CONTEXT:The frequency and acuity at diagnosis of youth-onset type 1 diabetes (T1D) and type 2 diabetes (T2D) were reported as higher in the first year of the COVID-19 pandemic, but it is unclear if these trends persist. OBJECTIVE:To describe trends in new cases of youth-onset diabetes comparing the first 2 years of the COVID-19 pandemic with the 2 preceding years. DESIGN:Retrospective study. SETTING:Twenty-three clinical centers in the United States. PATIENTS:New-onset T1D and T2D in youth between March 1, 2018, and February 28, 2022. MAIN OUTCOME MEASURES:New diagnosis of youth-onset T1D or T2D and acuity at diagnosis. RESULTS:A total of 4851 youth were diagnosed with T1D in the prepandemic period [year (Yr) 1: March 1, 2018, to February 28, 2019; Yr 2: March 1, 2019, to February 29, 2020] and 5955 individuals during the pandemic (Yr 3: March 1, 2020, to February 29, 2021; Yr 4: March 1, 2021, to February 28, 2022), a 22.8% increase (nonsignificant). The proportion of diabetic ketoacidosis in T1D was higher during (43.41%) vs prepandemic (37.77%, P < .01). For T2D, 1610 youth were diagnosed in the prepandemic period while 3443 patients were diagnosed with T2D during the pandemic (a 114% increase). The increase in frequency of T2D attributable to the pandemic from Yr 2 to Yr 3 was 76.8% (P < .01), while the increase from Yr 3 to Yr 4 was not significant. CONCLUSION:In youth, the frequency of both T1D and T2D increased during the COVID-19 pandemic but was significant only for T2D. When controlled for yearly trends, only the frequency of T2D increased significantly in the first year of the pandemic, suggesting that the pandemic environment differentially impacted rates of T1D and T2D in youth.

Among the most impactful therapeutic advances in the management of diabetes over the past two decades has been the development of incretin-based therapies, specifically glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) and in combination with glucose-dependent insulinotropic polypeptide (GIP) RAs. Since the introduction of exenatide in 2005, a growing number of these drugs has transformed the management of type 2 diabetes (T2D). Their pleiotropic effects include weight loss, reduced insulin resistance, improved glucose regulation, and reductions in known risk markers for diabetic kidney disease and cardiovascular disease. To date, these important noninsulin glucose-lowering therapies have only received regulatory approval for use in T2D, obesity, sleep apnea, and metabolic dysfunction-associated steatohepatitis with moderate-advanced fibrosis, supported by randomized controlled trials (RCTs) and real-world data that demonstrate efficacy and safety. Regulatory approval for use of weekly GLP-1 and GLP-1/GIP RAs in type 1 diabetes (T1D) has not yet been achieved, in part because of the limited number of inconsistent, small-scale, RCTs and real-world studies for glycemic impacts of these agents in T1D. Larger RCTs are ongoing or planned in participants with T1D. Potential safety risks include hypoglycemia and hyperglycemia-related ketosis in T1D after initiation of GLP-1/GIP RA drugs. While RCTs are ongoing to further investigate GLP-1 and GLP-1/GIP RA agents as adjunct therapy for people with T1D, access to these drugs is already possible, based on their use to treat overweight and obesity. However, without regulatory approval for the T1D indication, access and opportunities for people with T1D to engage with important education regarding the safety of GLP-1 and GLP-1/GIP RA therapy may be limited. This precludes support from diabetes health care professionals to optimize diabetes management of these agents alongside expected insulin dose changes. The purpose of this consensus report is to review the current literature and provide guidelines for diabetes clinicians and people with T1D to facilitate the safe use of GLP-1/GIP RAs in the management of T1D. This consensus statement has been endorsed by the following professional associations: Advanced Technologies & Treatments for Diabetes (ATTD), International Diabetes Federation-Europe, American Association of Clinical Endocrinologists (AACE), Breakthrough T1D, International Society for Pediatric and Adolescent Diabetes (ISPAD), Association of Diabetes Care and Education Specialists (ADCES).

