Introduction and Objective: Our goal was to identify the value of continuous glucose monitor (CGM) screening to identify individuals with stage 2 type 1 diabetes (T1D). If these individuals are identified, then useful treatments, such as teplizumab, may help delay the onset of stage 3 (symptomatic) T1D. Methods: We used a group consensus process consisting of an in-person meeting of authors and panelists on October 15, 2024, and a virtual meeting with additional panelists. Following conversations at these meetings, the authors drafted the article and sent the first and second draft out for review, comments, and endorsement by the remaining in-person and virtual panelists. Results: The committee developed sixteen conclusions about CGM screening for stage 2 T1D, in three different categories: current status of screening for stage 2 T1D, current status of CGM screening for stage 2 T1D, and future status of CGM screening for stage 2 T1D (see table). Conclusion: CGM offers promise as a tool to identify people with stage 2 T1D. These individuals could then undergo traditional venous blood glucose testing to screen for stage 2 T1D, to confirm the diagnosis so that an immune protective drug may be prescribed. Eventually, instead of serving as an adjunctive tool, CGM testing may be designated to replace plasma glucose testing and HbA1c testing to identify individuals with stage 2 T1D who may benefit from immunotherapy. A. Ayers: Consultant; Liom Health AG. C. Ho: None. J.K. Mader: Advisory Panel; Abbott. Speaker's Bureau; Abbott. Advisory Panel; Eli Lilly and Company. Speaker's Bureau; Eli Lilly and Company. Stock/Shareholder; elyte Diagnostics. Advisory Panel; embecta. Speaker's Bureau; embecta, Menarini. Advisory Panel; Medtronic. Speaker's Bureau; Dexcom, Inc. Advisory Panel; Dexcom, Inc., Novo Nordisk A/S. Speaker's Bureau; Novo Nordisk A/S. Advisory Panel; Roche Diabetes Care. Speaker's Bureau; Roche Diabetes Care. Advisory Panel; Sanofi. Speaker's Bureau; Sanofi. Advisory Panel; Biomea Fusion, PharmaSens, Tingo Medical. Stock/Shareholder; decide Clinical Software. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. G. Freckmann: Advisory Panel; Abbott, Boydsense, Dexcom, Inc., Lilly Diabetes, Vertex Pharmaceuticals Incorporated. Speaker's Bureau; Abbott, Menarini, Roche Diabetes Care, Sinocare Inc. Research Support; Ascensia Diabetes Care, Bionime, i-Sens. Consultant; i-Sens, Perfood. Advisory Panel; PharmaSens. Consultant; Roche Diabetes Care, Sinocare Inc, Ypsomed AG. J.F. Garcia-Tirado: None. I.B. Hirsch: Research Support; Dexcom, Inc., Tandem Diabetes Care, Inc, MannKind Corporation. Consultant; Abbott, Roche Diabetes Care, Hagar. S.B. Johnson: None. D. Kerr: None. S.H. Kim: Other Relationship; Novo Nordisk. Consultant; TeCure. R. Lal: Consultant; Abbott, Biolinq, Capillary Biomedical, Inc, Gluroo, PhysioLogic Devices, Portal Insulin, Sanofi, Tidepool. Advisory Panel; Provention Bio, Inc, Provention Bio, Inc, Microbion, Microbion, Lilly Diabetes. Research Support; Insulet Corporation, Medtronic, Tandem Diabetes Care, Inc, Sinocare Inc. E. Montaser: None. H.K. O'Donnell: Advisory Panel; Sanofi. Other Relationship; Sanofi. V.N. Shah: Consultant; Dexcom, Inc. Advisory Panel; Sanofi, Novo Nordisk. Consultant; Lilly Diabetes. Advisory Panel; embecta. Consultant; Insulet Corporation. Advisory Panel; Tandem Diabetes Care, Inc, Ascensia Diabetes Care. Research Support; Enable Bioscience. Consultant; Genomelink and Lumosfit. D.C. Klonoff: Consultant; Synchneuro, Thirdwayv, Tingo, Afon, embecta, Glucotrack, Lifecare, Novo Nordisk, Samsung. Abbott Diabetes Care Sanofi

This consensus report evaluates the potential role of continuous glucose monitoring (CGM) in screening for stage 2 type 1 diabetes (T1D). CGM offers a minimally invasive alternative to venous blood testing for detecting dysglycemia, facilitating early identification of at-risk individuals for confirmatory blood testing. A panel of experts reviewed current evidence and addressed key questions regarding CGM’s diagnostic accuracy and screening protocols. They concluded that while CGM cannot yet replace blood-based diagnostics, it holds promise as a screening tool that could lead to earlier, more effective intervention. Metrics such as time above range >140 mg/dL could indicate progression risk, and artificial intelligence (AI)-based modeling may enhance predictive capabilities. Further research is needed to establish CGM-based diagnostic criteria and refine screening strategies to improve T1D detection and intervention.

