BACKGROUND: We present a clinical trial establishing the feasibility of a control-to-range (CTR) closed-loop system informed by heart rate (HR) and assess the effect of HR information added to CTR on the risk for hypoglycemia during and after exercise. SUBJECTS AND METHODS: Twelve subjects with type 1 diabetes (five men, seven women; weight, 68.9± 3.1 kg; age, 38 ± 3.3 years; glycated hemoglobin, 6.9 ± 0.2%) participated in a randomized crossover clinical trial comparing CTR versus CTR+HR in two 26-h admissions, each including 30 min of mild exercise. The CTR algorithm was implemented in the DiAs portable artificial pancreas platform based on an Android(®) (Google, Mountainview, CA) smartphone. We assessed blood glucose (BG) decline during exercise, the Low BG Index (LBGI) (a measure of hypoglycemic risk), number of hypoglycemic episodes (BG <70 mg/dL) and overall glucose control (percentage time within the target range 70 mg/dL ≤ BG ≤ 180 mg/dL). RESULTS: Using HR to inform the CTR algorithm reduced significantly the BG decline during exercise (P=0.022), indicated marginally lower LBGI (P=0.3) and fewer hypoglycemic events during exercise (none vs. two events; P=0.16), and resulted in overall higher percentage time within the target range (81% vs. 75%; P=0.2). LBGI and average BG remained unchanged overall, during recovery, and overnight. CONCLUSIONS:HR-informed closed-loop control can be implemented in a portable artificial pancreas. Although closed loop has been shown to reduce hypoglycemia, adding HR signal may further limit the risk for hypoglycemia during and immediately after exercise. The most prominent effect of adding HR information is reduced BG decline during exercise, without deterioration of overall glycemic control.
RCT Entities:
BACKGROUND: We present a clinical trial establishing the feasibility of a control-to-range (CTR) closed-loop system informed by heart rate (HR) and assess the effect of HR information added to CTR on the risk for hypoglycemia during and after exercise. SUBJECTS AND METHODS: Twelve subjects with type 1 diabetes (five men, seven women; weight, 68.9 ± 3.1 kg; age, 38 ± 3.3 years; glycated hemoglobin, 6.9 ± 0.2%) participated in a randomized crossover clinical trial comparing CTR versus CTR+HR in two 26-h admissions, each including 30 min of mild exercise. The CTR algorithm was implemented in the DiAs portable artificial pancreas platform based on an Android(®) (Google, Mountainview, CA) smartphone. We assessed blood glucose (BG) decline during exercise, the Low BG Index (LBGI) (a measure of hypoglycemic risk), number of hypoglycemic episodes (BG <70 mg/dL) and overall glucose control (percentage time within the target range 70 mg/dL ≤ BG ≤ 180 mg/dL). RESULTS: Using HR to inform the CTR algorithm reduced significantly the BG decline during exercise (P=0.022), indicated marginally lower LBGI (P=0.3) and fewer hypoglycemic events during exercise (none vs. two events; P=0.16), and resulted in overall higher percentage time within the target range (81% vs. 75%; P=0.2). LBGI and average BG remained unchanged overall, during recovery, and overnight. CONCLUSIONS: HR-informed closed-loop control can be implemented in a portable artificial pancreas. Although closed loop has been shown to reduce hypoglycemia, adding HR signal may further limit the risk for hypoglycemia during and immediately after exercise. The most prominent effect of adding HR information is reduced BG decline during exercise, without deterioration of overall glycemic control.
Authors: Sarah K McMahon; Luis D Ferreira; Nirubasini Ratnam; Raymond J Davey; Leanne M Youngs; Elizabeth A Davis; Paul A Fournier; Timothy W Jones Journal: J Clin Endocrinol Metab Date: 2006-11-21 Impact factor: 5.958
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Authors: Claudio Cobelli; Eric Renard; Boris P Kovatchev; Patrick Keith-Hynes; Najib Ben Brahim; Jérôme Place; Simone Del Favero; Marc Breton; Anne Farret; Daniela Bruttomesso; Eyal Dassau; Howard Zisser; Francis J Doyle; Stephen D Patek; Angelo Avogaro Journal: Diabetes Care Date: 2012-09 Impact factor: 19.112
Authors: Jennifer L Sherr; Eda Cengiz; Cesar C Palerm; Bud Clark; Natalie Kurtz; Anirban Roy; Lori Carria; Martin Cantwell; William V Tamborlane; Stuart A Weinzimer Journal: Diabetes Care Date: 2013-06-11 Impact factor: 19.112
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Authors: Stephen T Bartlett; James F Markmann; Paul Johnson; Olle Korsgren; Bernhard J Hering; David Scharp; Thomas W H Kay; Jonathan Bromberg; Jon S Odorico; Gordon C Weir; Nancy Bridges; Raja Kandaswamy; Peter Stock; Peter Friend; Mitsukazu Gotoh; David K C Cooper; Chung-Gyu Park; Phillip OʼConnell; Cherie Stabler; Shinichi Matsumoto; Barbara Ludwig; Pratik Choudhary; Boris Kovatchev; Michael R Rickels; Megan Sykes; Kathryn Wood; Kristy Kraemer; Albert Hwa; Edward Stanley; Camillo Ricordi; Mark Zimmerman; Julia Greenstein; Eduard Montanya; Timo Otonkoski Journal: Transplantation Date: 2016-02 Impact factor: 4.939
Authors: Laya Ekhlaspour; Gregory P Forlenza; Daniel Chernavvsky; David M Maahs; R Paul Wadwa; Mark D Deboer; Laurel H Messer; Marissa Town; Jennifer Pinnata; Geoff Kruse; Boris P Kovatchev; Bruce A Buckingham; Marc D Breton Journal: Pediatr Diabetes Date: 2019-05-23 Impact factor: 4.866