Objective: To assess differences in time in range (TIR) between automated insulin delivery systems (AID) in youth with low bolus frequency. Research Design and Methods: Youth using Omnipod 5 (OP5) or Tandem Control-IQ (CIQ) averaging ≤3.0 boluses/day over 90-days were included. Propensity score matching accounted for between-group differences. A multiple linear regression model assessed for differences in TIR by system. Results: 202 youth had low bolus frequency (CIQ n=75 of 290, OP5 n=127 of 535, p=0.5). Propensity score matching paired 98 youth for analyses and eliminated between-group differences, excluding time in automated insulin delivery which remained higher for CIQ-users (80.0% vs 64.0%, p=0.01). There was no between-group difference in user-initiated boluses (2.2 boluses/day). Adjusted TIR was 8.0% higher in CIQ-users (54.9% vs 46.9%, p=0.002). Conclusions: Among AID users with ≤3.0 boluses/day, CIQ use was associated with greater TIR, likely due to increased time in automated delivery and AID-initiated boluses.

INTRODUCTION:The present study assessed the impact of the disposable Simplera Sync™ sensor with the MiniMed™ 780G (MM780G) advanced hybrid closed-loop (AHCL) system on type 1 diabetes (T1D) glycemic metrics, insulin delivery, and safety. MATERIALS AND METHODS:Youths (aged 7-17 years) and adults (aged 18-80 years) with T1D were enrolled in this single-arm, nonrandomized study at 24 sites in the United States. Participants began with an ∼2-week run-in period where hybrid closed-loop (HCL; auto basal only) or open-loop insulin delivery was used, followed by an ∼3-month study period with AHCL activated. Glycemic outcomes and insulin delivery during the last 6-7 weeks of the study, when settings were optimized at investigator's discretion, were compared with the run-in. Glycemic outcomes with the use of recommended optimal settings (ROS, 100 mg/dL glucose target with a 2-h active insulin time) were explored. RESULTS:Time in automation was high (>93%) and mean time in range (TIR) increased from 54.4% ± 15.7% to 71.4% ± 9.9% (P < 0.001) in youths and from 66.5% ± 12.6% to 80.2% ± 8.1% (P < 0.001) in adults, primarily due to reduced time above range. Youths had a slight increase in time below range (TBR <70 mg/dL) from 1.6% ± 1.7% to 1.9% ± 1.4% (P < 0.001), while adults had no significant difference in TBR. For ROS users, TIR was 74.7% ± 9.3% in youths and 83.8% ± 7.4% in adults. Throughout the study ∼60% of total daily insulin dose was automated (auto basal and auto correction) in both cohorts. There were two cases of severe hypoglycemia and one episode of diabetic ketoacidosis (not related to the device). CONCLUSIONS:MM780G use with the Simplera Sync sensor is safe and demonstrated improved glycemic outcomes in both pediatric and adult participants with T1D, compared with the run-in period.

