Stacey M Anderson1, Eyal Dassau2,3,4, Dan Raghinaru5, John Lum5, Sue A Brown1, Jordan E Pinsker3, Mei Mei Church3, Carol Levy6, David Lam6, Yogish C Kudva7, Bruce Buckingham8, Gregory P Forlenza9, R Paul Wadwa9, Lori Laffel4, Francis J Doyle2, J Hans DeVries10, Eric Renard11,12, Claudio Cobelli13, Federico Boscari14, Simone Del Favero13, Boris P Kovatchev1. 1. 1 Center for Diabetes Technology, Department of Medicine, University of Virginia. 2. 2 John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts. 3. 3 Sansum Diabetes Research Institute, Santa Barbara, California. 4. 4 Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts. 5. 5 Jaeb Center for Health Research, Tampa, Florida. 6. 6 Division of Endocrinology, Icahn School of Medicine at Mount Sinai, New York City, New York. 7. 7 Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota. 8. 8 Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California. 9. 9 Barbara Davis Center for Diabetes, University of Colorado, Anschutz Medical Campus, Aurora, Colorado. 10. 10 Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands. 11. 11 Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, Montpellier, France. 12. 12 INSERM 1411 Clinical Investigation Center, Institute of Functional Genomics, UMR CNRS 5203/INSERM U1191, University of Montpellier, Montpellier, France. 13. 13 Department of Information Engineering, University of Padova, Padova, Italy. 14. 14 Department of Medicine, University of Padova, Padova, Italy.
Abstract
BACKGROUND: Use of artificial pancreas (AP) requires seamless interaction of device components, such as continuous glucose monitor (CGM), insulin pump, and control algorithm. Mobile AP configurations also include a smartphone as computational hub and gateway to cloud applications (e.g., remote monitoring and data review and analysis). This International Diabetes Closed-Loop study was designed to demonstrate and evaluate the operation of the inControl AP using different CGMs and pump modalities without changes to the user interface, user experience, and underlying controller. METHODS: Forty-three patients with type 1 diabetes (T1D) were enrolled at 10 clinical centers (7 United States, 3 Europe) and 41 were included in the analyses (39% female, >95% non-Hispanic white, median T1D duration 16 years, median HbA1c 7.4%). Two CGMs and two insulin pumps were tested by different study participants/sites using the same system hub (a smartphone) during 2 weeks of in-home use. RESULTS: The major difference between the system components was the stability of their wireless connections with the smartphone. The two sensors achieved similar rates of connectivity as measured by percentage time in closed loop (75% and 75%); however, the two pumps had markedly different closed-loop adherence (66% vs. 87%). When connected, all system configurations achieved similar glycemic outcomes on AP control (73% [mean] time in range: 70-180 mg/dL, and 1.7% [median] time <70 mg/dL). CONCLUSIONS: CGMs and insulin pumps can be interchangeable in the same Mobile AP system, as long as these devices achieve certain levels of reliability and wireless connection stability.
BACKGROUND: Use of artificial pancreas (AP) requires seamless interaction of device components, such as continuous glucose monitor (CGM), insulin pump, and control algorithm. Mobile AP configurations also include a smartphone as computational hub and gateway to cloud applications (e.g., remote monitoring and data review and analysis). This International Diabetes Closed-Loop study was designed to demonstrate and evaluate the operation of the inControl AP using different CGMs and pump modalities without changes to the user interface, user experience, and underlying controller. METHODS: Forty-three patients with type 1 diabetes (T1D) were enrolled at 10 clinical centers (7 United States, 3 Europe) and 41 were included in the analyses (39% female, >95% non-Hispanic white, median T1D duration 16 years, median HbA1c 7.4%). Two CGMs and two insulin pumps were tested by different study participants/sites using the same system hub (a smartphone) during 2 weeks of in-home use. RESULTS: The major difference between the system components was the stability of their wireless connections with the smartphone. The two sensors achieved similar rates of connectivity as measured by percentage time in closed loop (75% and 75%); however, the two pumps had markedly different closed-loop adherence (66% vs. 87%). When connected, all system configurations achieved similar glycemic outcomes on AP control (73% [mean] time in range: 70-180 mg/dL, and 1.7% [median] time <70 mg/dL). CONCLUSIONS:CGMs and insulin pumps can be interchangeable in the same Mobile AP system, as long as these devices achieve certain levels of reliability and wireless connection stability.
Entities:
Keywords:
Continuous glucose monitor use; Insulin pump use; International Diabetes Closed-Loop Study
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