Literature DB >> 22920817

Feasibility of overnight closed-loop control based on hourly blood glucose measurements.

Caroline Patte1, Stefan Pleus, Paul Galley, Stefan Weinert, Cornelia Haug, Guido Freckmann.   

Abstract

INTRODUCTION: Safe and effective closed-loop control (artificial pancreas) is the ultimate goal of insulin delivery. In this study, we examined the performance of a closed-loop control algorithm used for the overnight time period to safely achieve a narrow target range of blood glucose (BG) concentrations prior to breakfast. The primary goal was to compare the quality of algorithm control during repeated overnight experiments.
MATERIALS AND METHODS: Twenty-three subjects with type 1 diabetes performed 2 overnight experiments on each of three visits at the study site, resulting in 138 overnight experiments. On the first evening, the subject's insulin therapy was applied; on the second, the insulin was delivered by an algorithm based on subcutaneous continuous glucose measurements (including meal control) until midnight. Overnight closed-loop control was applied between midnight and 6 a.m. based on hourly venous BG measurements during the first and second nights.
RESULTS: The number of BG values within the target range (90-150 mg/dl) increased from 52.9% (219 out of 414 measurements) during the first nights to 72.2% (299 out of 414 measurements) during the second nights (p < .001, χ²-test). The occurrence of hypoglycemia interventions was reduced from 14 oral glucose interventions, the latest occurring at 2:36 a.m. during the first nights, to 1 intervention occurring at 1:02 a.m. during the second nights (p < .001, χ²-test).
CONCLUSIONS: Overnight controller performance improved when optimized initial control was given; this was suggested by the better metabolic control during the second night. Adequate controller run-in time seems to be important for achieving good overnight control. In addition, the findings demonstrate that hourly BG data are sufficient for the closed-loop control algorithm tested to achieve appropriate glycemic control.
© 2012 Diabetes Technology Society.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 22920817      PMCID: PMC3440162          DOI: 10.1177/193229681200600422

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  33 in total

1.  Improved glycemic control in poorly controlled patients with type 1 diabetes using real-time continuous glucose monitoring.

Authors:  Dorothee Deiss; Jan Bolinder; Jean-Pierre Riveline; Tadej Battelino; Emanuele Bosi; Nadia Tubiana-Rufi; David Kerr; Moshe Phillip
Journal:  Diabetes Care       Date:  2006-12       Impact factor: 19.112

2.  Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes.

Authors:  David M Nathan; Patricia A Cleary; Jye-Yu C Backlund; Saul M Genuth; John M Lachin; Trevor J Orchard; Philip Raskin; Bernard Zinman
Journal:  N Engl J Med       Date:  2005-12-22       Impact factor: 91.245

3.  Probabilistic evolving meal detection and estimation of meal total glucose appearance.

Authors:  Fraser Cameron; Günter Niemeyer; Bruce A Buckingham
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

Review 4.  Recent advances in continuous glucose monitoring.

Authors:  G Freckmann; B Kalatz; B Pfeiffer; U Hoss; C Haug
Journal:  Exp Clin Endocrinol Diabetes       Date:  2001       Impact factor: 2.949

5.  Less severe hypoglycaemia, better metabolic control, and improved quality of life in Type 1 diabetes mellitus with continuous subcutaneous insulin infusion (CSII) therapy; an observational study of 100 consecutive patients followed for a mean of 2 years.

Authors:  R Linkeschova; M Raoul; U Bott; M Berger; M Spraul
Journal:  Diabet Med       Date:  2002-09       Impact factor: 4.359

6.  Prevention of nocturnal hypoglycemia using predictive alarm algorithms and insulin pump suspension.

Authors:  Bruce Buckingham; H Peter Chase; Eyal Dassau; Erin Cobry; Paula Clinton; Victoria Gage; Kimberly Caswell; John Wilkinson; Fraser Cameron; Hyunjin Lee; B Wayne Bequette; Francis J Doyle
Journal:  Diabetes Care       Date:  2010-03-03       Impact factor: 19.112

7.  Is an automatic pump suspension feature safe for children with type 1 diabetes? An exploratory analysis with a closed-loop system.

Authors:  Eda Cengiz; Karena L Swan; William V Tamborlane; Garry M Steil; Amy T Steffen; Stuart A Weinzimer
Journal:  Diabetes Technol Ther       Date:  2009-04       Impact factor: 6.118

8.  Continuous glucose monitoring and intensive treatment of type 1 diabetes.

Authors:  William V Tamborlane; Roy W Beck; Bruce W Bode; Bruce Buckingham; H Peter Chase; Robert Clemons; Rosanna Fiallo-Scharer; Larry A Fox; Lisa K Gilliam; Irl B Hirsch; Elbert S Huang; Craig Kollman; Aaron J Kowalski; Lori Laffel; Jean M Lawrence; Joyce Lee; Nelly Mauras; Michael O'Grady; Katrina J Ruedy; Michael Tansey; Eva Tsalikian; Stuart Weinzimer; Darrell M Wilson; Howard Wolpert; Tim Wysocki; Dongyuan Xing
Journal:  N Engl J Med       Date:  2008-09-08       Impact factor: 91.245

9.  The relationship of glycemic exposure (HbA1c) to the risk of development and progression of retinopathy in the diabetes control and complications trial.

Authors: 
Journal:  Diabetes       Date:  1995-08       Impact factor: 9.461

10.  Fully automated closed-loop insulin delivery versus semiautomated hybrid control in pediatric patients with type 1 diabetes using an artificial pancreas.

Authors:  Stuart A Weinzimer; Garry M Steil; Karena L Swan; Jim Dziura; Natalie Kurtz; William V Tamborlane
Journal:  Diabetes Care       Date:  2008-02-05       Impact factor: 19.112

View more
  2 in total

1.  Use of microdialysis-based continuous glucose monitoring to drive real-time semi-closed-loop insulin infusion.

Authors:  Guido Freckmann; Nina Jendrike; Stefan Pleus; Harvey Buck; Steven Bousamra; Paul Galley; Ajay Thukral; Robin Wagner; Stefan Weinert; Cornelia Haug
Journal:  J Diabetes Sci Technol       Date:  2014-09-09

2.  Closed-loop artificial pancreas systems: engineering the algorithms.

Authors:  Francis J Doyle; Lauren M Huyett; Joon Bok Lee; Howard C Zisser; Eyal Dassau
Journal:  Diabetes Care       Date:  2014       Impact factor: 19.112

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.