Introduction and Objective: The Automated Insulin Delivery as an Adaptive NETwork FCL system may improve glycemic outcomes while reducing burden by eliminating meal announcement. Continuous glucose monitoring (CGM) metrics were compared in users with T1D using the FCL system who had high or low baseline A1c. Methods: Youth and adults with T1D were enrolled in a randomized crossover study with a supervised hotel stay followed by 7 days of home use in FCL compared to usual care (UC). Half were selected with baseline A1c <8% (low A1c) and half with baseline A1c 8-12% (high A1c). CGM metrics were analyzed by A1c subgroups. Results: Thirty-four participants (25.4±12.6 years, 62% female) completed the study. Those with high A1c showed non-inferiority of FCL vs UC on all CGM metrics and lower mean glucose with FCL (Table). Time in 70-180 mg/dL, in 70-140 mg/dL, >180 mg/dL, and >250 mg/dL showed significant improvement with FCL in the high A1c group. Those with low A1c had statistically equivalent mean glucose and time <54 mg/dL with FCL vs UC; other CGM metrics were inconclusive. Conclusion: Use of a FCL system results in significant improvement in CGM metrics in those with less optimal glycemic management, while not deteriorating control in those with more optimal A1c. FCL systems have the potential to make the most impact in those with challenges in meeting glycemic goals. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. M. Moscoso-Vasquez: Other Relationship; Dexcom, Inc. Research Support; Tandem Diabetes Care, Inc, National Institute of Diabetes and Digestive and Kidney Diseases. L. Ekhlaspour: Other Relationship; Medtronic. Advisory Panel; Abbott, Medtronic. Consultant; Jaeb Center for Health Research. Research Support; MannKind Corporation. Speaker's Bureau; Insulet Corporation. Advisory Panel; Sequel Med Tech. Other Relationship; Tandem Diabetes Care, Inc. Research Support; Abbott. Other Relationship; Sanofi. S.A. Brown: Research Support; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc, Tolerion, Roche Diabetes Care. Other Relationship; MannKind Corporation. M.D. Breton: Speaker's Bureau; Sinocare Inc, Tandem Diabetes Care, Inc. Consultant; Roche Diabetes Care, Boydsense. G.P. Forlenza: Advisory Panel; Medtronic. Research Support; Medtronic, Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; Insulet Corporation. Consultant; Insulet Corporation. Research Support; Tandem Diabetes Care, Inc. Advisory Panel; Tandem Diabetes Care, Inc. Research Support; Abbott. Advisory Panel; Sequel Med Tech. Breakthrough T1D

Introduction and Objective: Novel Interventions in Children’s Healthcare (NICH) has shown improved health outcomes for youth with diabetes experiencing inequity. NICH does not specifically target symptoms of mental health diagnoses (MHD)s, but never excludes youth and caregivers from enrollment and evaluation due to MHDs. Given uncertainty regarding role in NICH outcomes, this study explores prevalence of MHDs and related health outcomes for youth in NICH. Methods: Youth with diabetes (N=30; T1D=26, T2D=4) who participated in NICH at two new healthcare systems were included. Chart review collected HbA1c, emergency department visits, and days admitted one year prior to and during NICH enrollment. Provider-reported social drivers of health and MHD presence for youth and caregivers were also included. Non-parametric t-tests examined differences in health outcomes during NICH for those with and without MHDs. Results: Youth mean age was 13.2 years; 57% of youth were from historically marginalized racial and ethnic groups; 76% of youth and 53% of caregivers had a MHD. Youth with a MHD experienced higher mean A1c prior to NICH (12.8±1.4%) compared to youth without (12.1±2.2%; p<.03). Decreased mean HbA1c from baseline to post-NICH was found for all youth in NICH (12.6+1.7% to 11.2+2.3%; p<.001), youth with a MHD (12.8±1.4% to 11.8±2.3%; p<.02), youth of caregivers with a MHD (13.1±1.8% to 11.3±2.6%; p<.01), and youth of caregivers without a MHD (12.1±1.5% to 11.1±2.0%; p<.03). Youth of caregivers without a MHD also demonstrated a decrease in mean days admitted while in NICH (8.3±7.8 to 4.1±5.8; p<.01). All other baseline findings and changes over time were nonsignificant. Conclusion: NICH implementation at new sites continues to demonstrate clinically and statistically significant improvements in HbA1c. Co-occurring MHD in youth and caregivers served by NICH are common. NICH demonstrates improved HbA1c regardless of presence of MHD for youth with T1D or their caregivers. L.D. Hicks: None. K.A. Torres: None. L.J. Levy: None. D. Naranjo: Consultant; Sanofi. A. Reed: None. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. K.B. Spiro: None. N.A. Cisneros: None. I.C. Gomez: None. M.A. Harris: None. D.V. Wagner: None. The Leona M. and Harry B. Helmsley Charitable Trust

