Mobile Health and Wearable Devices for Diabetes Complication Management
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…
Conditions studied
Diabetes Mellitus Type 2, Diabetes Mellitus Complications
About this study
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.
Interventions
- Other: Device: No specific devices — Routine doctor-patient interaction.
- Other: Device: CGM,CGM management platform — Wearable monitoring + CGM management platform-assisted administration
- Other: Device: "Professor Tang" WeChat Mini-program — Mini-program-assisted health management
- Other: Device: CGM, Smart Bracelet, "Professor Tang" WeChat Mini-program — Wearable monitoring + mini-program integrated management
Primary outcomes
- HbA1c (Baseline, 1 year)
Eligibility information
Study locations
- Second Xiangya Hospital of Central South University, Changsha, China
Source: ClinicalTrials.gov. Record last refreshed by Varda Clinical: 2026-09-27.