Literature DB >> 34773301

Real-world evidence on clinical outcomes of people with type 1 diabetes using open-source and commercial automated insulin dosing systems: A systematic review.

Christine Knoll1,2,3, Sofia Peacock4,5, Mandy Wäldchen3, Drew Cooper1,2, Simran Kaur Aulakh6, Klemens Raile1, Sufyan Hussain4,5,7, Katarina Braune1,2,8.   

Abstract

AIMS: Several commercial and open-source automated insulin dosing (AID) systems have recently been developed and are now used by an increasing number of people with diabetes (PwD). This systematic review explored the current status of real-world evidence on the latest available AID systems in helping to understand their safety and effectiveness.
METHODS: A systematic review of real-world studies on the effect of commercial and open-source AID system use on clinical outcomes was conducted employing a devised protocol (PROSPERO ID 257354).
RESULTS: Of 441 initially identified studies, 21 published 2018-2021 were included: 12 for Medtronic 670G; one for Tandem Control-IQ; one for Diabeloop DBLG1; two for AndroidAPS; one for OpenAPS; one for Loop; three comparing various types of AID systems. These studies found that several types of AID systems improve Time-in-Range and haemoglobin A1c (HbA1c ) with minimal concerns around severe hypoglycaemia. These improvements were observed in open-source and commercially developed AID systems alike.
CONCLUSIONS: Commercially developed and open-source AID systems represent effective and safe treatment options for PwD of several age groups and genders. Alongside evidence from randomized clinical trials, real-world studies on AID systems and their effects on glycaemic outcomes are a helpful method for evaluating their safety and effectiveness.
© 2021 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.

Entities:  

Keywords:  automated insulin delivery; automated insulin dosing; diabetes mellitus; diabetes technology; open-source; real-world evidence; type 1 diabetes

Mesh:

Substances:

Year:  2021        PMID: 34773301     DOI: 10.1111/dme.14741

Source DB:  PubMed          Journal:  Diabet Med        ISSN: 0742-3071            Impact factor:   4.359


  4 in total

1.  Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems.

Authors:  Arsalan Shahid; Dana M Lewis
Journal:  Nutrients       Date:  2022-05-02       Impact factor: 6.706

2.  Quantifying Input Behaviors That Influence Clinical Outcomes in Diabetes and Other Chronic Illnesses.

Authors:  Dana M Lewis
Journal:  J Diabetes Sci Technol       Date:  2021-12-31

3.  Open-source Web Portal for Managing Self-reported Data and Real-world Data Donation in Diabetes Research: Platform Feasibility Study.

Authors:  Drew Cooper; Tebbe Ubben; Christine Knoll; Hanne Ballhausen; Shane O'Donnell; Katarina Braune; Dana Lewis
Journal:  JMIR Diabetes       Date:  2022-03-31

4.  Practical Guidance on Open Source and Commercial Automated Insulin Delivery Systems: A Guide for Healthcare Professionals Supporting People with Insulin-Requiring Diabetes.

Authors:  Dana M Lewis; Sufyan Hussain
Journal:  Diabetes Ther       Date:  2022-08-01       Impact factor: 3.595

  4 in total

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