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Biological age for chronic kidney disease patients using index model
The estimation of biological age (BA) is an important asymptomatic measure that can be used to understand the physical changes and the aging process of a living being. Factors that contribute towards profiling the human biological age can be diverse. Therefore, this study focuses on developing a BA...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351620/ https://www.ncbi.nlm.nih.gov/pubmed/35935256 http://dx.doi.org/10.7717/peerj.13694 |
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author | Abu Bakar, Shaiful Anuar Syed Mohamed Shahruddin, Sharifah Nazatul Shima Ismail, Noriszura Wan Md Adnan, Wan Ahmad Hafiz |
author_facet | Abu Bakar, Shaiful Anuar Syed Mohamed Shahruddin, Sharifah Nazatul Shima Ismail, Noriszura Wan Md Adnan, Wan Ahmad Hafiz |
author_sort | Abu Bakar, Shaiful Anuar |
collection | PubMed |
description | The estimation of biological age (BA) is an important asymptomatic measure that can be used to understand the physical changes and the aging process of a living being. Factors that contribute towards profiling the human biological age can be diverse. Therefore, this study focuses on developing a BA model for patients with Chronic Kidney Disease (CKD). The procedure commences with the selection of significant biomarkers using a correlation test. Appropriate weighting is then assigned to each selected biomarker using the indexing method to produce a BA index. The BA index is matched to the age variation within the sample to acquire additional terms for the chronological age leading ultimately to the estimated BA. From a sample of 190 patients (133 trained data and 57 testing data) obtained from the University of Malaya Medical Centre (UMMC), Malaysia, the intensity of the BA is found to be between three to nine years from the chronological age. Visual observations further validate the high similarities between the training and testing data sets. |
format | Online Article Text |
id | pubmed-9351620 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93516202022-08-05 Biological age for chronic kidney disease patients using index model Abu Bakar, Shaiful Anuar Syed Mohamed Shahruddin, Sharifah Nazatul Shima Ismail, Noriszura Wan Md Adnan, Wan Ahmad Hafiz PeerJ Global Health The estimation of biological age (BA) is an important asymptomatic measure that can be used to understand the physical changes and the aging process of a living being. Factors that contribute towards profiling the human biological age can be diverse. Therefore, this study focuses on developing a BA model for patients with Chronic Kidney Disease (CKD). The procedure commences with the selection of significant biomarkers using a correlation test. Appropriate weighting is then assigned to each selected biomarker using the indexing method to produce a BA index. The BA index is matched to the age variation within the sample to acquire additional terms for the chronological age leading ultimately to the estimated BA. From a sample of 190 patients (133 trained data and 57 testing data) obtained from the University of Malaya Medical Centre (UMMC), Malaysia, the intensity of the BA is found to be between three to nine years from the chronological age. Visual observations further validate the high similarities between the training and testing data sets. PeerJ Inc. 2022-08-01 /pmc/articles/PMC9351620/ /pubmed/35935256 http://dx.doi.org/10.7717/peerj.13694 Text en © 2022 Abu Bakar et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Global Health Abu Bakar, Shaiful Anuar Syed Mohamed Shahruddin, Sharifah Nazatul Shima Ismail, Noriszura Wan Md Adnan, Wan Ahmad Hafiz Biological age for chronic kidney disease patients using index model |
title | Biological age for chronic kidney disease patients using index model |
title_full | Biological age for chronic kidney disease patients using index model |
title_fullStr | Biological age for chronic kidney disease patients using index model |
title_full_unstemmed | Biological age for chronic kidney disease patients using index model |
title_short | Biological age for chronic kidney disease patients using index model |
title_sort | biological age for chronic kidney disease patients using index model |
topic | Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351620/ https://www.ncbi.nlm.nih.gov/pubmed/35935256 http://dx.doi.org/10.7717/peerj.13694 |
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