SIESTA
Synergies in Sleep, Software, and Diabetes Management
With a cross-sectional survey, sleep study and machine learning analysis, SIESTA aims to better characterise sleep quality and duration in people with type 1 diabetes and their caregivers, with a focus on the impact use of automated insulin delivery (AID) systems has on both sleep and diabetes management.
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Motivation
People with type 1 diabetes are increasingly using AID systems—algorithmically-regulated “closed-loop” insulin dosing—to manage their diabetes day and night, with evidence supporting their efficacy in maintaining target glucose ranges over other methods of management.
While many individuals report improved sleep quality using AID over other methods, there are still users who regularly experience poor, disrupted sleep. Sleep disruption has marked effects on health outcomes in people with diabetes, and profoundly impacts quality of life both for them and their caregivers.
Research into the mechanistic relationship between sleep and diabetes could identify avenues for improving AID systems, leading to better health outcomes and quality of life.
Innovations and perspectives
Building from the OPEN project—which is the first patient-led interdisciplinary project to be funded by the EU and first international research project on open-source technologies in diabetes—SIESTA should deepen understanding of the synergistic relationship between diabetes and sleep, through assessment of both real-world data and subjective measures.
Selected Publications
- Cooper D, Ubben T, Knoll C, Ballhausen H, O'Donnell S, Braune K, Lewis D. Open-source Web Portal for Managing Self-reported Data and Real-world Data Donation in Diabetes Research: Platform Feasibility Study. JMIR Diabetes 2022;7(1):e33213. doi.org/10.2196/33213
Project partners
- Brain Simulation Section (part of Charité - Universitätsmedizin Berlin)