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      The changing landscape of automated insulin delivery in the management of type 1 diabetes

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          Abstract

          Automated insulin delivery systems, also known as closed-loop or ‘artificial pancreas’ systems, are transforming the management of type 1 diabetes. These systems consist of an algorithm which responds to real-time glucose sensor levels by automatically modulating insulin delivery through an insulin pump. We review the rapidly changing landscape of automated insulin-delivery systems over recent decades, from initial prototypes to the different hybrid closed-loop systems commercially available today. We discuss the growing body of clinical trials and real-world evidence demonstrating their glycaemic and psychosocial benefits. We also address future directions in automated insulin delivery such as dual-hormone systems and adjunct therapy as well as the challenges around ensuring equitable access to closed-loop technology.

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          State of Type 1 Diabetes Management and Outcomes from the T1D Exchange in 2016–2018

          Nicole C Foster, Roy Beck, Kellee Miller … (2019)
          To provide a snapshot of the profile of adults and youth with type 1 diabetes (T1D) in the United States and assessment of longitudinal changes in T1D management and clinical outcomes in the T1D Exchange registry.
          Article 0 comments Cited 606 times – based on 0 reviews     Review now
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            International Consensus on Use of Continuous Glucose Monitoring

            Thomas Danne, Revital Nimri, Tadej Battelino … (2017)
            Measurement of glycated hemoglobin (HbA1c) has been the traditional method for assessing glycemic control. However, it does not reflect intra- and interday glycemic excursions that may lead to acute events (such as hypoglycemia) or postprandial hyperglycemia, which have been linked to both microvascular and macrovascular complications. Continuous glucose monitoring (CGM), either from real-time use (rtCGM) or intermittently viewed (iCGM), addresses many of the limitations inherent in HbA1c testing and self-monitoring of blood glucose. Although both provide the means to move beyond the HbA1c measurement as the sole marker of glycemic control, standardized metrics for analyzing CGM data are lacking. Moreover, clear criteria for matching people with diabetes to the most appropriate glucose monitoring methodologies, as well as standardized advice about how best to use the new information they provide, have yet to be established. In February 2017, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address these issues. This article summarizes the ATTD consensus recommendations and represents the current understanding of how CGM results can affect outcomes.
            Article 0 comments Cited 596 times – based on 0 reviews     Review now
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              The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study at 30 Years: Overview

              David M Nathan, (2013)
              OBJECTIVE The Diabetes Control and Complications Trial (DCCT) was designed to test the glucose hypothesis and determine whether the complications of type 1 diabetes (T1DM) could be prevented or delayed. The Epidemiology of Diabetes Interventions and Complications (EDIC) observational follow-up determined the durability of the DCCT effects on the more-advanced stages of diabetes complications including cardiovascular disease (CVD). RESEARCH DESIGN AND METHODS The DCCT (1982–1993) was a controlled clinical trial in 1,441 subjects with T1DM comparing intensive therapy (INT), aimed at achieving levels of glycemia as close to the nondiabetic range as safely possible, with conventional therapy (CON), which aimed to maintain safe asymptomatic glucose control. INT utilized three or more daily insulin injections or insulin pump therapy guided by self-monitored glucose. EDIC (1994–present) is an observational study of the DCCT cohort. RESULTS The DCCT followed >99% of the cohort for a mean of 6.5 years and demonstrated a 35–76% reduction in the early stages of microvascular disease with INT, with a median HbA1c of 7%, compared with CONV, with a median HbA1c of 9%. The major adverse effect of INT was a threefold increased risk of hypoglycemia, which was not associated with a decline in cognitive function or quality of life. EDIC showed a durable effect of initial assigned therapies despite a loss of the glycemic separation (metabolic memory) and demonstrated that the reduction in early-stage complications during the DCCT translated into substantial reductions in severe complications and CVD. CONCLUSIONS DCCT/EDIC has demonstrated the effectiveness of INT in reducing the long-term complications of T1DM and improving the prospects for a healthy life span.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Endocr Connect
                Journal ID (iso-abbrev): Endocr Connect
                Journal ID (hwp): EC
                Title: Endocrine Connections
                Publisher: Bioscientifica Ltd (Bristol )
                ISSN (Electronic): 2049-3614
                Publication date (Electronic): 08 June 2023
                Publication date (Electronic preprint): 08 June 2023
                Publication date Collection: 01 August 2023
                Volume: 12
                Issue: 8
                Electronic Location Identifier: e230132
                Affiliations
                [1 ]Wellcome-MRC Institute of Metabolic Science , Addenbrooke's Hospital, Cambridge, UK
                [2 ]Cambridge University Hospitals NHS Foundation Trust , Wolfson Diabetes and Endocrine Clinic, Cambridge, UK
                Author notes
                Correspondence should be addressed to R Lakshman: rama.lakshman4@ 123456nhs.net
                Author information
                http://orcid.org/0000-0002-4341-1307
                Article
                Publisher ID: EC-23-0132
                DOI: 10.1530/EC-23-0132
                PMC ID: 10448576
                PubMed ID: 37289734
                SO-VID: a3084d80-03c1-4837-9705-418ee574c186
                Copyright © © the author(s)
                License:

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                Date received : 25 May 2023
                Date accepted : 08 June 2023
                Categories
                Subject: Review

                Keywords: automated insulin delivery,artificial pancreas,closed-loop systems,type 1 diabetes
                Data availability:
                Keywords: automated insulin delivery, artificial pancreas, closed-loop systems, type 1 diabetes

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