Clinical Management and Pump Parameter Adjustment of the Control-IQ Closed-Loop Control System: Results from a 6-Month, Multicenter, Randomized Clinical Trial

Grenye O'Malley, Laurel H. Messer, Carol J. Levy, Jordan E. Pinsker, Gregory P. Forlenza, Elvira Isganaitis, Yogish C. Kudva, Laya Ekhlaspour, Dan Raghinaru, John Lum, Sue A. Brown

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Background: Data are limited on the need for and benefits of pump setting optimization with automated insulin delivery. We examined clinical management of a closed-loop control (CLC) system and its relationship to glycemic outcomes. Materials and Methods: We analyzed personal parameter adjustments in 168 participants in a 6-month multicenter trial of CLC with Control-IQ versus sensor-augmented pump (SAP) therapy. Preset parameters (BR = basal rates, CF = correction factors, CR = carbohydrate ratios) were optimized at randomization, 2 and 13 weeks, for safety issues, participant concerns, or initiation by participants' usual diabetes care team. Time in range (TIR 70-180 mg/dL) was compared in the week before and after parameter changes. Results: In 607 encounters for parameter changes, there were fewer adjustments for CLC than SAP (3.4 vs. 4.1/participant). Adjustments involved BR (CLC 69%, SAP 80%), CR (CLC 68%, SAP 50%), CF (CLC 44%, SAP 41%), and overnight parameters (CLC 62%, SAP 75%). TIR before and after adjustments was 71.2% and 71.3% for CLC and 61.0% and 62.9% for SAP. The highest baseline HbA1c CLC subgroup had the largest TIR improvement (51.2% vs. 57.7%). When a CR was made more aggressive in the CLC group, postprandial time >180 mg/dL was 43.1% before the change and 36.0% after the change. The median postprandial time <70 mg/dL before making CR less aggressive was 1.8%, and after the change was 0.7%. Conclusions: No difference in TIR was detected with parameter changes overall, but they may have an effect in higher HbA1c subgroups or following user-directed boluses, suggesting that changes may matter more in suboptimal control or during discrete periods of the day.

Original languageEnglish
Pages (from-to)245-252
Number of pages8
JournalDiabetes Technology and Therapeutics
Volume23
Issue number4
DOIs
StatePublished - 1 Apr 2021

Keywords

  • Automated insulin delivery
  • Closed-loop control
  • Continuous glucose monitor
  • Pump parameters
  • Type 1 diabetes

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