Literature DB >> 33955251

Algorithms for Automated Insulin Delivery: An Overview.

Andreas Thomas1, Lutz Heinemann1.   

Abstract

The technology needed to "close the loop," that is, a system for continuous glucose monitoring and a pump that infuses insulin, are only 2 of the 3 components needed for each system for automated insulin delivery (AID), the other is a "translation" of the glucose information into the appropriate amount of insulin to be applied at a given point in time to keep glucose levels in the body in the target range. It might look straightforward to calculate the required insulin dose and control the pump to apply this immediately; however, once a given amount of insulin is in the body, it will be absorbed and become metabolically active. To avoid lowering glucose levels toward too low levels, the algorithms used to calculate the insulin dose have to take a number of other factors into account. This is needed to make sure that AID systems are not only efficient but also safe, that is, not only Time-in-Range should be maximal, also Time-below-Range should be minimal. The review characterizes the different types of AID algorithms that were developed in the last decades. Using a structured approach, the different algorithms are classified. A systematic evaluation of the performance of the different algorithms is missing, not only during the clinical development of AID systems, but also in daily practice. However, it might very well be that other factors determine which AID algorithms will be used in practice.

Entities:  

Keywords:  automated insulin delivery; continuous glucose monitoring; insulin therapy

Mesh:

Substances:

Year:  2021        PMID: 33955251      PMCID: PMC9445345          DOI: 10.1177/19322968211008442

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


  33 in total

1.  Graphical and numerical evaluation of continuous glucose sensing time lag.

Authors:  Boris P Kovatchev; Devin Shields; Marc Breton
Journal:  Diabetes Technol Ther       Date:  2009-03       Impact factor: 6.118

2.  Six-Month Randomized, Multicenter Trial of Closed-Loop Control in Type 1 Diabetes.

Authors:  Sue A Brown; Boris P Kovatchev; Dan Raghinaru; John W Lum; Bruce A Buckingham; Yogish C Kudva; Lori M Laffel; Carol J Levy; Jordan E Pinsker; R Paul Wadwa; Eyal Dassau; Francis J Doyle; Stacey M Anderson; Mei Mei Church; Vikash Dadlani; Laya Ekhlaspour; Gregory P Forlenza; Elvira Isganaitis; David W Lam; Craig Kollman; Roy W Beck
Journal:  N Engl J Med       Date:  2019-10-16       Impact factor: 91.245

Review 3.  Role of Glucagon in Automated Insulin Delivery.

Authors:  Leah M Wilson; Peter G Jacobs; Jessica R Castle
Journal:  Endocrinol Metab Clin North Am       Date:  2019-12-10       Impact factor: 4.741

4.  Pharmacokinetic and Pharmacodynamic Characteristics of Dasiglucagon, a Novel Soluble and Stable Glucagon Analog.

Authors:  Ulrike Hövelmann; Britta Væver Bysted; Ulrik Mouritzen; Francesca Macchi; Daniela Lamers; Birgit Kronshage; Daniél Vega Møller; Tim Heise
Journal:  Diabetes Care       Date:  2017-12-22       Impact factor: 19.112

5.  Feasibility of automating insulin delivery for the treatment of type 1 diabetes.

Authors:  Garry M Steil; Kerstin Rebrin; Christine Darwin; Farzam Hariri; Mohammed F Saad
Journal:  Diabetes       Date:  2006-12       Impact factor: 9.461

6.  Preliminary evaluation of a new semi-closed-loop insulin therapy system over the prandial period in adult patients with type 1 diabetes: the WP6.0 Diabeloop study.

Authors:  Marie Aude Quemerais; Maeva Doron; Florent Dutrech; Vincent Melki; Sylvia Franc; Michel Antonakios; Guillaume Charpentier; Helene Hanaire; Pierre Yves Benhamou
Journal:  J Diabetes Sci Technol       Date:  2014-08-04

7.  Confusion Regarding Duration of Insulin Action: A Potential Source for Major Insulin Dose Errors by Bolus Calculators.

Authors:  John Walsh; Ruth Roberts; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2014-01-01

8.  Time lag of glucose from intravascular to interstitial compartment in humans.

Authors:  Ananda Basu; Simmi Dube; Michael Slama; Isabel Errazuriz; Jose Carlos Amezcua; Yogish C Kudva; Thomas Peyser; Rickey E Carter; Claudio Cobelli; Rita Basu
Journal:  Diabetes       Date:  2013-09-05       Impact factor: 9.461

9.  Blood glucose control in type 1 diabetes with a bihormonal bionic endocrine pancreas.

Authors:  Steven J Russell; Firas H El-Khatib; David M Nathan; Kendra L Magyar; John Jiang; Edward R Damiano
Journal:  Diabetes Care       Date:  2012-08-24       Impact factor: 19.112

Review 10.  International Consensus on Use of Continuous Glucose Monitoring.

Authors:  Thomas Danne; Revital Nimri; Tadej Battelino; Richard M Bergenstal; Kelly L Close; J Hans DeVries; Satish Garg; Lutz Heinemann; Irl Hirsch; Stephanie A Amiel; Roy Beck; Emanuele Bosi; Bruce Buckingham; Claudio Cobelli; Eyal Dassau; Francis J Doyle; Simon Heller; Roman Hovorka; Weiping Jia; Tim Jones; Olga Kordonouri; Boris Kovatchev; Aaron Kowalski; Lori Laffel; David Maahs; Helen R Murphy; Kirsten Nørgaard; Christopher G Parkin; Eric Renard; Banshi Saboo; Mauro Scharf; William V Tamborlane; Stuart A Weinzimer; Moshe Phillip
Journal:  Diabetes Care       Date:  2017-12       Impact factor: 19.112

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  1 in total

1.  Diurnal Variation of Real-Life Insulin Sensitivity Factor Among Children and Adolescents With Type 1 Diabetes Using Ultra-Long-Acting Basal Insulin Analogs.

Authors:  Ahmed M Hegab
Journal:  Front Pediatr       Date:  2022-03-08       Impact factor: 3.418

  1 in total

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