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Biological age for chronic kidney disease patients using index model
Shaiful Anuar Abu Bakar1, Sharifah Nazatul Shima Syed Mohamed Shahruddin1, Noriszura Ismail2
1Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia.
Peerj
|August 8, 2022
Summary
This study developed a biological age (BA) model for Chronic Kidney Disease (CKD) patients, finding BA is 3-9 years different from chronological age. This aging biomarker model aids in understanding disease progression.
Area of Science:
- Biomedical Science
- Gerontology
- Nephrology
Background:
- Biological age (BA) estimation offers insights into aging and physical changes.
- Diverse factors influence human biological age.
- Chronic Kidney Disease (CKD) impacts aging processes.
Purpose of the Study:
- To develop a novel biological age model specifically for patients with Chronic Kidney Disease (CKD).
- To identify significant biomarkers and their weighting for accurate BA estimation in CKD.
Main Methods:
- Biomarker selection via correlation tests.
- Weighting biomarkers using an indexing method to create a BA index.
- Matching BA index with chronological age variations to estimate BA.
Main Results:
- The developed BA model for CKD patients showed biological age intensity between 3 to 9 years from chronological age.
- High similarity was observed between training and testing datasets, validating the model.
- Data was sourced from 190 patients at the University of Malaya Medical Centre (UMMC).
Conclusions:
- The study successfully established a BA estimation model for CKD patients.
- The model provides a quantitative measure of aging in CKD, potentially aiding clinical assessment.
- Further research can explore the clinical utility of this BA model in managing CKD.
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