Literature DB >> 25049364

Novel insulin delivery profiles for mixed meals for sensor-augmented pump and closed-loop artificial pancreas therapy for type 1 diabetes mellitus.

Asavari Srinivasan1, Joon Bok Lee2, Eyal Dassau2, Francis J Doyle3.   

Abstract

Maintaining euglycemia for people with type 1 diabetes is highly challenging, and variations in glucose absorption rates with meal composition require meal type specific insulin delivery profiles for optimal blood glucose control. Traditional basal/bolus therapy is not fully optimized for meals of varied fat contents. Thus, regimens for low- and high-fat meals were developed to improve current insulin pump therapy. Simulations of meals with varied fat content demonstrably replicated published data. Subsequently, an insulin profile library with optimized delivery regimens under open and closed loop for various meal compositions was constructed using particle swarm optimization. Calculations showed that the optimal basal bolus insulin profiles for low-fat meals comprise a normal bolus or a short wave. The preferred delivery for high-fat meals is typically biphasic, but can extend to multiple phases depending on meal characteristics. Results also revealed that patients that are highly sensitive to insulin could benefit from biphasic deliveries. Preliminary investigations of the optimal closed-loop regimens also display bi- or multiphasic patterns for high-fat meals. The novel insulin delivery profiles present new waveforms that provide better control of postprandial glucose excursions than existing schemes. Furthermore, the proposed novel regimens are also more or similarly robust to uncertainties in meal parameter estimates, with the closed-loop schemes demonstrating superior performance and robustness.
© 2014 Diabetes Technology Society.

Entities:  

Keywords:  artificial pancreas; biomedical control; bolus wizard; insulin dosage; insulin pump therapy; particle swarm optimization; type 1 diabetes

Mesh:

Substances:

Year:  2014        PMID: 25049364      PMCID: PMC4455363          DOI: 10.1177/1932296814543660

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


  24 in total

1.  Post-prandial glucose excursions following four methods of bolus insulin administration in subjects with type 1 diabetes.

Authors:  H P Chase; S Z Saib; T MacKenzie; M M Hansen; S K Garg
Journal:  Diabet Med       Date:  2002-04       Impact factor: 4.359

2.  Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes.

Authors:  Roman Hovorka; Valentina Canonico; Ludovic J Chassin; Ulrich Haueter; Massimo Massi-Benedetti; Marco Orsini Federici; Thomas R Pieber; Helga C Schaller; Lukas Schaupp; Thomas Vering; Malgorzata E Wilinska
Journal:  Physiol Meas       Date:  2004-08       Impact factor: 2.833

Review 3.  Type 1 diabetes.

Authors:  Denis Daneman
Journal:  Lancet       Date:  2006-03-11       Impact factor: 79.321

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

Review 5.  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

Review 6.  A new approach to diabetic control: fuzzy logic and insulin pump technology.

Authors:  Paul Grant
Journal:  Med Eng Phys       Date:  2006-10-18       Impact factor: 2.242

7.  Benefit of supplementary fat plus protein counting as compared with conventional carbohydrate counting for insulin bolus calculation in children with pump therapy.

Authors:  Olga Kordonouri; Reinhard Hartmann; Kerstin Remus; Sarah Bläsig; Evelin Sadeghian; Thomas Danne
Journal:  Pediatr Diabetes       Date:  2012-07-06       Impact factor: 4.866

8.  Optimal insulin pump dosing and postprandial glycemia following a pizza meal using the continuous glucose monitoring system.

Authors:  Susan M Jones; Jill L Quarry; Molly Caldwell-McMillan; David T Mauger; Robert A Gabbay
Journal:  Diabetes Technol Ther       Date:  2005-04       Impact factor: 6.118

9.  Acute effect of meal glycemic index and glycemic load on blood glucose and insulin responses in humans.

Authors:  José Galgani; Carolina Aguirre; Erik Díaz
Journal:  Nutr J       Date:  2006-09-05       Impact factor: 3.271

10.  Clinical evaluation of a personalized artificial pancreas.

Authors:  Eyal Dassau; Howard Zisser; Rebecca A Harvey; Matthew W Percival; Benyamin Grosman; Wendy Bevier; Eran Atlas; Shahar Miller; Revital Nimri; Lois Jovanovic; Francis J Doyle
Journal:  Diabetes Care       Date:  2012-11-27       Impact factor: 19.112

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  6 in total

Review 1.  Boluses in Insulin Therapy.

Authors:  Ralph Ziegler; Guido Freckmann; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2016-07-10

2.  Randomized Crossover Comparison of Personalized MPC and PID Control Algorithms for the Artificial Pancreas.

Authors:  Jordan E Pinsker; Joon Bok Lee; Eyal Dassau; Dale E Seborg; Paige K Bradley; Ravi Gondhalekar; Wendy C Bevier; Lauren Huyett; Howard C Zisser; Francis J Doyle
Journal:  Diabetes Care       Date:  2016-06-11       Impact factor: 19.112

3.  Assessing Mealtime Macronutrient Content: Patient Perceptions Versus Expert Analyses via a Novel Phone App.

Authors:  Melanie B Gillingham; Zoey Li; Roy W Beck; Peter Calhoun; Jessica Castle; Mark Clements; Eyal Dassau; Francis J Doyle; Robin L Gal; Peter Jacobs; Susana R Patton; Michael R Rickels; Michael Riddell; Corby K Martin
Journal:  Diabetes Technol Ther       Date:  2020-09-29       Impact factor: 6.118

4.  An Adaptive Nonlinear Basal-Bolus Calculator for Patients With Type 1 Diabetes.

Authors:  Dimitri Boiroux; Tinna Björk Aradóttir; Kirsten Nørgaard; Niels Kjølstad Poulsen; Henrik Madsen; John Bagterp Jørgensen
Journal:  J Diabetes Sci Technol       Date:  2016-09-25

Review 5.  Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.

Authors:  Ivan Contreras; Josep Vehi
Journal:  J Med Internet Res       Date:  2018-05-30       Impact factor: 5.428

Review 6.  Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.

Authors:  Nichole S Tyler; Peter G Jacobs
Journal:  Sensors (Basel)       Date:  2020-06-05       Impact factor: 3.576

  6 in total

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