Background: Studies investigating the safety and efficacy of automated insulin delivery (AID) systems in people with cystic fibrosis-related diabetes are limited. There are no published studies investigating the tubeless Omnipod 5 (OP5) AID system. Methods: This dual-center retrospective cohort study compared 14 days of baseline continuous glucose monitoring (CGM) data with days 1-90 and 91-180 post-OP5 initiation. Multivariable mixed-effects linear regression models were used to assess changes in glycemic metrics. Results: Among the 26 individuals with sufficient data initiating OP5, 65% were female, with a median age of 27.3 years and median diabetes duration of 10.9 years. Six (23%) had a history of solid organ transplant, and 2 (8%) were receiving enteral tube feeds. Participants transitioned to OP5 from multiple daily injections (54%), prior Omnipod generation (31%), or another AID system (15%). CGM time in range (70-180 mg/dL) increased from 54% (95% confidence interval [CI]: 45.0, 63.0) to 64% (95% CI: 57, 71.8, P < 0.001) during the first 90 days and to 62.7% (95% CI: 54.9, 70.5, P < 0.001) during 91-180 days. Time above range (TAR) 181-250 mg/dL and TAR >250 mg/dL improved at 1-90 days and 91-180 days compared with baseline (P = 0.001 and P = 0.002, respectively). There were no significant changes in time below range (54-69 mg/dL, <54 mg/dL) or coefficient of variation. Two individuals discontinued OP5 within 14 days due to persistent hypoglycemia. One adult experienced a hypoglycemic seizure after 3 months of use. Conclusions: Use of the OP5 system in youth and adults with CFRD led to significant improvements in multiples measures of hyperglycemia without a change in CGM-measured hypoglycemia over a 6-month period, although patient experience with hypoglycemia may limit sustained use. Given the unique comorbidities and pathophysiology of CFRD, these results emphasize the need for future studies to investigate the safety and efficacy of AID devices in this patient population.

Introduction: Consensus guidelines recommend reviewing 14 days of continuous glucose monitor (CGM) data when assessing glycemia in people with type 1 diabetes (T1D). Adult studies have shown that 7 days of CGM data provide a reliable assessment of glycemia. Objectives: To understand the minimum amount of CGM data required to assess glycemia in the pediatric T1D population. Methods: Real-world Dexcom G6 CGM data were extracted from cloud-based CGM software for 8 time windows (3, 5, 7, 10, 14, 30, 60, and 90 days), all starting on March 1, 2023. Youth <21 years with T1D and ≥70% CGM active time in each window were included. Pearson correlation and interclass correlation coefficients (ICCs) between 14-day data and other windows were calculated. Differences in the percentage of youth within predetermined thresholds of 14-day CGM metrics (±0.3% glucose management indicator [GMI]; ±5% time in range [TIR]/time in tight range; ±1% time below range <70 and <54 mg/dL) were assessed using chi-squared analyses. Sub-analyses were conducted according to categorical groupings of 14-day TIR, coefficient of variation (CV), and age. Results: A total of 1316 youth were included (45.0% female, 76.9% non-Hispanic White, median age 14.6 years). Median 14-day CGM active time was 97.2% and GMI and TIR were 7.4% (7.0, 7.9) and 60.5% (48.6, 70.6), respectively. Pearson correlation coefficients and ICCs between 14-day and GMI and TIR for all 8 windows were >0.9; however, categorical agreement as defined by the percentage of subjects acceptable thresholds for GMI and TIR only exceeded 90% at 10 days. Although there was no difference in agreement for CGM metrics according to categorical groupings of age, agreement was stronger for youth with TIR ≥70% and CV <36%. Conclusions: Although 14 days of CGM data are considered the gold standard, assessing ∼9.6 days of data in youth with T1D provides a reliable assessment of glycemia. For youth with higher TIR (≥70%) and lower CV (<36%), 7-day CGM data may prove sufficient.

