The value of intelligent lifestyle intervention for T2D and its complications has been initially explored, but evidence-based support for the effectiveness of related AI risk prediction models and intervention models remains to be confirmed. The primary objective of this study is to verify the effectiveness of an AI model for predicting the risk of T2D complications based on phenotype, laboratory indicators and wearable device indicators, and to explore the effect and applicability of an intelligent lifestyle intervention model combining wearable devices and smartphones in preventing T2D complications.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
NONE
Enrollment
6,000
Routine doctor-patient interaction.
Wearable monitoring + CGM management platform-assisted administration
Mini-program-assisted health management
Wearable monitoring + mini-program integrated management
Second Xiangya Hospital of Central South University
Changsha, China
RECRUITINGHbA1c
Between-group differences in HbA1c change (from Central Lab)
Time frame: Baseline, 1 year
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