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Abstract ContextYouth with type 1 diabetes (T1D) struggle to meet and sustain hemoglobin A1c (HbA1c) targets. Youth enrolled in the Pilot 4T Study improved HbA1c by 0.5% at 1 year, compared to historical controls. ObjectiveTo assess 3 years of glycemic outcomes in the Pilot 4T Study. MethodsThe Pilot 4T Extension cohort was prospectively followed to determine changes in HbA1c and continuous glucose monitoring (CGM) metrics over 3 years at the Stanford Medicine Children's Health Diabetes Clinic. Youth with T1D in the Pilot 4T Study enrolled in the extension phase started CGM in the first month of diabetes diagnosis, received intensified education and remote patient monitoring (RPM) weekly for the first year of diabetes diagnosis, and monthly RPM in the extension phase. HbA1c and CGM metrics were evaluated over the first 3 years of diagnosis. ResultsIn the Pilot 4T cohort, 78.5% (n = 102) of participants enrolled in the study extension phase and were followed through 3 years. The adjusted difference in HbA1c at 3 years was 1.2% (95% CI 0.7%-1.7%) lower in the Pilot 4T cohort than in the Historical cohort. In the Pilot 4T cohort, 68% and 37% met the <7.5% and <7% HbA1c targets at 3 years, respectively, compared to 37% and 20% in the Historical cohort. ConclusionYouth with T1D in the Pilot 4T extension phase sustained improvements in HbA1c over 3 years. Focusing resources on intensive management during the first year after T1D diagnosis may impact long-term glycemia. 

Background:Youth with type 1 diabetes (T1D) and public insurance have lower diabetes technology use. This pilot study assessed the feasibility of a program to support continuous glucose monitor (CGM) use with remote patient monitoring (RPM) to improve glycemia for youth with established T1D and public insurance. Methods:From August 2020 to June 2023, we provided CGM with RPM support via patient portal messaging for youth with established T1D on public insurance with challenges obtaining consistent CGM supplies. We prospectively collected hemoglobin A_1c(HbA_1c), standard CGM metrics, and diabetes technology use over 12 months. Results:The cohort included 91 youths with median age at enrollment 14.7 years, duration of diabetes 4.4 years, 33% non-English speakers, and 44% Hispanic. Continuous glucose monitor data were consistently available (≥70%) in 23% of the participants. For the 64% of participants with paired HbA_1cvalues at enrollment and study end, the median HbA_1cdecreased from 9.8% to 9.0% ( P < .001). Insulin pump users increased from 31 to 48 and automated insulin delivery users increased from 11 to 38. Conclusions:We established a program to support CGM use in youth with T1D and barriers to consistent CGM supplies, offering lessons for other clinics to address disparities with team-based, algorithm-enabled, remote T1D care. This real-world pilot and feasibility study noted challenges with low levels of protocol adherence and obtaining complete data in this cohort. Future iterations of the program should explore RPM communication methods that better align with this population’s preferences to increase participant engagement. 

Abstract AimsPsychosocial impacts of early continuous glucose monitoring (CGM) initiation in youth soon after type 1 diabetes diagnosis are underexplored. We report parent/guardian and youth patient‐reported outcomes (PROs) that measure psychosocial states for families in 4T Study 1. Materials and MethodsOf the 133 families in the 4T Study 1, 132 parent/guardian and 66 youth (≥11 years) were eligible to complete PROs. PROs evaluated included diabetes distress, global health, diabetes technology attitudes and CGM benefits/burden scales. Temporal trends of PROs were assessed via generalised linear mixed effects regression. Sociodemographic and clinical characteristics associated with PROs were evaluated. Psychosocial associations were evaluated by regressing parental distress on youth distress. ResultsPRO completion rates were 85.6% and varied between parent/guardian and youth. Throughout the study, parent/guardian and youth distress remained low and youth had increased technology acceptance (p = 0.046). Each additional month of CGM use was associated with a 14% decrease in the odds of experiencing diabetes distress (aOR = 0.86, 95% CI [0.76, 0.99],p = 0.029). Additionally, higher time‐in‐range was associated with decreased diabetes distress (p = 0.048). Age, diabetic ketoacidosis at diagnosis, gender, ethnicity, insurance status and language spoken were not associated with PROs. ConclusionsInitiation of CGM shortly after type 1 diabetes diagnosis does not have unintended negative psychological consequences. Longer duration of CGM use was associated with decreased youth distress and technology acceptance increased throughout the study. 

