Health Condition 1: E112- Type 2 diabetes mellitus with kidney complications
Conditions
Interventions
Intervention1: Nil: Nil
Sponsors
Dr Cynthia Amrutha
Eligibility
Inclusion criteria
Inclusion criteria: 1. Patients with DKD of GFR category G2 and G3a/G3b (CKD-EPI eGFR 30- 89 ml/min/1.73m2) 2. Adult patients within the age of 30-65 years 3. Patients who are diagnosed with DKD and entered into the follow-up cohort at Kasturba Hospital in the last 1 year.
Exclusion criteria
Exclusion criteria:
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Development of machine learning based Clinical Prediction Tool- a validated machine learning model that combines clinical parameters to predict the risk and progression of Diabetic Kidney Disease (DKD), Timepoint: 24 months | — |
Secondary
| Measure | Time frame |
|---|---|
| 2.Identification of Prognostic miRNAs: Discovery of specific circulating microRNAs (miRNAs) that serve as early, non-invasive biomarkers for forecasting DKD progression. 3.Differentiation of DKD phenotypes using miRNA signatures: Isolation and characterization of miRNA expression patterns capable of distinguishing between proteinuric and non-proteinuric forms of DKD, potentially enabling phenotype-specific diagnosis and treatment planning. Timepoint: 24-36 months | — |
Countries
India
Contacts
Public ContactDr Cynthia Amrutha Sukumar
Kasturba Medical College, Manipal
Outcome results
None listed