Background Information
This tool predicts the endotypes of Type 2 Diabetes in four groups such as:
- Severe Insulin Deficient Diabetes (SIDD)
- Insulin Resistant Obese Diabetes (IROD)
- Combined Insulin Resistant and Deficient Diabetes (CIRDD)
- Mild Age-Related Diabetes (MARD)
Information Required for Cluster Assignment
To assign a person with type 2 diabetes to one of the identified subtypes, the following clinical parameters are required:
- Age at diagnosis (years)
- Body Mass Index (BMI)
- Waist circumference
- HbA1c (%)
- Triglycerides
- HDL cholesterol
- C-peptide (stimulated) – CPS
- C-peptide (fasting) – CPF
Information Required for Risk Prediction
The following parameters are used to estimate the risk of diabetes-related complications or disease progression:
- Age
- Age at diagnosis
- Waist circumference
- Gender
- Body Mass Index (BMI)
- HbA1c (%)
- Triglycerides
- HDL cholesterol
- Total cholesterol
- Systolic and Diastolic Blood Pressure
- Serum Creatinine
These parameters are analyzed using machine learning models trained on longitudinal data to predict individualized risk scores and disease progression profiles.
Note: The clustering model was originally developed for individuals with newly onset diabetes patients; please consider this context while interpreting the results
References
-
Anjana RM, Baskar V, Nair AT, Jebarani S, Siddiqui MK, Pradeepa R, Unnikrishnan R, Palmer C, Pearson E, Mohan V.
Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study.
BMJ Open Diabetes Research and Care. 2020 Aug 1; 8(1): e001506. - Anjana RM, Pradeepa R, Unnikrishnan R, Tiwaskar M, Aravind SR, Saboo B, Joshi SR, Mohan V.
New and unique clusters of type 2 diabetes identified in Indians.
J Assoc Physicians India. 2021 Feb 1;69(2):58-61.
developed by Madras Diabetes Research Foundation
Legal Information
Contact
If you have any questions or feedback regarding this tool, please contact us at: baskarv@mdrf.in
Author Information
Department of Data Science
Madras Diabetes Research Foundation
Plot No. 20, Golden Jubilee Biotech Park for Women Society,
SIPCOT - IT Park, Siruseri,
Chennai, Tamil Nadu 603103, India
Disclaimer
This tool is developed solely for research purposes to assist in classifying individuals with type 2 diabetes into specific clusters, based on published methodologies.
It is not intended to replace medical advice, diagnosis, or treatment. The results generated by this tool must be interpreted in conjunction with professional clinical evaluation and judgment.
By using this tool, you acknowledge and agree that:
- The outputs do not constitute medical advice or a diagnosis.
- No personal medical decisions should be made solely based on this tool.
- The authors, developers, and affiliated institutions are not liable for any direct or indirect damages resulting from the use or misuse of this tool or the data provided within.
Important Note
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