T2DM
Background
People with type 2 diabetes mellitus (T2DM) have insulin resistance and relative insulin deficiency. Therefore, the management of this condition involves both reducing insulin resistance and promoting insulin secretion.
T2DM naturally progresses towards an increasingly marked insulin deficiency, which leads to the need for the pancreas to supplement insulin.
Artificial intelligence using a self-learning algorithm can be used to automatise and personalise insulin administration. These “closed loop” systems improve glycaemic control, reduce the number of hypo- and hyperglycaemias, as well as the mental burden associated with the disease, thereby improving the quality of life of affected individuals. To date, these “closed loops” are only available for people with type 1 diabetes. The considerable benefits of these systems for T1DM suggest that similar benefits could occur for T2DM treated with basal-bolus insulin regimens. This study is part of a project to develop a specific algorithm that addresses the specific characteristics of T2DM.
Promotor
Diabeloop
Project coordination
IC@dom
Type of study
Interventional / Clinical investigation in the home
Single-centre protocol
Grenoble University Hospital
Sample size
35 participants
Study design
Prospective observational data collection study.
The aim of this study is to record changes in blood glucose levels in people with T2DM during different daily life situations: physical activity, meal-times, sleep etc. The data will be used to develop a bench test for the evaluation of insulin delivery algorithms to treat people with insulin-dependent diabetes using a closed-loop system.
IC@dom has been commissioned to provide comprehensive support for Diabeloop at every stage of the clinical investigation:
Project design and management
Drafting the protocol
Drafting the CRF (case report form)
Home-intervention by a team of diabetes nurse specialists
Inclusion and follow-up of participants
Provision of actimeters and data analysis
Results
Blood glucose data were collected over 7 consecutive days and compared with data collected during daily life situations (physical activity, meal-times, sleep, etc.) to model an algorithm test bed for the development of the first closed-loop treatment for people with T2DM
This initial study led to a second feasibility trial, in which people with T2DM underwent closed-loop treatment as part of the trial.
2nd
feasibility study
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