Introduction and Objective: Prior real-world studies of youth with type 1 diabetes (T1D) did not identify significant differences in time in range (TIR) between Insulet Omnipod 5 (OP5) and Tandem Control IQ (CIQ) users. In this follow-up study, we assessed differences in glycemia between youth with low bolus frequency. Methods: This single center, retrospective study included youth managing T1D with OP5 or CIQ who averaged ≤3 boluses/day over a 90-day period (6/15/24-9/12/24). Propensity scores following nearest-neighbor 1:1 matching with a caliper width requirement of 0.2 were used to account for between group differences. A multiple linear regression model adjusting for covariates (race/ethnicity, insurance, sex, T1D duration, CGM active time, manual boluses/day) assessed for differences in TIR by AID system in the propensity matched sample. Results: A total of 202 youth had low bolus frequency (CIQ n=75, OP5 n=127). CIQ users had a longer T1D duration (8.8 vs 7.9yrs, p=0.0001), higher CGM active time (91.7% vs 80.4%, p=0.0001), higher time in automated mode (81.3% vs 62%, p=0.0001), and higher total daily insulin dose (59.6 vs 49.5 units/day, p=0.0001). Propensity score matching paired CIQ users (n=49) with OP5 users (n=49). All between group differences were eliminated with propensity matching, with the exception of time in automated mode which remained higher for CIQ users (80% vs 64.0%, p=0.01). Demographics of the matched sample included: age 17.0yrs, 54.1% female, 68.4% NHW, 32.7% publicly insured. Median CGM active time was 87.7% and median manual bolus frequency was 2.2 boluses/day. Adjusted TIR was 8.0% higher (95% CI 2.9-13.1 p=0.002) in CIQ (54.9%) vs OP5 users (46.9%). Conclusion: In youth with T1D who bolus infrequently, CIQ use was associated with greater time in automated mode and greater TIR though neither group attained TIR goals. This information should be discussed when counseling families choosing an AID system. P. Chatty: None. R.J. Gallop: None. A. Rearson: None. S. Gera: None. J.N. Mountain: None. N. Alicea-Trelles: None. B.E. Marks: Consultant; Insulet Corporation. Board Member; International Society for Pediatric and Adolescent Diabetes. Research Support; Tandem Diabetes Care, Inc, Dexcom, Inc., Medtronic. Advisory Panel; T1D Exchange. B.E.M. is supported by the National Institutes of Health (PI: Marks, NIH: K23DK129827).

The Dexcom G7 continuous glucose monitor is labeled for 10 days of wear. We assessed the real-world duration of Dexcom G7 sensor wear in youth with type 1 diabetes (T1D) in this single-center retrospective cohort study. Median duration of sensor wear was calculated for youth using ≥3 sensors over a 93-day period (May 13, 2024, to August 13, 2024). Overall, 643 unique individuals (15.1 years, 45.1% female, 66.3% non-Hispanic White, 60.2% privately insured, 4.9 years T1D duration) wore 5055 sensors over the 93 days. The median sensor wear time was 8.6 days (interquartile range 7.3, 9.6). Wear time was <7.0 days for 24.8% of sensors, and just 39.9% of sensors were worn for ≥10.0 days. In summary, the real-world duration of Dexcom G7 sensor wear is <10 days for most youth with T1D. Whereas people with diabetes typically receive 36 sensors per year, with a median wear time of 8.6 days, youth would require 43 sensors or more to allow for continuous use.

Limited insulin pump cartridge volumes can present challenges to automated insulin delivery (AID) system use for adolescents and young adults (AYA) with type 1 diabetes (T1D) and high insulin requirements. We assessed the real-world safety and effectiveness of U200 concentrated insulin use in AID (U200-AID) among AYAs with T1D. We conducted a two-center, retrospective cohort study assessing glycemia, pump utilization, and safety outcomes pre-/post-U200-AID. Among 50 AYAs initiating U200-AID (age 15.4 years, T1D duration 5.5 years, hemoglobin A1c 8.5%), time in range (70-180 mg/dL) increased (44.6% ± 12.6% vs. 48.9% ± 11.4%, P = 0.012) and time below range (<70 mg/dL) did not change significantly. Days between cartridge changes increased (2.2 ± 0.5 vs. 3.0 ± 0.5 days, P < 0.001) despite increased total daily insulin dose (102.6 ± 23.5 vs. 125.8 ± 38.9 U100 insulin units, P < 0.001). No severe hypoglycemia or diabetic ketoacidosis occurred (median follow-up 290 days [interquartile range 227, 476]). These data suggest that U200-AID is a viable option for individuals with T1D and high insulin requirements.