Introduction and Objective: Adverse childhood experiences (ACEs) are known to impact the health and well-being of those living with T1D. Less is known regarding how ACEs of a primary caregiver (parent, grandparent, etc.) may indirectly impact youth with chronic health conditions - potentially via influence on parenting practices. The current study investigates the relationship between caregiver ACEs, parenting practices, and health of youth with T1D. Methods: Youth (N=158) ages 12-17 years, with T1D for ≥1 year, and an HbA1c ≥ 10% in the past year were enrolled from 5 academic medical centers. Youth caregivers reported on parenting practices (Alabama Parenting Questionnaire) and their own ACEs (ex: experience of racial discrimination, parental death). Chart review collected HbA1c and ED visits 12 months prior to enrollment and ED visits 6 months following study enrollment. Chi square tests, bivariate correlations, and independent t-tests were conducted. Results: Youth mean age was 14.5+2 years with mean HbA1c of 11.1+2%. Less than 50% of youth were Non-Latinx white; 15.2% Latinx; 14.1% Black. Youth whose caregivers experienced specific ACEs were more likely to experience an ED visit than youth whose caregivers did not (parental divorce: 51.4% vs. 28.9%, p<.01; parental incarceration: 61.1% vs. 36.5%; p<.05; racial discrimination: 60.9% vs. 35.6%; p<.05). Youth of caregivers who experienced racial discrimination had more ED visits (M=1.4+1.4) than youth of caregivers who did not (M=0.7+1.6; p<.05). Caregiver experience of racial discrimination correlated with lower positive parenting (r=-.18) and poorer supervision (r=.17; p<.05). Conclusion: Findings demonstrate that ACEs in caregivers raising youth with T1D are associated with parenting practices and youth health. Given prior associations between parenting practices and T1D outcomes, and these findings regarding caregiver ACEs, healthcare systems should consider caregiver experiences and functioning as prime areas for potential screening and intervention. K.A. McMullen: None. K.A. Torres: None. J. Raymond: None. M.A. Clements: Consultant; Glooko, Inc. Research Support; Dexcom, Inc., Abbott. D. Naranjo: Consultant; Sanofi. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. A. Reed: None. S.R. Melnick: None. M.A. Harris: None. D.V. Wagner: None. JDRF

Objective: The primary objective of this study was to evaluate the first full-scale implementation of the behavioral health program Novel Interventions in Children's Healthcare (NICH) in racially and ethnically diverse youth with diabetes and high degrees of social risk. We hypothesized that youth would demonstrate improved health outcomes and psychosocial functioning following program involvement. Methods: Youth with diabetes who enrolled in NICH (n = 26) and their caregivers completed measures of diabetes distress, depression, and diabetes strengths prior to and following program enrollment. Electronic health records were reviewed to describe change in hemoglobin A1C, change in continuous glucose monitoring use, and change in the number of hospital admission days from baseline to the time following program participation. Parametric and nonparametric tests were used to compare data. Results: Youth (mean age, 13.7 +/- 3.5 years, 92% from historically marginalized racial or ethnic groups, 96% with public insurance) demonstrated a significant (P < .01) mean hemoglobin A1C reduction of -1.1% (-12 mmol/mol) and increase in continuous glucose monitoring use (27%-73%) 1 year following NICH enrollment, and they had significantly fewer hospital admission days over time. Youth reported significant reductions in depressive symptoms, and caregivers reported significant reductions in diabetes distress after participation in NICH (P < .05). Conclusion: This study is the first to show successful full-scale implementation of NICH in a new geographic location with unique racial and ethnic diversity and social challenges, demonstrating associations with improved health and well-being. (c) 2025 AACE. Published by Elsevier Inc. This is an open access article under the CC BY license (http://

Introduction and Objective: Youth receiving BFST for diabetes experienced improved diabetes self-management, parent-adolescent communication, and HbA1c. The BFST Skills Inventory (BFST-SI) was developed to assess intervention fidelity and family skills. While this measure has been used in numerous intervention studies for youth with diabetes, it has yet to be validated. This study aimed to examine the psychometric properties of the BFST-SI in youth participating in Novel Interventions in Children’s Health Care (NICH), a health equity intervention for youth with diabetes experiencing high social needs, medical risks, and healthcare costs. Methods: Youth participating in NICH at 3 academic medical centers completed the BFST-SI (N=127) and the Diabetes Strengths and Resilience Measure (DSTAR; N=48). The 20 BFST-SI items were examined using exploratory factor analysis with maximum likelihood extraction and direct oblimin rotation. Items with low item-to-total correlations and factor loadings (<0.3) were removed. Results: Youth with complete demographic data had a mean age of 15.4+1.9 years and mean HbA1c of 11.9+2.1%, with 96% on Medicaid. Fifteen items were retained and loaded onto 3 factors. Cronbach’s α was reliable for the total scale (α=.90) and each factor (α=.82-.89), which we labeled Family Problem Solving (6 items), Challenging Family Patterns (4 items), and Family Respect and Collaboration (5 items). BFST-SI total scores were correlated with DSTAR scores (r=.47, p<.01). Conclusion: The BFST-SI is a psychometrically sound measure used to assess BFST-D fidelity and family skill outcomes. This study adds to the extant literature demonstrating that family communication and problem-solving are critical skills for families of youth with diabetes. Screening for BFST skills will help identify families needing additional communication intervention and aid in treatment development and evaluation for youth with diabetes and their families. K.A. Torres: None. J. Shapiro: None. F.S. Richey: None. D. Naranjo: Consultant; Sanofi. A. Reed: None. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. M. Gonzales Granados: None. M.E. Hilliard: None. M.A. Harris: None. D.V. Wagner: None. The Leona M. and Harry B. Helmsley Charitable Trust

