Literature DB >> 22023376

Effects of everyday life events on glucose, insulin, and glucagon dynamics in continuous subcutaneous insulin infusion-treated type 1 diabetes: collection of clinical data for glucose modeling.

Signe Schmidt1, Daniel A Finan, Anne Katrine Duun-Henriksen, John Bagterp Jørgensen, Henrik Madsen, Henrik Bengtsson, Jens Juul Holst, Sten Madsbad, Kirsten Nørgaard.   

Abstract

BACKGROUND: In the development of glucose control algorithms, mathematical models of glucose metabolism are useful for conducting simulation studies and making real-time predictions upon which control calculations can be based. To obtain type 1 diabetes (T1D) data for the modeling of glucose metabolism, we designed and conducted a clinical study.
METHODS: Patients with insulin pump-treated T1D were recruited to perform everyday life events on two separate days. During the study, patients wore their insulin pumps and, in addition, a continuous glucose monitor and an activity monitor to estimate energy expenditure. The sequence of everyday life events was predetermined and included carbohydrate intake, insulin boluses, and bouts of exercise; the events were introduced, temporally separated, in different orders and in different quantities. Throughout the study day, 10-min plasma glucose measurements were taken, and samples for plasma insulin and glucagon analyses were obtained every 10 min for the first 30 min after an event and subsequently every 30 min.
RESULTS: We included 12 patients with T1D (75% female, 34.3±9.1 years old [mean±SD], hemoglobin A1c 6.7±0.4%). During the 24 study days we collected information-rich, high-quality data during fast and slow changes in plasma glucose following carbohydrate intake, exercise, and insulin boluses.
CONCLUSIONS: This study has generated T1D data suitable for glucose modeling, which will be used in the development of glucose control strategies. Furthermore, the study has given new physiologic insight into the metabolic effects of carbohydrate intake, insulin boluses, and exercise in continuous subcutaneous insulin infusion-treated patients with T1D.

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Year:  2011        PMID: 22023376     DOI: 10.1089/dia.2011.0101

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  8 in total

1.  Model-based closed-loop glucose control in type 1 diabetes: the DiaCon experience.

Authors:  Signe Schmidt; Dimitri Boiroux; Anne Katrine Duun-Henriksen; Laurits Frøssing; Ole Skyggebjerg; John Bagterp Jørgensen; Niels Kjølstad Poulsen; Henrik Madsen; Sten Madsbad; Kirsten Nørgaard
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

Review 2.  Physical activity and type 1 diabetes: time for a rewire?

Authors:  Sheri R Colberg; Remmert Laan; Eyal Dassau; David Kerr
Journal:  J Diabetes Sci Technol       Date:  2015-01-06

3.  Evaluation of pharmacokinetic model designs for subcutaneous infusion of insulin aspart.

Authors:  Erin J Mansell; Signe Schmidt; Paul D Docherty; Kirsten Nørgaard; John B Jørgensen; Henrik Madsen
Journal:  J Pharmacokinet Pharmacodyn       Date:  2017-08-22       Impact factor: 2.745

4.  Preserved glucose response to low-dose glucagon after exercise in insulin-pump-treated individuals with type 1 diabetes: a randomised crossover study.

Authors:  Isabelle I K Steineck; Ajenthen Ranjan; Signe Schmidt; Trine R Clausen; Jens J Holst; Kirsten Nørgaard
Journal:  Diabetologia       Date:  2019-01-14       Impact factor: 10.122

5.  Model identification using stochastic differential equation grey-box models in diabetes.

Authors:  Anne Katrine Duun-Henriksen; Signe Schmidt; Rikke Meldgaard Røge; Jonas Bech Møller; Kirsten Nørgaard; John Bagterp Jørgensen; Henrik Madsen
Journal:  J Diabetes Sci Technol       Date:  2013-03-01

6.  Challenges and Recent Progress in the Development of a Closed-loop Artificial Pancreas.

Authors:  B Wayne Bequette
Journal:  Annu Rev Control       Date:  2012-12       Impact factor: 6.091

7.  Accuracy of continuous glucose monitoring during exercise in type 1 diabetes pregnancy.

Authors:  Kavita Kumareswaran; Daniela Elleri; Janet M Allen; Karen Caldwell; Marianna Nodale; Malgorzata E Wilinska; Stephanie A Amiel; Roman Hovorka; Helen R Murphy
Journal:  Diabetes Technol Ther       Date:  2013-02-27       Impact factor: 6.118

8.  Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor.

Authors:  Lyvia Biagi; Charrise M Ramkissoon; Andrea Facchinetti; Yenny Leal; Josep Vehi
Journal:  Sensors (Basel)       Date:  2017-06-12       Impact factor: 3.576

  8 in total

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