Background: Use of automated insulin delivery (AID) systems improves glycemic control, however, racial and ethnic disparities in glycemic control among youth with type 1 diabetes (T1D) persist. We studied whether the Omnipod 5 (OP5) AID system could close gaps in glycemia between White and Black youth with T1D. Methods: This retrospective longitudinal analysis compared matched pairs of White and Black youth with T1D using OP5 at two pediatric academic centers. In unadjusted and adjusted models, we assessed changes in the gap in time in range (TIR), average continuous glucose monitor (CGM) glucose, and hemoglobin A1c (HbA1c) between White and Black youth from baseline to 9 days and 90 days. Results: Matched pairs (n = 132) of White and Black youth using OP5 (61% female, mean age 11.6 years, 40% publicly insured, median T1D duration 2.9 years, mean HbA1c 8.6%) were included. Within 9 days of OP5 use, the baseline TIR gap of 7.8% points decreased to 3.9% points (P = 0.052), and the average CGM glucose gap of 20.5mg/dL at baseline decreased to 8.0 mg/dL (P = 0.012), demonstrating a reduction in the gap between groups. At 90 days, there was no significant reduction in gap from baseline for TIR (P = 0.35) or CGM glucose (P = 0.09). When adjusting for insurance and baseline insulin delivery method, there was no significant reduction in gaps at either 9 days or 90 days. All youth had decreases in HbA1c. At 90 days, time in automated mode (88% vs. 94%, P < 0.0001) and boluses per day (3.9 vs. 5.3, P < 0.0001) were lower in Black youth. In multivariable analysis, youth transitioning to OP5 from multiple daily injections had the greatest increases in TIR at 9 days (P < 0.001) and at 90 days (P < 0.01). Conclusions: Gaps in TIR and average CGM glucose between White and Black youth narrow with AID use, but do not close completely. Equitable access to AID should be encouraged for all youth, however, differences in AID interaction emphasize the need for additional interventions to overcome social determinants of health that likely explain the inability of diabetes technology to fully close the gaps.

PURPOSE:The purpose of this study was to explore the educational experiences of youth with type 1 diabetes (T1D), their parents, and clinicians when initiating continuous glucose monitoring (CGM) and insulin pumps. METHODS:Twenty parent-child dyads with T1D ≥6 months and ≥1 month CGM and insulin pump use were eligible to participate in semistructured dyadic interviews. Purposive sampling was used to recruit youth with a range of A1C levels and to overrepresent dyads from minoritized backgrounds. Eight diabetes clinicians with ≥1 year of experience participated in individual interviews using a parallel interview guide. A subset of interviews was double-coded, and thematic analysis was used to generate themes. RESULTS:Poor internet connections, distractions in the home, and small screens made in-person education the preferred modality for dyads and clinicians due to the physical skills required when learning to use these devices. Structured education addressing essential topics was constrained by allotted appointment times and thus (1) often overlooked cognitive and emotional burdens of diabetes technology education and (2) insufficiently accounted for individual learning pace and capacity. Real-world experiential learning supported by the clinical team through telemedicine, phone calls, and electronic medical record messaging was often used to fill the gaps of structured education. CONCLUSIONS:Both clinicians and parent-child dyads initiating CGM and automated insulin delivery expressed a preference for in-person education. Although experiential learning can supplement important concepts not adequately addressed during structured education, relying solely on this approach may unintentionally omit crucial concepts. Educational strategies are needed to overcome information overload and support families in diabetes self-management.