Introduction and Objective: HCL is the preferred insulin delivery method for people with T1D, however mealtime carbohydrate counting limits benefit. Use of AI to implement automated insulin delivery (AID) algorithms, able to avoid mealtime interactions, could alleviate burden and broaden use. We tested the latest UVA AID neural network-based system (AIDANET) in FCL in a people with T1D. Methods: Adults (>25 y, n=12), young adults (18-25 y, n=10), and adolescents (14-17 y, n=12) were enrolled at three sites to compare AIDANET in FCL to usual care in HCL (NCT06041917). Participants spent 5 days using FCL in a supervised hotel environment followed by 7 days of at-home use. Usual care data was collected randomly for two weeks before or after FCL use. The prespecified primary outcome was difference in mean CGM. Results: Overall, 34 participants (25.4±12.6 y, 62% F, HbA1c 8.0±1.1%) completed the study. Mean CGM significantly improved from 177.9 mg/dL with HCL to 163.8 mg/dL with FCL (-14.1 mg/dL; p=0.013; Table). TIR, TITR, TAR>180, and TAR>250 also significantly improved. TBR<70 and TBR<54 were non-inferior in FCL vs HCL. CV increased in FCL vs HCL but SD did not. Daily meal boluses decreased from 4.0±2.6 to 0.0±0.0 (p<0.001). Conclusion: Fully closed loop therapy with the AIDANET system can significantly improve average glycemia while removing the need for mealtime bolusing for people with T1D. G.P. Forlenza: Advisory Panel; Medtronic. Research Support; Medtronic, Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; Insulet Corporation. Consultant; Insulet Corporation. Research Support; Tandem Diabetes Care, Inc. Advisory Panel; Tandem Diabetes Care, Inc. Research Support; Abbott. Advisory Panel; Sequel Med Tech. M. Moscoso-Vasquez: Other Relationship; Dexcom, Inc. Research Support; Tandem Diabetes Care, Inc, National Institute of Diabetes and Digestive and Kidney Diseases. S.A. Brown: Research Support; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc, Tolerion, Roche Diabetes Care. Other Relationship; MannKind Corporation. G. Capodanno: None. E. Cengiz: Advisory Panel; Novo Nordisk, Arecor Therapeutics, Eli Lilly and Company, Tandem Diabetes Care, Inc, Portal Insulin, MannKind Corporation. E.C. Cobry: Advisory Panel; Dexcom, Inc. M.D. DeBoer: Research Support; Dexcom, Inc., Tandem Diabetes Care, Inc, Medtronic. R. Wadwa: Consultant; Dexcom, Inc., Tandem Diabetes Care, Inc. Advisory Panel; Provention Bio, Inc, Provention Bio, Inc, Microbion, Microbion, Sequel Med Tech. Research Support; Dexcom, Inc., Eli Lilly and Company, Tandem Diabetes Care, Inc. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. L. Ekhlaspour: Other Relationship; Medtronic. Advisory Panel; Abbott, Medtronic. Consultant; Jaeb Center for Health Research. Research Support; MannKind Corporation. Speaker's Bureau; Insulet Corporation. Advisory Panel; Sequel Med Tech. Other Relationship; Tandem Diabetes Care, Inc. Research Support; Abbott. Other Relationship; Sanofi. M.D. Breton: Speaker's Bureau; Sinocare Inc, Tandem Diabetes Care, Inc. Consultant; Roche Diabetes Care, Boydsense. Breakthrough T1D (2-SRA-2023-1275-M-B)

