outcomes in children and adolescents with type 1 diabetes using automated insulin delivery (AID) systems. Research Design and Methods: AID-treated (Tandem Control-IQ or Medtronic MiniMed 780G) children and adolescents (aged 6-21 years) from Stanford Medical Center and Steno Diabetes Center Copenhagen with ≥10 days of data were included in this two-center, binational, population-based, retrospective, 1-month cohort study. The primary outcome was the association between the number of algorithm-detected MLBs and time in target glucose range (TIR; 70-180 mg/dL). Results: The study included 189 children and adolescents (48% females with a mean ± standard deviation age of 13 ± 4 years). Overall, the mean number of MLBs per day in the cohort was 2.2 ± 0.9. For each additional MLB per day, TIR decreased by 9.7% points (95% confidence interval [CI] 11.3; 8.1), and compared with the quartile with fewest MLBs (Q1), the quartile with most (Q4) had 22.9% less TIR (95% CI: 27.2; 18.6). The age-, sex-, and treatment modality-adjusted probability of achieving a TIR of >70% in Q4 was 1.4% compared with 74.8% in Q1 (P < 0.001). Conclusions: MLBs significantly impacted glycemic outcomes in AID-treated children and adolescents. The results emphasize the importance of maintaining a focus on bolus behavior to achieve a higher TIR and support the need for further research in technological or behavioral support tools to handle MLBs.

Background: To evaluate the long-term safety and effectiveness of the Omnipod® 5 Automated Insulin Delivery (AID) System in very young children with type 1 diabetes with up to 2 years of use. Methods: Following a 13-week single-arm, multicenter, pivotal trial that took place after 14 days of standard therapy data collection, participating children (2-5.9 years of age at study enrollment) were provided the option to continue use of the AID system in an extension phase. HbA1c was measured every 3 months, up to 15 months of total use, and continuous glucose monitor metrics were collected through the completion of the extension study (for up to 2 years). Results: Participants (N = 80) completed 18.2 [17.4, 23.4] (median [interquartile range]) total months of AID, inclusive of the 3-month pivotal trial. During the pivotal trial, HbA1c decreased from 7.4% ± 1.0% (57 ± 10.9 mmol/mol) to 6.9% ± 0.7% (52 ± 7.7 mmol/mol, P < 0.0001) and was maintained at 7.0% ± 0.7% (53 ± 7.7 mmol/mol) after 15 months total use (P < 0.0001 from baseline). Time in target range (70-180 mg/dL) increased from 57.2% ± 15.3% during standard therapy to 68.1% ± 9.0% during the pivotal trial (P < 0.0001) and was maintained at 67.2% ± 9.3% during the extension phase (P < 0.0001 from standard therapy). Participants spent a median 97.1% of time in Automated Mode during the extension phase, with one episode of severe hypoglycemia and one episode of diabetic ketoacidosis. Conclusion: This evaluation of the Omnipod 5 AID System indicates that long-term use can safely maintain improvements in glycemic outcomes with up to 2 years of use in very young children with type 1 diabetes. Clinical Trials Registration Number: NCT04476472.

Objectives: To report the safety and side effects associated with taking verapamil for beta -cell preservation in children with newly -diagnosed T1D. Research Design and Methods: Eighty-eight participants aged 8.5 to 17.9 years weighing >= 30 kg were randomly assigned to verapamil (N = 47) or placebo (N = 41) within 31 days of T1D diagnosis and followed for 12 months from diagnosis, main CLVer study. Drug dosing was weight -based with incremental increases to full dosage. Side effect monitoring included serial measurements of pulse, blood pressure, liver enzymes, and electrocardiograms (ECGs). At study end, participants were enrolled in an observational extension study (CLVerEx), which is ongoing. No study drug is provided during the extension, but participants may use verapamil if prescribed by their diabetes care team. Results: Overall rates of adverse events were low and comparable between verapamil and placebo groups. There was no difference in the frequency of liver function abnormalities. Three CLVer participants reduced or discontinued medication due to asymptomatic ECG changes. One CLVerEx participant (18 years old), treated with placebo during CLVer, who had not had a monitoring ECG, experienced complete AV block with a severe hypotensive episode 6 weeks after reaching his maximum verapamil dose following an inadvertent double dose on the day of the event. Conclusions: The use of verapamil in youth newly -diagnosed with T1D appears generally safe and well tolerated with appropriate monitoring. We strongly recommend monitoring for potential side effects including an ECG at screening and an additional ECG once full dosage is reached. ClinicalTrials.gov number: NCT04233034.

Objective Examine patient-reported outcomes (PROs) after the use of t:slim X2 insulin pump with Control-IQ technology (CIQ) in young children with type 1 diabetes. Methods Children with type 1 diabetes, ages 2 to < 6 years (n = 102), were randomly assigned 2:1 to either CIQ or standard care (SC) with pump or multiple daily injections (MDI) plus continuous glucose monitoring (CGM) for 13 weeks. Both groups were offered to use CIQ for an additional 13 weeks after the randomized control trial's (RCT) completion. Guardians completed PRO questionnaires at baseline, 13-, and 26-weeks examining hypoglycemia concerns, quality of life, parenting stress, and sleep. At 26 weeks, 28 families participated in user-experience interviews. Repeated measures analyses compared PRO scores between systems used. Result Comparing CIQ vs SC, responses on all 5 PRO surveys favored the CIQ group, showing that CIQ was superior to SC at 26 weeks (p values < 0.05). User-experience interviews indicated significant benefits in optimized glycemic control overall and nighttime control (28 of 28 families endorsed). All but 2/28 families noted substantial reduction in management burden resulting in less mental burden and all but 4 stated that they wanted their children to continue using CIQ. Conclusions Families utilizing CIQ experienced glycemic benefits coupled with substantial benefits in PROs, documented in surveys and interviews. Families utilizing CIQ had reduced hypoglycemia concerns and parenting stress, and improved quality of life and sleep. These findings demonstrate the benefit of CIQ in young children with type 1 diabetes that goes beyond documented glycemic benefit.