Introduction and Objective: Adherence to OGTT screening for CF-related diabetes (CFRD) is poor. We assessed the accuracy of glucose measurements not requiring phlebotomy during an OGTT. Methods: Standard OGTT with plasma glucose sampling at 0, 60, and 120-min was conducted in youth ≥10y with CF. Glucoses were measured simultaneously using a self-administered OGTT kit (Digostics GTT@Home), home glucometer (Contour Next) and hospital glucometer (StatStrip). Dexcom G7 continuous glucose monitor (CGM) interstitial glucose was recorded at 0, 60, and 120-min and at 5 min intervals for 20 min after each time point accounting for lag. Absolute glucose, median differences, and categorical glucose tolerance [normal (NGT), impaired (IGT), indeterminate (IGT), CFRD] were assessed for all methods (Table 1). Results: Plasma glucose tolerance was categorized as: NGT (n=8), IGT (n=5), and CFRD (n=1). Alternative measurement approaches correctly categorized CFRD, except the GTT@Home. Agreement for categorical diagnoses of glucose tolerance was strongest for CGM at 20-min post-OGTT time point (85.7%) and StatStrip (78.6%). Categorical agreement was poorest for the GTT@Home (54.5%). Conclusion: CGM, home glucometer, and hospital glucometer correctly diagnosed CFRD in one subject. Alternative approaches to glucose measurement did not reliably assess other glucose tolerance categories. S. Meighan: None. D.M. Johnson: None. R.J. Gallop: None. A. Kelly: None. M.S. Putman: Consultant; Anagram Therapeutics. Research Support; Dexcom, Inc. Other Relationship; Vertex Pharmaceuticals Incorporated. B.E. Marks: Consultant; Insulet Corporation. Board Member; International Society for Pediatric and Adolescent Diabetes. Research Support; Tandem Diabetes Care, Inc, Dexcom, Inc., Medtronic. Advisory Panel; T1D Exchange. Cystic Fibrosis Foundation (004524122)

Background Adherence to annual OGTT screening for cystic fibrosis-related diabetes (CFRD) is poor. In this mixed methods study we assessed the accuracy, feasibility, and acceptability of alternative approaches to glucose measurements during an OGTT. Methods Standard OGTT with plasma glucose sampling at 0, 60, and 120-min was conducted in 14 youth ≥ 10 years of age with CF. A self-administered OGTT kit (Digostics, GTT@home) measuring capillary glucose and Dexcom G7 continuous glucose monitoring (CGM) were performed concomitantly with OGTT. CGM glucose values were recorded at 5-minute intervals for 20-minutes after each time point to account for lag. Plasma OGTT glucose and glucose tolerance categories [normal (NGT), impaired (IGT), indeterminate (INDET), and CFRD] were compared with these same outcomes as defined by the self-administered kit and CGM. Younden’s index was used to determine the optimal CGM timepoint for categorization of glucose tolerance, and ROC curves were used to identify the optimal glucose thresholds. Participants and their parents were interviewed to understand their experience with alternative testing approaches. Results Based on plasma glucose, participants were characterized as NGT (n = 8), IGT (n = 5), and CFRD (n = 1). Whereas the GTT@home correctly categorized glucose tolerance in 6 participants (43 %), CGM correctly categorized 13 (93 %). The CGM glucose at 125 min was identified as the timepoint at which the measured glucose yielded maximum discrimination for all categories of glucose tolerance (AUC for NGT = 0.979, IGT = 0.867, CFRD = 1.0). A CGM glucose threshold of 154 mg/dL demonstrated 100 % sensitivity and 87.5 % specificity for identifying NGT; for IGT a threshold of 182 mg/dL exhibited 80 % sensitivity and 88.9 % specificity. Parent-child dyads valued convenience during OGTT screening, but expressed concerns about glucose measurement accuracy and performing medical procedures in the home. Conclusions CGM glucose values during OGTT may offer an accurate assessment of glucose tolerance categories, though this approach may require further refinement for patient acceptability.

