Introduction and Objective: The Pilot 4T Study and 4T Study 1 showed that early intensive type 1 diabetes (T1D) management, including early CGM initiation and weekly remote patient monitoring (RPM) improves glycemic outcomes in youth with T1D. However, sustained weekly RPM is resource intensive. Methods: 4T Study 2 evaluated decreased RPM cadence (Stepped Down cohort, SD-RPM) in youth with new onset T1D. Participants initiated CGM within 30 days of diagnosis and received RPM weekly for 3 months then monthly reviews. Participants were encouraged to take an Automated Insulin Delivery (AID) class within 3 months of diagnosis. The primary outcome was the adjusted 4-12 month HbA1c change between SD-RPM and prior 4T cohorts with weekly RPM for 12 months (Weekly-RPM). Results: SD-RPM (n=183) had similar demographics to Weekly-RPM (n=222) and similar HbA1c trajectories (Figure 1). The adjusted difference in 4-12 month HbA1c change was 0.036% (95% CI −0.022 to 0.095), meeting the pre-specified non-inferiority margin (p=0.017). Early AID education increased AID adoption (66.1% vs 44.1%) and shortened time to AID initiation. Sensitivity analysis did not find a difference in HbA1c based on AID use. Conclusion: Early intensive education combined with a stepped-down RPM cadence is non-inferior to weekly RPM for glycemic outcomes in youth with newly diagnosed T1D. This model offers a pragmatic, scalable pathway for implementing RPM within constrained diabetes care workforces. Disclosure P. Prahalad: Consultant; Current; Sanofi. Advisory Panel; Ended; Insulet Corporation. V. Ding: None. V. Ritter: None. F.K. Bishop: None. D. Zaharieva: Speaker's Bureau; Ended; Dexcom, Inc., Medtronic. Speaker's Bureau; Current; Insulet Corporation. Research Support; Current; Leona M. and Harry B. Helmsley Charitable Trust. A. Addala: None. M. Lee: None. R. Johari: None. D. Scheinker: None. M. Desai: None. D. Maahs: Advisory Panel; Current; Abbott Diabetes, Sanofi, Medtronic, biospex, enable biosciences, kriya. Funding This work was supported in part by the NIH via the Stanford Diabetes Research Center (1P30DK11607401) and grant no. R18DK122422 to D.M.M. Funding support was also received from the Helmsley Charitable Trust (grant no. G-2002-04251-2 to D.P.Z. and R.J.), the National Science Foundation (NSF) (grant no. 2205084 to R.J., D.S, D.M.M, P.P.), Stanford Human-Centered Artificial Intelligence (HAI) to D.M.M., D.S., P.P. and R.J. and Stanford Maternal & Child Health Research Institute (MCHRI) grants to P.P., D.M.M., D.S. and R.J. Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UM1TR004921. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The Stanford REDCap Platform (UL1 T001085) provided additional support. A.A. received support from grant no. K23 DK131342. This manuscript was partially supported by the Biostatistics Shared Resource of the National Cancer Institute-sponsored Stanford Cancer Institute (P30CA124435). Funding for the iOS devices and some CGM supplies was provided by a grant through the Lucile Packard Children’s Hospital Auxiliaries Endowment to P.P.
Prahalad et al. (Fri,) studied this question.