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Multinational Home Use of Closed-Loop Control Is Safe and Effective

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Anderson, Stacey M., Raghinaru, Dan, Pinsker, Jordan E., Boscari, Federico, Renard, Eric, Buckingham, Bruce A., Nimri, Revital, Doyle, Francis J. +23 more·2016·Diabetes Care
DOI 10.2337/dc15-2468PMC PMC5876016
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Abstract

OBJECTIVE: To evaluate the efficacy of a portable, wearable, wireless artificial pancreas system (the Diabetes Assistant [DiAs] running the Unified Safety System) on glucose control at home in overnight-only and 24/7 closed-loop control (CLC) modes in patients with type 1 diabetes. RESEARCH DESIGN AND METHODS: At six clinical centers in four countries, 30 participants 18–66 years old with type 1 diabetes (43% female, 96% non-Hispanic white, median type 1 diabetes duration 19 years, median A1C 7.3%) completed the study. The protocol included a 2-week baseline sensor-augmented pump (SAP) period followed by 2 weeks of overnight-only CLC and 2 weeks of 24/7 CLC at home. Glucose control during CLC was compared with the baseline SAP. RESULTS: Glycemic control parameters for overnight-only CLC were improved during the nighttime period compared with baseline for hypoglycemia (time <70 mg/dL, primary end point median 1.1% vs. 3.0%; P < 0.001), time in target (70–180 mg/dL: 75% vs. 61%; P < 0.001), and glucose variability (coefficient of variation: 30% vs. 36%; P < 0.001). Similar improvements for day/night combined were observed with 24/7 CLC compared with baseline: 1.7% vs. 4.1%, P < 0.001; 73% vs. 65%, P < 0.001; and 34% vs. 38%, P < 0.001, respectively. CONCLUSIONS: CLC running on a smartphone (DiAs) in the home environment was safe and effective. Overnight-only CLC reduced hypoglycemia and increased time in range overnight and increased time in range during the day; 24/7 CLC reduced hypoglycemia and increased time in range both overnight and during the day. Compared with overnight-only CLC, 24/7 CLC provided additional hypoglycemia protection during the day.

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  • In July 2016, Diabetes Care published a symposium featuring several outpatient AID studies using DiAs running in two different in silico designed algorithm configurations.

    “In July 2016, Diabetes Care published a symposium, 129 which featured several outpatient AID studies using DiAs running in two different in silico designed algorithm configurations.[123][124][125]”

    From Developing the UVA/Padova Type 1 Diabetes Simulator: Modeling, Validation, Refinements, and Utility (2023) · cites this paper as [123]

    The Conclusions (page unavailable) describe outpatient and home DiAs studies and name two closed-loop algorithms; this paper reports home use of one, DiAs-USS Virginia. Our copy does not establish that the algorithms were designed in silico. The symposium reference has a separate citation in the citing sentence, so this verdict does not assess it. (LLM, conf=0.83)

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Authors
Anderson, S. M., Raghinaru, D., Pinsker, J. E., Boscari, F., Renard, E., Buckingham, B. A., Nimri, R., Doyle, F. J., Brown, S. A., Keith-Hynes, P., Breton, M. D., Chernavvsky, D., Bevier, W. C., Bradley, P. K., Bruttomesso, D., Del Favero, S., Calore, R., Cobelli, C., Avogaro, A., Farret, A., Place, J., Ly, T. T., Shanmugham, S., Phillip, M., Dassau, E., Dasanayake, I. S., Kollman, C., Lum, J. W., Beck, R. W., Kovatchev, B., & for the Control to Range Study Group
Affiliations
  • University of Virginia (US)
  • Jaeb Center for Health Research (US)
  • Sansum Diabetes Research Institute (US)
  • University of Padua (IT)
  • Department of Endocrinology, Diabetes, and Nutrition and INSERM 1411 Clinical Investigation Center, Montpellier University Hospital, and UMR CNRS 5203/INSERM U1191, Institute of Functional Genomics, University of Montpellier, Montpellier, France
  • Stanford Medicine (US)
  • Tel Aviv University (IL)
  • Harvard University (US)
  • University of Virginia, Charlottesville, VA
  • University of Padova, Padova, Italy
  • Centre National de la Recherche Scientifique (FR)
  • University of California, Santa Barbara (US)
Corresponding author
Beck, Roy W.
ORCID
Venue
Diabetes Care
Publisher
American Diabetes Association
Published
2016-03-16
Volume
39
Issue
7
Pages
1143-1150
ISSN
  • 0149-5992 (ISSN-L)
  • 1935-5548
DOI
10.2337/dc15-2468
PMC
PMC5876016
OpenAlex
W2335897113
Cited by
120
References
26
Citations by year
2026: 5 · 2025: 9 · 2024: 4 · 2023: 8 · 2022: 6 · 2021: 7 · 2020: 11 · 2019: 22 · 2018: 18 · 2017: 22 · 2016: 8
FWCI
23.45
Type
journal article
Language
en
Open access
Licence
www.diabetesjournals.org/site/license (vor, 291 d)
Locations
  • Diabetes Care (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Padua Research Archive (University of Padova) (submittedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
  • HAL (submittedVersion)
Funders
JDRF (22-2011-649, 17-2013-509)
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
Keywords
type 1 diabetes, feedback control, artificial pancreas, sensor-augmented pump, hypoglycemia, glycemic control, time in range, glycemic variability
MeSH terms
Smartphone, Adolescent, Adult, Aged, Blood Glucose, Diabetes Mellitus, Type 1, Female, Humans, Hypoglycemia, Hypoglycemic Agents, Insulin, Insulin Infusion Systems, Male, Middle Aged, Blood Glucose Self-Monitoring, Pancreas, Artificial, Internationality, Young Adult, Mobile Applications

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