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Predictors of Time-in-Range (70–180 mg/dL) Achieved Using a Closed-Loop Control System

2021; Mary Ann Liebert, Inc.; Volume: 23; Issue: 7 Linguagem: Inglês

10.1089/dia.2020.0646

1557-8593

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 Gonder‐Frederick, 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, Rayhan A. Lal, Laya Ekhlaspour, Lisa Norlander, Korey K. Hood, Marissa Town, Christine Weir, Kerren Smith, Liana Hsu, Deanna Shinksy, J. Roberto Viana, Eda Cengiz, Stuart A. Weinzimer, Kate Weyman, Lori Carria, Melinda Zgorski, Katrina J. Ruedy, Roy W. Beck, Sarah Borgman, Jessica Rusnak, Lauren G. Kanapka, 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, R. Paul Wadwa, Bruce Buckingham, Francis J. Doyle, Eric Renard, Claudio Cobelli, Yves Reznik, Guillermo Arreza-Rubin, John Lum, Roy W. Beck, Katrina J. Ruedy, Robert Janicek, Deanna Gabrielson,

Diabetes and associated disorders

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.