Introduction and Objective: The AIDANET system uses an adaptive algorithm that removes the need for meal announcement. This may help address age-specific obstacles in T1D, as older people may struggle with diabetes technology, while younger people face hormonal changes and inconsistencies in premeal dosing. Given these challenges, the glycemic outcomes of the AIDANET system in FCL were evaluated across three age groups. Methods: This study was a randomized, crossover trial evaluating the safety and feasibility of the AIDANET system. Sensor glucose data was collected from: Adolescents (14-17 y), Young Adults (18-25 y), and Adults (26-60 y). Participants used the system in FCL during a supervised hotel setting for 5 days followed by a 7-day home period. Each cohort underwent a 14-day usual care (UC) period. Results: The Adult cohort had a significant increase in TIR and TITR by 8.0% and 9.0%, respectively (Table). TAR180 also significantly decreased by 8.1%. Young Adults exhibited non-inferior results for TBR54 between UC and FCL. For Adolescents, TIR, TITR, TAR180, TAR250, and TBR54 values were non-inferior between UC and FCL. Conclusion: Adults significantly improved their glycemic outcomes with short-term use of the FCL system. Future research with long-term wear may be needed to give the system more time to adapt to the unique needs of all age groups. J.Y. Hosseinipour: None. G.P. Forlenza: Advisory Panel; Medtronic. Research Support; Medtronic, Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; Insulet Corporation. Consultant; Insulet Corporation. Research Support; Tandem Diabetes Care, Inc. Advisory Panel; Tandem Diabetes Care, Inc. Research Support; Abbott. Advisory Panel; Sequel Med Tech. L. Ekhlaspour: Other Relationship; Medtronic. Advisory Panel; Abbott, Medtronic. Consultant; Jaeb Center for Health Research. Research Support; MannKind Corporation. Speaker's Bureau; Insulet Corporation. Advisory Panel; Sequel Med Tech. Other Relationship; Tandem Diabetes Care, Inc. Research Support; Abbott. Other Relationship; Sanofi. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. E. Escobar: None. E.C. Cobry: Advisory Panel; Dexcom, Inc. M. Moscoso-Vasquez: Other Relationship; Dexcom, Inc. Research Support; Tandem Diabetes Care, Inc, National Institute of Diabetes and Digestive and Kidney Diseases. S.A. Brown: Research Support; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc, Tolerion, Roche Diabetes Care. Other Relationship; MannKind Corporation.

Introduction and Objective: Youth with T1D and elevated HbA1c experience higher rates of short- and long-term complications. While individuals from some racial and ethnic groups are at greater risk of disparities in HbA1c due to systemic barriers and discrimination, less is known about the impact on family functioning amongst youth already experiencing elevated HbA1c. This study examines disparities in racially and ethnically diverse youth with elevated HbA1c. Methods: Youth (N=217) from 5 academic medical centers were enrolled if they were 1) 12-17 years old, 2) diagnosed with T1D for ≥ 1 year, and 3) had an HbA1c ≥ 10%. Chart review collected HbA1c values. Youth and their caregivers completed measures of family functioning (Diabetes Family Conflict Scale-R, Diabetes Family Responsibility Questionnaire). Bivariate correlations and non-parametric t-tests were conducted. Results: Youth had a mean age of 14.6±1.6 years and mean HbA1c of 11.0±1.9%. 45.9% were non-Latinx White; 13.8% were Black; 21.6% were Latinx. Black youth experienced higher HbA1c and reported higher conflict regarding direct management of T1D levels compared to non-Black youth (p<.05). Latinx youth had higher indirect T1D responsibility (M=10.3 vs 8.7) and conflict regarding indirect management (M=13.4 vs. 11.8) compared to non-Latinx youth (p<.05). Higher youth-reported family conflict was associated with higher HbA1c (r=.29, p<.01). Conclusion: Youth with T1D from racial and ethnic groups who have been historically marginalized experience significant disparities in health and life outcomes, and this is even more evident in youth with elevated HbA1c. These findings suggest that disparities have an exponentially negative impact on Black and Latinx youth living with T1D. Interventions that are specifically designed for and implemented with minoritized youth with T1D need to be a priority in providing equitable access to specialty care, diabetes technology, and other health-promoting services and resources. E. Washington: None. K.A. Torres: None. J. Flores Garcia: None. C. Jenisch: None. J. Raymond: None. M.A. Clements: Consultant; Glooko, Inc. Research Support; Dexcom, Inc., Abbott. D. Naranjo: Consultant; Sanofi. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. A. Reed: None. M.A. Harris: None. D.V. Wagner: None. JDRF

Introduction and Objective: HCL has become standard therapy for T1D, with particular glycemic improvements overnight. These systems require meal announcement for optimal daytime glycemia. FCL therapy will reduce daytime diabetes management burden and may further improve nighttime glycemia. Methods: Adolescents (14-17yrs), young adults (18-25yrs), and adults (26-60yrs) were enrolled at 3 sites to evaluate a novel FCL system (Automated Insulin Delivery as an Adaptive NETwork [AIDANET]). AIDENET was initiated in a supervised hotel setting, followed by 7 days at home. Results were analyzed by time of day (nighttime: 12am-6am) and compared to usual care with HCL. T-tests were used to assess non-inferiority and difference of glycemic metrics with a primary outcome of mean sensor glucose. Results: 34 subjects (25.4±12.6 yrs, HbA1c 8.0±1.1%, 62% F) participated. Daytime FCL use was non-inferior, but not different, to HCL for all glycemic metrics except coefficient of variation (Table). Nighttime FCL wear was both non-inferior and significantly different (p<0.05) for most glycemic metrics. Conclusion: The AIDANET FCL system significantly improved nighttime glycemia and was equivalent during the daytime compared to HCL. Longer use studies are necessary to determine sustainability in the home setting. E.C. Cobry: Advisory Panel; Dexcom, Inc. M. Moscoso-Vasquez: Other Relationship; Dexcom, Inc. Research Support; Tandem Diabetes Care, Inc, National Institute of Diabetes and Digestive and Kidney Diseases. L. Towers: None. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. S.A. Brown: Research Support; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc, Tolerion, Roche Diabetes Care. Other Relationship; MannKind Corporation. L. Ekhlaspour: Other Relationship; Medtronic. Advisory Panel; Abbott, Medtronic. Consultant; Jaeb Center for Health Research. Research Support; MannKind Corporation. Speaker's Bureau; Insulet Corporation. Advisory Panel; Sequel Med Tech. Other Relationship; Tandem Diabetes Care, Inc. Research Support; Abbott. Other Relationship; Sanofi. Breakthrough T1D (2-SRA-2023-1275-M-B)

