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About
The goal of this interventional study is to build a high quality, real world multimodal dataset that combines continuous glucose monitoring (CGM), wearable and fitness data, performance metrics, and saliva and urine omics collected during a prolonged, moderate intensity outdoor gravel-cycling session in adults with type 1 diabetes (T1D).
The main questions it aims to answer are:
Participants will:
This study will generate an integrated resource that supports the development and validation of AI models for predicting glucose responses to exercise in T1D and will help guide future studies on how prolonged exercise affects glucose control.
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Inclusion (healthy control group): adults 18-60 years without diabetes and physically active (≥ 4 hours/week of exercise) who can provide pre/post saliva and uringe samples for omics analyses.
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29 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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