Diabetes
Conditions
Brief summary
The prevalence of diabetes has been increasing year by year. According to the International Diabetes Federation (IDF) statistics in 2021, the global number of people with diabetes has reached 537 million. The patient population is large and heterogeneous, and precise diagnosis and treatment of diabetes patients have been a focus of attention. The objective of this study is to clarify the current status of precision classification and diagnosis of diabetes patients through retrospective and prospective cohort studies, and to establish a model for precision classification and diagnosis of diabetes, improving the accuracy of diabetes classification and diagnosis; based on big data of precision medicine for diabetes patients and follow-up cohorts, to establish precise diagnostic, therapeutic, and predictive methods for diabetes; and through multi-omics data analysis, to explore the potential pathogenesis of diabetes, explaining the heterogeneity of patients, and guiding individualized treatment for patients.
Interventions
OTHERno intervention
It's an observational study, no intervention included
Sponsors
Second Xiangya Hospital of Central South University
Study design
Observational model
COHORT
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* Patients diagnosed with diabetes according to WHO 1999 criteria
Exclusion criteria
* with duration more than 1 year; Diabetes has not been diagnosed by WHO standards in 1999; Absence of medical history data
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The currency analysis of diabetes classification | July 1st 2023 to December 31th 2023 | To assess the accuracy rate of diabetes classification diagnoses according to Classification of diabetes mellitus in China: an expert consensus statement and explore variations across centers in different regions and hospital levels. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| To establish a model for predicting diabetic retinopathy | January 1st 2024 to December 31th 2028 | To establish a model for diabetic retinopathy prediction, and calculate the sensitivity and specificity of the model were by comparing with the retinopathy outcome of patients. |
| To establish a model for predicting diabetic kidney disease | January 1st 2024 to December 31th 2028 | To establish a model for diabetic kidney disease (DKD) prediction, and calculate the sensitivity and specificity of the model were by comparing with the DKD outcome of patients. |
| To establish a model for predicting diabetic neuropathy | January 1st 2024 to December 31th 2028 | To establish a model for diabetic neuropathy prediction, and calculate the sensitivity and specificity of the model were by comparing with the outcome of patients. |
Other
| Measure | Time frame | Description |
|---|---|---|
| To establish a model for hypoglycemic therapy | January 1st 2024 to December 31th 2028 | To establish a model for hypoglycemic therapy selection, and compare the rate of HbA1c\<7% in patients who are in accordance with the model choice and those who aren't. |
Countries
China
Outcome results
None listed