Literature DB >> 18709180

A Run-to-Run Control Strategy to Adjust Basal Insulin Infusion Rates in Type 1 Diabetes.

Cesar C Palerm1, Howard Zisser, Lois Jovanovič, Francis J Doyle.   

Abstract

Maintaining good glycemic control is a daily challenge for people with type 1 diabetes. Insulin requirements are changing constantly due to many factors, such as levels of stress and physical activity. The basal insulin requirement also has a circadian rhythm, adding another level of complexity. Automating the adjustment of insulin dosing would result in improved glycemic control, as well as an improved quality of life by significantly reducing the burden on the patient. Building on our previous success of using run-to-run control for prandial insulin dosing (a strategy adapted from the chemical process industry), we show how this same framework can be used to adjust basal infusion profiles. We present a mathematical model of insulin-glucose dynamics which we augment in order to capture the circadian variation in insulin requirements. Using this model, we show that the run-to-run framework can also be successfully applied to adjust basal insulin dosing.

Entities:  

Year:  2008        PMID: 18709180      PMCID: PMC2516944          DOI: 10.1016/j.jprocont.2007.07.010

Source DB:  PubMed          Journal:  J Process Control        ISSN: 0959-1524            Impact factor:   3.666


  30 in total

1.  Run-to-run control of meal-related insulin dosing.

Authors:  Howard Zisser; Lois Jovanovic; Frank Doyle; Paulina Ospina; Camelia Owens
Journal:  Diabetes Technol Ther       Date:  2005-02       Impact factor: 6.118

2.  Glycemic control and cardiovascular disease--should we reassess clinical goals?

Authors:  William T Cefalu
Journal:  N Engl J Med       Date:  2005-12-22       Impact factor: 91.245

3.  An improved PID switching control strategy for type 1 diabetes.

Authors:  Gianni Marchetti; Massimiliano Barolo; Lois Jovanovic; Howard Zisser; Dale E Seborg
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2006

4.  A model-based algorithm for blood glucose control in type I diabetic patients.

Authors:  R S Parker; F J Doyle; N A Peppas
Journal:  IEEE Trans Biomed Eng       Date:  1999-02       Impact factor: 4.538

5.  Run-to-run control of blood glucose concentrations for people with Type 1 diabetes mellitus.

Authors:  Camelia Owens; Howard Zisser; Lois Jovanovic; Bala Srinivasan; Dominique Bonvin; Francis J Doyle
Journal:  IEEE Trans Biomed Eng       Date:  2006-06       Impact factor: 4.538

6.  Closed-loop subcutaneous insulin infusion algorithm with a short-acting insulin analog for long-term clinical application of a wearable artificial endocrine pancreas.

Authors:  S Shimoda; K Nishida; M Sakakida; Y Konno; K Ichinose; M Uehara; T Nowak; M Shichiri
Journal:  Front Med Biol Eng       Date:  1997

7.  Strict glycemic control in diabetic dogs with closed-loop intraperitoneal insulin infusion algorithm designed for an artificial endocrine pancreas.

Authors:  Yasuto Matsuo; Seiya Shimoda; Michiharu Sakakida; Kenro Nishida; Taiji Sekigami; Shinji Ichimori; Kenshi Ichinose; Motoaki Shichiri; Eiichi Araki
Journal:  J Artif Organs       Date:  2003       Impact factor: 1.731

8.  Randomized trial of computer-assisted insulin delivery in patients with type I diabetes beginning pump therapy.

Authors:  C M Peterson; L Jovanovic; L H Chanoch
Journal:  Am J Med       Date:  1986-07       Impact factor: 4.965

9.  Controlled multicenter study on the effect of computer assistance in intensive insulin therapy of type 1 diabetics.

Authors:  Jürgen Schrezenmeir; Kay Dirting; Peter Papazov
Journal:  Comput Methods Programs Biomed       Date:  2002-08       Impact factor: 5.428

10.  Restoring euglycemia in the basal state using continuous glucose monitoring in subjects with type 1 diabetes mellitus.

Authors:  Howard C Zisser; Wendy C Bevier; Lois Jovanovic
Journal:  Diabetes Technol Ther       Date:  2007-12       Impact factor: 6.118

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  27 in total

1.  Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters.

Authors:  M W Percival; Y Wang; B Grosman; E Dassau; H Zisser; L Jovanovič; F J Doyle
Journal:  J Process Control       Date:  2011-03-01       Impact factor: 3.666

2.  Anticipating the next meal using meal behavioral profiles: a hybrid model-based stochastic predictive control algorithm for T1DM.

Authors:  C S Hughes; S D Patek; M Breton; B P Kovatchev
Journal:  Comput Methods Programs Biomed       Date:  2010-06-19       Impact factor: 5.428

3.  Clinical update on optimal prandial insulin dosing using a refined run-to-run control algorithm.

Authors:  Howard Zisser; Cesar C Palerm; Wendy C Bevier; Francis J Doyle; Lois Jovanovic
Journal:  J Diabetes Sci Technol       Date:  2009-05-01

4.  A novel adaptive basal therapy based on the value and rate of change of blood glucose.

Authors:  Youqing Wang; Matthew W Percival; Eyal Dassau; Howard C Zisser; Lois Jovanovic; Francis J Doyle
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

Review 5.  Bolus Advisors: Sources of Error, Targets for Improvement.

Authors:  John Walsh; Ruth Roberts; Timothy S Bailey; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2017-07-25

6.  Controlling the AP Controller: Controller Performance Assessment and Modification.

Authors:  Iman Hajizadeh; Nicole Hobbs; Sediqeh Samadi; Mert Sevil; Mudassir Rashid; Rachel Brandt; Mohammad Reza Askari; Zacharie Maloney; Ali Cinar
Journal:  J Diabetes Sci Technol       Date:  2019-09-27

7.  Historical data enhances safety supervision system performance in T1DM insulin therapy risk management.

Authors:  Colleen Hughes-Karvetski; Stephen D Patek; Marc D Breton; Boris P Kovatchev
Journal:  Comput Methods Programs Biomed       Date:  2012-02-17       Impact factor: 5.428

Review 8.  Multivariable Adaptive Artificial Pancreas System in Type 1 Diabetes.

Authors:  Ali Cinar
Journal:  Curr Diab Rep       Date:  2017-08-15       Impact factor: 4.810

9.  Run-to-run tuning of model predictive control for type 1 diabetes subjects: in silico trial.

Authors:  Lalo Magni; Marco Forgione; Chiara Toffanin; Chiara Dalla Man; Boris Kovatchev; Giuseppe De Nicolao; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

10.  Adaptive Zone Model Predictive Control of Artificial Pancreas Based on Glucose- and Velocity-Dependent Control Penalties.

Authors:  Dawei Shi; Eyal Dassau; Francis J Doyle
Journal:  IEEE Trans Biomed Eng       Date:  2018-08-21       Impact factor: 4.538

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