Introduction and Objective: The ACGME requires pediatric endocrinology fellows to master diabetes management, including AID. Despite the demonstrated benefits of AID, many youth are unable to attain glycemic targets. Insufficient clinician understanding of AID may contribute to suboptimal clinical outcomes. Methods: We evaluated pediatric endocrinology fellows' AID knowledge using a 42-item survey distributed to Pediatric Endocrine Society members. Responses to 5 point Likert scale questions were grouped into agree and disagree (4,5 v 1,2,3). Pearson’s chi-squared assessed for differences in knowledge of specific AID systems. Results: Pediatric endocrinology fellows (n=54) and attending physicians (n=52) participated. Because responses did not differ between groups, data are presented in aggregate. The majority (98%) agreed about the importance of endocrinologists understanding AID, and 37% reported fellowship was the most common source of AID knowledge. Although 91% agreed that a formal AID curriculum for trainees would improve patient care, only 35% had a curriculum at their institution. For the most commonly (Omnipod 5) versus least commonly used systems (iLet) there were significant differences (all p<0.01) in perceived comfort in counseling about AID system features (86% v 39%), managing AID users (86% v 40%), changing settings (79% v 30%), analyzing reports (82% v 29%), ketone management (89% v 42%), and exercise management (83% v 31%). Regardless of system, fellows were uncomfortable (47%) counseling youth with low total daily insulin needs in choosing an AID system. Conclusion: Despite near universal agreement about the importance of trainees understanding AID, current education is perceived as inadequate. With limited access to formal curricula trainees are primarily learning about AID experientially, creating challenges for mastering less commonly used systems. Formal AID curricula are needed to support fellows in attaining ACGME requirements. J. Iyer: None. S. Meighan: None. B.E. Marks: Consultant; Insulet Corporation. Board Member; International Society for Pediatric and Adolescent Diabetes. Research Support; Tandem Diabetes Care, Inc, Dexcom, Inc., Medtronic. Advisory Panel; T1D Exchange. NIH T32 Grant (GRT-00004137)Children's Hospital of Philadelphia, Center for Leadership and Innovation in Medical Education (CLIME) Educator Development Grant

Purpose The purpose of the study was to identify the most common reasons for and timing of continuous glucose monitoring (CGM) attrition in youth with type 1 diabetes (T1DM). Methods This single center retrospective chart review included youth with T1DM <22 years seen between November 1, 2021, and October 31, 2022. Data were gathered from CGM cloud-based software and the electronic medical record. Results Among 2663 youth, 88.3% (n = 2351) actively used CGM, and 5.9% (n = 311) had CGM attrition. Those who discontinued CGM were older (17.0 vs 14.9 years, P = .0001), had a longer T1DM duration (7.4 vs 5.1 years), higher A1C (9% vs 7.4%), and were non-Hispanic Black (NHB; 34.0% vs 11.5%). The odds of CGM attrition were 5.0 and 2.8 times higher in NHB and Latine youth, respectively, compared to non-Hispanic White youth. Median time to CGM discontinuation was 4 months, 21 days after initiation; 57% of youth who discontinued did so in the first 6 months of use. The most common reasons for CGM attrition were problems with device adhesion (18.4%), dislike device on the body (10.8%), insurance problems (9.5%), pain with device use (8.3%), and system mistrust due to inaccurate readings (8.2%). NHB and Latine youth were more likely to discontinue CGM due to insurance problems (3.2% vs 15.1% vs 16.7%). Conclusions To support equitable, uninterrupted CGM use, education at CGM initiation should address practical approaches to improve adhesion and wearability and provide a clear pathway to obtaining supplies. Interventions to support sustained CGM use should occur within the first 6 months of initiation.

INTRODUCTION:Automated insulin delivery systems (AID) have revolutionized type 1 diabetes (T1D) management. Guidelines support offering AID to all people with T1D and engaging in shared decision making when choosing among the available AID systems. RESULTS:In clinical trials, AID has been shown to improve glycemic control and reduce hypoglycemia while also improving quality of life. However, participants in clinical trials do not accurately reflect the entire T1D population and outcomes from these controlled may not generalize to clinical care. A growing body of real-world evidence seeks to understand the effect of AID systems on glycemia and person-reported outcome measures in real-world populations. These real-world studies highlight the effect of differences in engagement with AID, including time in automated mode and boluses per day, considerations about AID system selection, and approaches to educate people with T1D. CONCLUSION:In this review, we compare glycemic and person reported outcomes in clinical trials and the real-world studies, with consideration of the effects of different systems according to user characteristics. We also review the current state of device selection and education for people with diabetes, their caregivers, and clinicians. Lastly, we summarize key findings across AID systems and opportunities for further research.

