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Fully closed-loop systems: can people with type 1 diabetes just do it? Insights from open-source systems.

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Summary

Open-source automated insulin delivery (OS-AID) systems show promise for diabetes management without meal announcements. These systems offer comparable glucose control to commercial options, potentially reducing user burden but requiring expert configuration.

Keywords:
AIDAutomated insulin deliveryDIYDiabetes technologyFully closed-loopHybrid closed-loopOpen-sourcePatient-led innovationReviewUnannounced meals

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Area of Science:

  • Endocrinology
  • Biomedical Engineering
  • Diabetes Technology

Background:

  • Automated insulin delivery (AID) systems have advanced diabetes care, reducing user interaction for glucose management.
  • Commercial hybrid closed-loop (HCL) systems require manual meal announcements, limiting real-world automation.
  • Open-source AID (OS-AID) systems, developed by the diabetes community, offer potential for operation without meal announcements.

Purpose of the Study:

  • To review the current status and future prospects of AID systems that do not require meal announcements.
  • To focus on real-world insights from OS-AID technologies.
  • To evaluate the potential for reduced user management burden with OS-AID.

Main Methods:

  • Review of current literature and clinical trials on AID systems without meal announcement.
  • Synthesis of user and healthcare professional experiences with OS-AID.
  • Analysis of emerging clinical evidence regarding OS-AID performance.

Main Results:

  • OS-AID systems demonstrate effective glucose management comparable to HCL systems, without requiring meal announcements.
  • Clinical trials suggest OS-AID can achieve similar glycaemic outcomes with potentially less user burden.
  • Challenges include the need for expert configuration and managing rapid physiological changes (e.g., exercise).

Conclusions:

  • Successful implementation of AID without meal announcement necessitates advanced algorithms, personalization, and clinician involvement.
  • Future advancements may include adjunctive therapies, AI, and enhanced physiological modeling for improved performance.
  • The goal is to achieve wider adoption and 'set-and-forget' functionality in diabetes management.