Introduction and Objective: Patient acceptance of an FCL automated insulin delivery (AID) system has not been previously studied. Methods: Adolescence (14-17yo), young adults (18-25yo), and adults (25-60yo) with type 1 diabetes enrolled in a randomized crossover device safety and feasibility study of the AIDANET system. Users participated in a 5-day supervised hotel stay, followed by 7 days at home. At baseline and after home use, users completed the INSPIRE survey, a measure of expectations of AID, and the Technology Acceptance Scale (TAS), which measures experiences with technology and the benefits and burdens. Paired t-tests were conducted for the whole cohort, each of the three age groups, and low HbA1c (<8.0%) and high HbA1c (8.0-12.0%) subgroups. Results: For the 33 participants (25.5±12.8yrs; 63%F), INSPIRE scores significantly decreased after 11 days of use (p=0.001). Young adults, adolescents, and low HbA1c groups showed significant decreases in INSPIRE scores (p=0.042, 0.006, 0.005, respectively). There was no significant change for adults and high HbA1c groups. TAS scores significantly decreased in adolescences (p=0.028), but remained unchanged in all other subgroups. There were no differences in changes between groups. Conclusion: Additional research is needed to determine user experience and acceptance after longer wear period of the AIDANET system. E. Escobar: None. L. Towers: None. G.P. Forlenza: Advisory Panel; Medtronic. Research Support; Medtronic, Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; Insulet Corporation. Consultant; Insulet Corporation. Research Support; Tandem Diabetes Care, Inc. Advisory Panel; Tandem Diabetes Care, Inc. Research Support; Abbott. Advisory Panel; Sequel Med Tech. E.C. Cobry: Advisory Panel; Dexcom, Inc. J.Y. Hosseinipour: None. A. Narayan: None. S.A. Brown: Research Support; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc, Tolerion, Roche Diabetes Care. Other Relationship; MannKind Corporation. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc.

Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians and the National Diabetes Education Program. This series is intended to highlight best practices and strategies from programs and clinics that have successfully improved the quality of care for people with diabetes or related conditions. Each article in the series is reviewed and follows a standard format developed by the editors of Clinical Diabetes. The following article describes an effort to improve diabetes-related retinopathy screening and documentation rates in eligible youth seen at an academic pediatric diabetes clinic in San Francisco, CA.

Introduction and Objective: Given the demands of T1D, youth with T1D can experience challenges to HRQOL. This study examines how HRQOL domains of youth with elevated HbA1cs are associated with health outcomes and compare to youth with other chronic conditions. Methods: Youth (N=157) from 5 children’s hospitals were included if 12-17 years old, T1D diagnosis for ≥1 year, and HbA1c ≥10% in past year. Youth completed the PROMIS Pediatric-25. Chart review collected emergency department (ED) visits and HbA1c. Literature review collected PROMIS outcomes for youth with other chronic conditions. Results: Youth mean age was 14.5+1.6 years; 45.9% female; 13% Latinx, 8% Black; HbA1c M=11.1+1.5%. Higher anxiety was associated with more frequent ED visits (r=.179; p<.05), and higher support from peers was related to lower HbA1c (r=-.171; p<.05). Youth reported moderate to severe ratings, respectively, for anxiety (28% and 22%), depression (24% and 23%), and fatigue (25% and 17%). Youth with elevated HbA1c showed greater challenges with HRQOL compared to youth with other health conditions (see Table). Conclusion: Youth with T1D and elevated HbA1c experience greater HRQOL impact compared to youth with other chronic conditions. Key HRQOL domains were associated with worse health outcomes. Given prevalent serious elevations across psychosocial domains, embedded psychosocial screening and treatment should be prioritized for youth with elevated HbA1c. R. Delgado-Kiggins: None. K.A. Torres: None. M.A. Clements: Consultant; Glooko, Inc. Research Support; Dexcom, Inc., Abbott. J. Raymond: None. D. Naranjo: Consultant; Sanofi. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. A. Reed: None. M.E. Hilliard: None. J. Flores Garcia: None. L.D. Hicks: None. M.A. Harris: None. D.V. Wagner: None. JDRF

