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Randomized Controlled Trial
. 2016 Nov 1;10(6):1216-1221.
doi: 10.1177/1932296816645119. Print 2016 Nov.

Efficacy of an Overnight Predictive Low-Glucose Suspend System in Relation to Hypoglycemia Risk Factors in Youth and Adults With Type 1 Diabetes

Peter M Calhoun  1 , Bruce A Buckingham  2 , David M Maahs  3 , Irene Hramiak  4 , Darrell M Wilson  2 , Tandy Aye  2 , Paula Clinton  2 , Peter Chase  3 , Laurel Messer  3 , Craig Kollman  1 , Roy W Beck  1 , John Lum  5 ; In Home Closed Loop Study Group
Affiliations
Randomized Controlled Trial

Efficacy of an Overnight Predictive Low-Glucose Suspend System in Relation to Hypoglycemia Risk Factors in Youth and Adults With Type 1 Diabetes

Peter M Calhoun et al. J Diabetes Sci Technol. .

Erratum in

  • Corrigendum.
    [No authors listed] [No authors listed] J Diabetes Sci Technol. 2017 Mar;11(2):NP1. doi: 10.1177/1932296817692062. Epub 2017 Jan 19. J Diabetes Sci Technol. 2017. PMID: 28264183 Free PMC article. No abstract available.

Abstract

Background: We developed a system to suspend insulin pump delivery overnight when the glucose trend predicts hypoglycemia. This predictive low-glucose suspend (PLGS) system substantially reduces nocturnal hypoglycemia without an increase in morning ketosis. Evaluation of hypoglycemia risk factors that could potentially influence the efficacy of the system remains critical for understanding possible problems with the system and identifying patients that may have the greatest benefit when using the system.

Methods: The at-home randomized trial consisted of 127 study participants with hemoglobin A1c (A1C) of ≤8.5% (mmol/mol) for patients aged 4-14 years and ≤8.0% for patient aged 15-45 years. Factors assessed included age, gender, A1C, diabetes duration, daily percentage basal insulin, total daily dose of insulin (units/kg-day), bedtime BG, bedtime snack, insulin on board, continuous glucose monitor (CGM) rate of change (ROC), day of the week, time system activated, daytime exercise intensity, and daytime CGM-measured hypoglycemia.

Results: The PLGS system was effective in preventing hypoglycemia for each factor subgroup. There was no evidence that the PLGS system was more or less effective in preventing hypoglycemia in any one subgroup compared with the other subgroups based on that factor. In addition, the effect of the system on overnight hyperglycemia did not differ in subgroups.

Conclusions: The PLGS system tested in this study effectively reduced hypoglycemia without a meaningful increase in hyperglycemia across a variety of factors.

Keywords: hypoglycemia; insulin pump; predictive low glucose suspend; sensor; type 1 diabetes.

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Conflict of interest statement

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Continuous glucose monitors and sensors were purchased at a bulk discount price from Medtronic MiniMed, Inc (Northridge, CA). Bayer HealthCare, LLC, Diabetes Care provided blood glucose meters, test strips, control solution, and lancets as product support through an investigator sponsored research grant. Home ketone meters and test strips were provided by Abbott Diabetes Care, Inc. The companies had no involvement in the design, conduct, or analysis of the trial or the manuscript preparation. PMC has no disclosures. BAB reports grants from NIDDK, during the conduct of the study; grants, personal fees, and nonfinancial support from Medtronic MiniMed, Inc, personal fees from Sanofi, personal fees from Tandem, personal fees from Novo-Nordisk, personal fees from Animas, outside the submitted work. In addition, BAB reports a Kalman filter based hypoglycemia prevention algorithm patent is pending. DMM reports grants from American Diabetes Association- Medtronic MiniMed, Inc. IH reports grants from JDRF-Federal Development funding during the conduct of the study, as well as grants, personal fees, and nonfinancial support from Abbott, from AstraZeneca/Bristol Myers Squibb; personal fees and nonfinancial support from Boehringer Ingelheim, grants, personal fees, and nonfinancial support from Eli Lilly, grants, personal fees, and nonfinancial support from Janssen-Ortho/Johnson & Johnson (JNJ), personal fees and nonfinancial support from Medtronic MiniMed, Inc, grants, personal fees, nonfinancial support, and other from Merck, grants, personal fees, and nonfinancial support from Novo Nordisk, grants from Pfizer, grants, personal fees, and nonfinancial support from Sanofi Aventis, outside the submitted work; DMW reports research supplies support from LifeScan, Inc and Medtronic MiniMed, Inc and a Kalman filter based hypoglycemia prevention algorithm patent pending. T. Aye has no disclosures. PC has no disclosures. HPC reports grants from Dexcom during the conduct of the study, as well as a Kalman filter based hypoglycemia prevention algorithm patent is pending. LM has no disclosures. RWB reports grants from NIH and from JDRF during the conduct of the study. CK reports consultant fees from Medtronic MiniMed, Inc. RWB reports grants from NIH and from JDRF during the conduct of the study. JWL has no disclosures.

Comment in

  • Corrigendum.
    [No authors listed] [No authors listed] J Diabetes Sci Technol. 2017 Mar;11(2):NP1. doi: 10.1177/1932296817692062. Epub 2017 Jan 19. J Diabetes Sci Technol. 2017. PMID: 28264183 Free PMC article. No abstract available.

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References

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