Continuous glucose monitoring (CGM) use soon after T1D diagnosis in the 4T Study was associated with improved glycemic outcomes. We evaluated participant factors associated with elevated versus in target A1c for youth in the 4T Study. All youth from the 4T Study 1 (n=133) were evaluated. In this analysis, the 110 youth who had a final A1c between 6-13 months were included in a complete case analysis. These 110 youth were comparable to the 133 4T Study 1 youth by race/ethnicity, insurance, preferred language, and age. Group differences by non-ordered A1c categories were evaluated for categorical (race/ethnicity, insurance, gender, and language) and continuous (age and time from CGM start) variables via chi-square and ANOVA, respectively. A majority of youth in the 4T Study 1 met glycemic targets (65% with A1c ≤7% between 6-13 months post-diagnosis). Age, race/ethnicity, and insurance status were significantly associated with A1c categories (p=0.02 for all; Table). Higher A1c categories were more likely to include Hispanic youth and youth with public insurance. In the 4T Study 1, Hispanic youth and youth with public insurance had higher A1c categories despite similar CGM access and training. These findings suggest the need to address additional drivers of disparities in addition to CGM access. Approaches focused on health equity are required to improve glycemic outcomes in all youth newly diagnosed with T1D. Disclosure J. Kim: None. D. P. Zaharieva: Advisory Panel; Dexcom, Inc., Research Support; Hemsley Charitable Trust, International Society for Pediatric and Adolescent Diabetes, Insulet Corporation, Speaker's Bureau; American Diabetes Association, Ascensia Diabetes Care, Medtronic. F. K. Bishop: None. D. Scheinker: None. R. Johari: None. M. Desai: None. K. K. Hood: Consultant; Cecelia Health. D. M. Maahs: Advisory Panel; Medtronic, LifeScan Diabetes Institute, MannKind Corporation, Consultant; Abbott, Research Support; Dexcom, Inc. A. Addala: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (K23DK13134201, R18DK122422) 

Methods to optimize care after T1D diagnosis are needed. We hypothesized lowering A1c targets to <7% would further lower A1c in the 4T Study in which CGM with asynchronous remote patient monitoring (RPM) is initiated after T1D diagnosis. All youth with newly diagnosed T1D (June 2020-March 2022) were offered CGM and RPM after diagnosis (Study 1, n=133). We compared A1c at 1-year in Study 1 with the 4T Pilot (2018-20) and Historical cohorts (2014-16). We visualized population-based A1c trajectories using locally estimated scatter plot smoothing (Fig) and % meeting A1c targets. Mean A1c at diagnosis was similar in Pilot (12.2%±2.1%) and Study 1 (12.2±2.4%) and higher than the Historical cohort (10.7±2.5%). In Study 1, the median age of diagnosis was 10.8 years, 55% male, 40% non-Hispanic White, and 38% with public insurance. CGM initiation occurred within 30 days of diagnosis in 98.5%. At 3, 6, 9, and 12 months post-diagnosis, the Study 1 cohort had LOESS-based mean A1c differences of 0.16%, 0.24%, 0.31%, and 0.58% lower than the Pilot and 0.04%, 0.60%, 0.83%, and 1.06% lower than the Historical cohort. A1c target <7% was met by 61% of youth in Study 1, 51% in the Pilot and 28% in the Historical cohort. Time <70mg/dl was ≤2.3%. The 4T program which emphasizes early CGM initiation, RPM, tighter glucose targets, and consistent team messaging was associated with lower A1c. These data support implementation of the 4T program in youth with T1D. Disclosure P.Prahalad: None. D.M.Maahs: Advisory Panel; Medtronic, LifeScan Diabetes Institute, MannKind Corporation, Consultant; Abbott, Research Support; Dexcom, Inc. 4t study group: n/a. V.Ding: None. D.P.Zaharieva: Advisory Panel; Dexcom, Inc., Research Support; Hemsley Charitable Trust, International Society for Pediatric and Adolescent Diabetes, Insulet Corporation, Speaker's Bureau; American Diabetes Association, Ascensia Diabetes Care, Medtronic. A.Addala: None. F.K.Bishop: None. D.Scheinker: None. R.Johari: None. M.Desai: None. K.K.Hood: Consultant; Cecelia Health. Funding National Institutes of Health (P30DK116074), (R18DK122422 to D.M.M.); Dexcom, Inc.; Lucile Packard Children’s Hospital Auxiliaries Endowment; Stanford Maternal and Child Health Research Institute