Literature DB >> 34291672

Automated Insulin Delivery Systems: Today, Tomorrow and User Requirements.

Marga Giménez1,2,3, Ignacio Conget1,2,3, Nick Oliver4.   

Abstract

Automated insulin delivery (AID) is the most recent advance in type 1 diabetes (T1D) management. It has the potential to achieve glycemic targets without disabling hypoglycemia, to improve quality of life and reduce diabetes distress and burden associated with self-management. Several AID systems are currently licensed for use by people with T1D in Europe, United States, and the rest of the world. Despite AID becoming a reality in routine clinical practice over the last few years, the commercially hybrid AID and other systems, are still far from a fully optimized automated diabetes management tool. Implementation of AID systems requires education and support of healthcare professionals taking care of people with T1D, as well as users and their families. There is much to do to increase usability, portability, convenience and to reduce the burden associated with the use of the systems. Co-design, involvement of people with lived experience of T1D and robust qualitative assessment is critical to improving the real-world use of AID systems, especially for those who may have greater need. In addition to this, information regarding the psychosocial impact of the use of AID systems in real life is needed. The first commercially available AID systems are not the end of the development journey but are the first step in learning how to optimally automate insulin delivery in a way that is equitably accessible and effective for people living with T1D.

Entities:  

Keywords:  automated insulin delivery; continuous glucose monitoring; psychosocial aspects; time in range; type 1 diabetes

Mesh:

Substances:

Year:  2021        PMID: 34291672      PMCID: PMC8655282          DOI: 10.1177/19322968211029937

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


  39 in total

Review 1.  Is it possible to constantly and accurately monitor blood sugar levels, in people with Type 1 diabetes, with a discrete device (non-invasive or invasive)?

Authors:  P Avari; M Reddy; N Oliver
Journal:  Diabet Med       Date:  2019-03-13       Impact factor: 4.359

2.  In Silico Testing of an Artificial-Intelligence-Based Artificial Pancreas Designed for Use in the Intensive Care Unit Setting.

Authors:  Leon DeJournett; Jeremy DeJournett
Journal:  J Diabetes Sci Technol       Date:  2016-11-01

3.  Closing the Loop in Adults, Children and Adolescents With Suboptimally Controlled Type 1 Diabetes Under Free Living Conditions: A Psychosocial Substudy.

Authors:  Katharine D Barnard; Timothy Wysocki; Vanessa Ully; Julia K Mader; Thomas R Pieber; Hood Thabit; Martin Tauschmann; Lalantha Leelarathna; Sara Hartnell; Carlo L Acerini; Malgorzata E Wilinska; Sibylle Dellweg; Carsten Benesch; Sabine Arnolds; Manuel Holzer; Harald Kojzar; Fiona Campbell; James Yong; Jennifer Pichierri; Peter Hindmarsh; Lutz Heinemann; Mark L Evans; Roman Hovorka
Journal:  J Diabetes Sci Technol       Date:  2017-04-03

4.  Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials.

Authors:  Roy W Beck; Richard M Bergenstal; Tonya D Riddlesworth; Craig Kollman; Zhaomian Li; Adam S Brown; Kelly L Close
Journal:  Diabetes Care       Date:  2018-10-23       Impact factor: 19.112

5.  Closing the loop overnight at home setting: psychosocial impact for adolescents with type 1 diabetes and their parents.

Authors:  Katharine D Barnard; Tim Wysocki; Janet M Allen; Daniela Elleri; Hood Thabit; Lalantha Leelarathna; Arti Gulati; Marianna Nodale; David B Dunger; Tannaze Tinati; Roman Hovorka
Journal:  BMJ Open Diabetes Res Care       Date:  2014-04-16

Review 6.  A Review of Safety and Design Requirements of the Artificial Pancreas.

Authors:  Helga Blauw; Patrick Keith-Hynes; Robin Koops; J Hans DeVries
Journal:  Ann Biomed Eng       Date:  2016-06-28       Impact factor: 3.934

7.  Reduced burden of diabetes and improved quality of life: Experiences from unrestricted day-and-night hybrid closed-loop use in very young children with type 1 diabetes.

Authors:  Gianluca Musolino; Klemen Dovc; Charlotte K Boughton; Martin Tauschmann; Janet M Allen; Katrin Nagl; Maria Fritsch; James Yong; Emily Metcalfe; Dominique Schaeffer; Muriel Fichelle; Ulrike Schierloh; Alena G Thiele; Daniela Abt; Harald Kojzar; Julia K Mader; Sonja Slegtenhorst; Nicole Ashcroft; Malgorzata E Wilinska; Judy Sibayan; Nathan Cohen; Craig Kollman; Sabine E Hofer; Elke Fröhlich-Reiterer; Thomas M Kapellen; Carlo L Acerini; Carine de Beaufort; Fiona Campbell; Birgit Rami-Merhar; Roman Hovorka
Journal:  Pediatr Diabetes       Date:  2019-06-13       Impact factor: 4.866

8.  Automated Insulin Delivery in Real Life (AID-IRL): Real-World User Perspectives on Commercial AID.

Authors:  Dana Lewis
Journal:  J Diabetes Sci Technol       Date:  2020-09-16

9.  Day-and-night glycaemic control with closed-loop insulin delivery versus conventional insulin pump therapy in free-living adults with well controlled type 1 diabetes: an open-label, randomised, crossover study.

Authors:  Lia Bally; Hood Thabit; Harald Kojzar; Julia K Mader; Jehona Qerimi-Hyseni; Sara Hartnell; Martin Tauschmann; Janet M Allen; Malgorzata E Wilinska; Thomas R Pieber; Mark L Evans; Roman Hovorka
Journal:  Lancet Diabetes Endocrinol       Date:  2017-01-14       Impact factor: 44.867

10.  Real-World Patient Reported Outcomes and Glycemic Results with Initiation of Control-IQ Technology.

Authors:  Jordan E Pinsker; Lars Müller; Alexandra Constantin; Scott Leas; Michelle Manning; Molly McElwee Malloy; Harsimran Singh; Steph Habif
Journal:  Diabetes Technol Ther       Date:  2020-08-26       Impact factor: 6.118

View more
  1 in total

Review 1.  Barriers and Facilitators to Diabetes Device Adoption for People with Type 1 Diabetes.

Authors:  Molly L Tanenbaum; Persis V Commissariat
Journal:  Curr Diab Rep       Date:  2022-05-06       Impact factor: 5.430

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.