Introduction and Objective: With the 2022 FDA approval of a disease-modifying therapy for the delay of stage 3 T1D, enthusiasm for T1D screening has grown. However, it remains unclear if healthcare practitioners are prepared to implement islet autoantibody screening and metabolic monitoring for relatives of people with T1D and, eventually, the general population. The objective was to assess current practices focusing on relatives of people with T1D. Methods: We surveyed U.S. endocrinologists within the T1DX-QI, a national collaborative focused on improving clinical outcomes for individuals with T1D. Over 60 medical centers who care for people with T1D were surveyed regarding current T1D screening and monitoring practices of which 38 pediatric and 18 adult centers responded (84% academic centers, 16% safety net hospitals), representing 91,694 individuals with T1D. Results: Eighty-four percent of pediatric centers screen for T1D, compared to only 39% of adult centers. Additionally, 66% of pediatric centers have monitoring programs for islet autoantibody-positive individuals compared to only 39% of adult centers, likely an underestimate due to selection bias. A major barrier to clinical implementation is limited or lack of insurance coverage for autoantibody testing in individuals not under the ordering practitioner’s care (i.e., relatives of people with T1D). As a result, 42% of pediatric and 72% of adult centers cannot order commercial autoantibody testing within their state/health system. Pediatric practices report having greater access to islet autoantibody screening programs under research protocols than do adult practices (71% vs 39%). Conclusion: Many pediatric and even more adult diabetes centers are not able to screen and monitor at-risk individuals. These insights highlight existing gaps and the need for targeted strategies to enhance screening accessibility and monitoring across healthcare systems. L.M. Jacobsen: Advisory Panel; Sanofi. D. Vora: None. E.L. Ospelt: None. N.R. Fogel: None. F. Vendrame: None. R.S. Weinstock: Research Support; Amgen Inc, Eli Lilly and Company, Tandem Diabetes Care, Inc, Diasome Pharmaceuticals, Insulet Corporation, MannKind Corporation, Dexcom, Inc. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. A. Guarneri: None. S. Thapa: None. C. Demeterco-Berggren: None.

Background: Disparities in glycemic outcomes and technology use in children with type 1 diabetes (T1D) from under-resourced backgrounds are well-documented. The feasibility of initiating automated insulin delivery (AID) soon after diagnosis of T1D is unknown in this population. This pilot study assessed the feasibility and acceptability of providing access to the Tandem Control-IQ Hybrid Closed-Loop (HCL) system to children with public insurance soon after diagnosis of T1D. Methods: Publicly insured child ren aged 6-17 years within 3 months of T1D diagnosis were eligible for the study. Participants were randomized 2:1 to HCL or control for 6 months. Continuous glucose monitoring data for both groups were collected at baseline, 3 months, and 6 months after enrollment. Caregivers and adolescents completed a closing survey on safety and user experience. Results: Seventeen participants were enrolled, 12 in the intervention group and 5 in the control group. The mean age was 11.5 ±2.5 years, 47% were female, 88% were from underrepresented racial or ethnic groups, 94% of caregivers did not have a college level degree, and 41% of families reported some degree of food insecurity. All families had access to smartphones, but 42% did not have access to a home computer. Of those who completed the study, a larger proportion of the intervention group compared to the control group achieved ADA benchmark of greater than 70% time in range (62% vs 0%, respectively, at 3 months, p=0.038; 37% vs 0% at 6 months, p=0.16). All caregivers in the intervention group reported satisfaction with HCL system and wished to continue using HCL technology. Conclusion: Early initiation of AID is feasible and acceptable in youth with recently diagnosed T1D from historically marginalized racial and ethnic groups and with social risk factors associated with lower technology adoption and less optimal glycemic outcomes. Clinicians should provide education and support for AID to these families early in diagnosis to promote equity in diabetes care. Disclosure K.Yen: None. S.Belapurkar: Other Relationship; T1D Exchange, Research Support; Dexcom, Inc., Tandem Diabetes Care, Inc., Medtronic. J.G.Hickey: None. L.Yglecias: None. K.S.Bal: None. L.Carelli: None. C.M.Loucel: None. M.Lodish: None. J.C.Wong: Research Support; Dexcom, Inc., Tandem Diabetes Care, Inc.