BACKGROUND:Inequities in the clinical care and health outcomes of youth and young adults (YYAs) with type 1 diabetes mellitus (T1D) and type 2 diabetes mellitus (T2D) are well-established. Systemic and institutional racism and barriers, as well as implicit biases underlie these inequities in the USA. SUMMARY:This article offers a broad overview and analysis of disparities in clinical care and outcomes among YYAs with T1D and T2D, framed within an ethical context. We argue that achieving ethical care requires centering assessments of patient and family needs within the realities of their lived experiences, as well as structural barriers and challenges. We examine the impact of structural racism and implicit bias on clinical care and explore how factors such as non-English language communication, literacy, numeracy, nutrition, school nursing services, access to diabetes technology and medications, and insurance disparities influence diabetes management and outcomes. The article concludes with a call to action and concrete recommendations to address and reduce these inequities. KEY MESSAGES:Clinicians can play a pivotal role in reducing diabetes-related healthcare disparities by adopting an ethical approach that centers upon lived experiences of YYA with diabetes thereby identifying opportunities for more equitable care.

The use of automated insulin delivery systems (AID) is standard of care for people with type 1 diabetes. However, the limited capacity of insulin pump cartridges, which can hold 1.6-3.0mL or the equivalent of 160-300 units of U100 insulin, can be a barrier to AID use for individuals with high total daily insulin (TDI) requirements. With the rising prevalence of obesity, expansion of AID use to type 2 diabetes, and trends towards smaller cartridge volumes to decrease the size of devices, practical solutions to reduce barriers to AID use for those with high TDI requirements are needed. U200 concentrated rapid-acting insulin (U200) has a similar pharmacokinetic and pharmacodynamic profile to U100 insulin, provides the same dose of U100 insulin in half of the volume, and has been used off-label to facilitate AID use for those with high TDI needs. In this perspective piece we provide practical considerations for clinical implementation of U200 use in AID systems, including identification of candidates, unique considerations in filling pumps with U200 insulin, guidance on programming appropriate AID settings for the different algorithms, concepts to address in patient education, and recommendations for standardized documentation in the electronic health record.

CONTEXT:Glycemic outcomes in youth with type 1 diabetes (T1D) in the United States using the 2 most common automated insulin delivery (AID) systems, Insulet Omnipod 5 (OP5) and Tandem Control IQ (CIQ), have not been compared. OBJECTIVE:We performed the first head-to-head analysis of changes in glycemic metrics among youth initiating AID. METHODS:This single-center, retrospective study included youth < 21 years with T1D, who started OP5 or CIQ between January 2020 and December 2023, and had ≥ 70% continuous glucose monitoring (CGM) active time. We obtained 14-day baseline and 90-day CGM and AID data. A multiple linear regression model assessed for changes in 90-day time in range (TIR) according to AID system, adjusting for covariates. Subanalyses were conducted according to baseline TIR categories. RESULTS:Among the 428 included youth, there were 214 (50%) in each AID group. OP5 users had a shorter T1D duration (1.6 vs 5.5 years, P < .001) and were more likely to have transitioned from multiple daily injections (76.1% vs 20.1%, P < .001). Baseline TIR was similar between groups (OP5 51.6% vs CIQ 53.1%, P = .70). 90-day TIR increased in both groups (P < .001), rising by 11.8 percentage points (95% CI [10.4, 13.3]) in OP5 users and 9.8 percentage points (95% CI [8.3, 11.2]) in CIQ users, without any significant between-group differences (P = .08). There were no between-group differences in 90-day TIR according to categorical baseline TIR. CONCLUSION:There are no clinically significant differences in 90-day TIR among youth with T1D initiating the 2 most commonly used AID systems. Patient preference and shared decision making should continue to guide the selection of AID systems.