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Predictors of Time-in-Range (70–180 mg/dL) Achieved Using a Closed-Loop Control System
Author(s) -
Melissa J. Schoelwer,
Lauren G. Kanapka,
R. Paul Wadwa,
Marc D. Breton,
Katrina J. Ruedy,
Laya Ekhlaspour,
Gregory P. Forlenza,
Erin Cobry,
Laurel H. Messer,
Eda Cengiz,
Emily Jost,
Lori Carria,
Emma Emory,
Liana Hsu,
Stuart A. Weinzimer,
Bruce A. Buckingham,
Rayhan A. Lal,
Mary C. Oliveri,
Craig C. Kollman,
Betsy B. Dokken,
Daniel R. Cherñavvsky,
Roy W. Beck,
Mark D. DeBoer,
Linda GonderFrederick,
J. Robic,
Mary Voelmle,
Katie Conschafter,
Kimberly Morris,
Charlotte L. Barnett,
Kelly Carr,
Jacob Hellmann,
Matthew Kime,
G. Todd Alonso,
Robert Slover,
Cari Berget,
Lindsey Towers,
Samantha Lange,
Bruce Buckingham,
David M. Maahs,
Lisa Norlander,
Korey K. Hood,
Marissa Town,
Christine Weir,
Kerren Smith,
Deanna Shinksy,
J. Roberto Viana,
Kate Weyman,
Melinda Zgorski,
Sarah Borgman,
Jessica Rusnak,
Craig Kollman,
Carlos Murphy,
Guillermo Arreza-Rubin,
Neal Green,
Boris Kovatchev,
Sue A. Brown,
Stacey M. Anderson,
Marc Breton,
Lori M. Laffel,
Jordan Pinsker,
Carol Levy,
Yogish C. Kudva,
Francis J. Doyle,
Eric Renard,
Claudio Cobelli,
Yves Reznik,
John Lum,
Robert Janicek,
Deanna Gabrielson
Publication year - 2021
Publication title -
diabetes technology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.142
H-Index - 88
eISSN - 1557-8593
pISSN - 1520-9156
DOI - 10.1089/dia.2020.0646
Subject(s) - medicine , quartile , glycemic , diabetes mellitus , insulin , surgery , confidence interval , endocrinology
Background: Studies of closed-loop control (CLC) in patients with type 1 diabetes (T1D) consistently demonstrate improvements in glycemic control as measured by increased time-in-range (TIR) 70-180 mg/dL. However, clinical predictors of TIR in users of CLC systems are needed. Materials and Methods: We analyzed data from 100 children aged 6-13 years with T1D using the Tandem Control-IQ CLC system during a randomized trial or subsequent extension phase. Continuous glucose monitor data were collected at baseline and during 12-16 weeks of CLC use. Participants were stratified into quartiles of TIR on CLC to compare clinical characteristics. Results: TIR for those in the first, second, third, and fourth quartiles was 54%, 65%, 71%, and 78%, respectively. Lower baseline TIR was associated with lower TIR on CLC ( r  = 0.69, P  < 0.001). However, lower baseline TIR was also associated with greater improvement in TIR on CLC ( r  = -0.81, P  < 0.001). During CLC, participants in the highest versus lowest TIR-quartile administered more user-initiated boluses daily (8.5 ± 2.8 vs. 5.8 ± 2.6, P  < 0.001) and received fewer automated boluses (3.5 ± 1.0 vs. 6.0 ± 1.6, P  < 0.001). Participants in the lowest (vs. the highest) TIR-quartile received more insulin per body weight (1.13 ± 0.27 vs. 0.87 ± 0.20 U/kg/d, P  = 0.008). However, in a multivariate model adjusting for baseline TIR, user-initiated boluses and insulin-per-body-weight were no longer significant. Conclusions: Higher baseline TIR is the strongest predictor of TIR on CLC in children with T1D. However, lower baseline TIR is associated with the greatest improvement in TIR. As with open-loop systems, user engagement is important for optimal glycemic control.

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