This project will leverage a large-scale cohort of early-onset type 2 diabetes patients to conduct innovative prospective clinical research. By integrating traditional Chinese medicine diagnostic information, clinical data, laboratory results, continuous glucose monitoring, genetic information, multi-omics data, and multi-modal monitoring data, and utilizing advanced data analysis methods such as deep learning, the project aims to establish a comprehensive monitoring, precise classification, and personalized diagnosis and treatment model-a holistic management approach integrating traditional Chinese and Western medicine for early-onset type 2 diabetes. This initiative is expected to enhance the management of early-onset type 2 diabetes, improve treatment outcomes and quality of life for affected patients, pioneer an innovative path for personalized integrated traditional Chinese and Western medicine management in this population, and promote the application of precision medicine in diabetes prevention and treatment.
Study Type
OBSERVATIONAL
Enrollment
2,000
No interventions
Traditional Chinese Medicine Syndrome Score
Time frame: Through study completion, an average of 3 months
HbA1c
Time frame: Through study completion, an average of 3 months
Triglycerides
Time frame: Through study completion, an average of 3 months
High-Density Lipoprotein Cholesterol
Time frame: Through study completion, an average of 3 months
Total Cholesterol
Time frame: Through study completion, an average of 3 months
Fasting Blood Glucose
Time frame: Through study completion, an average of 3 months
Low-Density Lipoprotein Cholesterol
Time frame: Through study completion, an average of 3 months
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