Introduction and Objective: Continuous glucose monitoring (CGM) has revolutionized diabetes care in the outpatient setting, though data on CGM accuracy in the pediatric inpatient setting remains lacking. We aim to see whether CGM values in this population, compared to standard hospital point of care blood glucose (POC BG) checks, fall within an acceptable range according to established CGM accuracy analyses. Methods: We conducted a retrospective chart review of pediatric patients aged 1-18 years using CGM devices who were admitted to a children’s hospital system from June 2022 to June 2024. CGM readings were compared with POC BG values within a 5 minute window. We excluded CGM values ≥400 mg/dL or ≤40 mg/dL. We used Surveillance Error Grid (SEG), MARD, and percentage of CGM values within 15%/20%/30% of POC value to determine CGM accuracy. Results: We collected 802 unique POC BG/CGM paired measurements (89 patients). CGM values were within 5% of POC BG values for 20% of pairs, and within 20% of POC BG values for 67% of pairs. In the SEG, 67%, 30%, 1.7%, 0.9% and 0.5% fell in zones A through E respectively. MARD for all device data was 17%. Conclusion: Investigating factors that impact inpatient CGM accuracy by future prospective studies is essential to integrate CGMs into standard inpatient protocols, enhancing real-time decision-making and reducing healthcare costs while prioritizing patient safety and comfort. E. Allen: None. L. Ekhlaspour: Other Relationship; Medtronic. Advisory Panel; Abbott, Medtronic. Consultant; Jaeb Center for Health Research. Research Support; MannKind Corporation. Speaker's Bureau; Insulet Corporation. Advisory Panel; Sequel Med Tech. Other Relationship; Tandem Diabetes Care, Inc. Research Support; Abbott. Other Relationship; Sanofi. E. Cengiz: Advisory Panel; Novo Nordisk, Arecor Therapeutics, Eli Lilly and Company, Tandem Diabetes Care, Inc, Portal Insulin, MannKind Corporation. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. Z.D. Perez: None. N.A. Sears: None.

Purpose: The purpose of this study was to determine whether clinician comfort differs in the provision of gender-affirming medical care to transgender and gender diverse (TGD) youth with binary versus nonbinary gender identities. Methods: A cross-sectional survey was distributed to three international health professional electronic mailing lists. Comfort providing gonadotropin-releasing hormone agonist (GnRHa) and gender-affirming hormone therapy (GAHT) to nonbinary and binary TGD youth was assessed using 5-point Likert scales and analyzed with Wilcoxon signed-rank tests. Logistic regression modeling comfort providing GnRHa and GAHT to nonbinary compared to binary TGD youth was performed to identify relevant predictors. Results: Fifty-five respondents completed the survey. Respondents reported more comfort providing both GnRHa therapy and GAHT to binary compared to nonbinary TGD youth. In univariate analyses, being in a pediatric endocrinology specialty and work within a multidisciplinary clinic setting were associated with less comfort providing GAHT to nonbinary compared to binary TGD youth. Non-straight/non-heterosexual sexual orientation, being in a general pediatrics specialty, and higher estimated percentage of nonbinary TGD youth cared for in clinical practice were associated with more comfort. Only nonstraight/nonheterosexual sexual orientation maintained significance after adjusting for potential confounders in multivariate analyses. Conclusions: Clinicians are less comfortable providing gender-affirming medical care to nonbinary versus binary TGD youth. Efforts to decrease barriers and to inform development of clinical practice guidelines inclusive of nonbinary TGD youth are needed.

Introduction and Objective: Residing in disadvantaged neighborhoods is linked to negative health outcomes. We aimed to assess if neighborhood disadvantage, measured by the area deprivation index (ADI), predicts glycemic outcomes and development of complications in youth-onset type 2 diabetes (T2D). Methods: We extracted data from 2014-2024 from the University of California (UC) Health Data Warehouse which includes electronic health records from six UCs. T2D diagnosis was identified using a validated algorithm (Teltsch et al, 2019) based on medications, device use, ICD and SNOMED codes. Zip codes informed ADI scores which were analyzed in quintiles. Mixed effects logistic regression, adjusting for age, A1c at diagnosis, race/ethnicity, and sex, was used to assess the relationship between ADI and A1c levels from diagnosis to year 5. We also examined the association of ADI with the development of diabetes-related neuropathy, nephropathy, and retinopathy. Results: The sample included 2322 participants diagnosed before age 21 (mean age 15.6 y; 55% female; 75% non-white), with 67% in the three most disadvantaged ADI quintiles. Mean A1c declined in the first year across all quintiles but increased over years 1-5. Only the least disadvantaged quintile maintained a mean A1c <7% at year 5. The odds of achieving an A1c of <7% for the most disadvantaged quintile were 50% lower (P<0.001), while odds of an A1c >8.5% were 120% higher (P<0.001) compared to the least disadvantaged quintile. At diagnosis, 91 participants had microvascular complications, 76% of which were in the three highest quintiles (P<0.05). Over five years, 136 additional participants developed complications, though incidence did not differ significantly by quintile. Conclusion: ADI is linked to lower odds of achieving glycemic targets and higher baseline complication prevalence, highlighting neighborhood deprivation as a key predictor of glycemic outcomes in youth-onset T2D. M. Yuasa: None. Z.D. Perez: None. J. Davidson: None. J.C. Wong: Research Support; Abbott, Dexcom, Inc., Tandem Diabetes Care, Inc. S. Srinivasan: Research Support; Abbott.