Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly

Chronic kidney disease (CKD) is a significant public health problem with increasing incidence and prevalence worldwide. This trend is also observed in Malaysia, where the prevalence of CKD was 9.07% in 2011. CKD progression is associated with specific metabolic and diagnostic parameters important in...

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Main Author: Khan, Irfanullah
Format: Thesis
Language:en
Published: 2023
Subjects:
Online Access:http://eprints.usm.my/60244/1/IRFANULLAH%20KHAN%20-%20TESIS%20cut.pdf
http://eprints.usm.my/60244/
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author Khan, Irfanullah
author_facet Khan, Irfanullah
author_sort Khan, Irfanullah
building Hamzah Sendut Library
collection Institutional Repository
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
continent Asia
country Malaysia
description Chronic kidney disease (CKD) is a significant public health problem with increasing incidence and prevalence worldwide. This trend is also observed in Malaysia, where the prevalence of CKD was 9.07% in 2011. CKD progression is associated with specific metabolic and diagnostic parameters important in the disease's progression. CKD patients frequently experience depression, which can further impact their well-being. A prognostic disease progression model was developed for CKD patients to understand the variations among individuals about metabolic and diagnostic parameters, encompassing all relevant factors. The study consisted of a retrospective analysis of 470 CKD patients selected from the Hospital Universiti Sains Malaysia (USM) clinic and a cross-sectional evaluation of 300 patients from outpatient department clinics using the Beck Depression Inventory questionnaire to assess depression. Computational statistical modeling approaches were utilized to evaluate CKD patients' sociodemographic, metabolic, and diagnostic characteristics. The hazard ratio was tested and implemented using the R-Studio software and syntax, which was also used to design and develop the hybrid biometry approach. The advanced methodology was carried out in three stages: developing syntax for R for the hybrid biometry method, which consists of multiple layer perceptrons (MLP), logistic regression, and data bootstrapping.
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language en
publishDate 2023
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spelling my.usm.eprints.60244 http://eprints.usm.my/60244/ Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly Khan, Irfanullah RS1-441 Pharmacy and materia medica Chronic kidney disease (CKD) is a significant public health problem with increasing incidence and prevalence worldwide. This trend is also observed in Malaysia, where the prevalence of CKD was 9.07% in 2011. CKD progression is associated with specific metabolic and diagnostic parameters important in the disease's progression. CKD patients frequently experience depression, which can further impact their well-being. A prognostic disease progression model was developed for CKD patients to understand the variations among individuals about metabolic and diagnostic parameters, encompassing all relevant factors. The study consisted of a retrospective analysis of 470 CKD patients selected from the Hospital Universiti Sains Malaysia (USM) clinic and a cross-sectional evaluation of 300 patients from outpatient department clinics using the Beck Depression Inventory questionnaire to assess depression. Computational statistical modeling approaches were utilized to evaluate CKD patients' sociodemographic, metabolic, and diagnostic characteristics. The hazard ratio was tested and implemented using the R-Studio software and syntax, which was also used to design and develop the hybrid biometry approach. The advanced methodology was carried out in three stages: developing syntax for R for the hybrid biometry method, which consists of multiple layer perceptrons (MLP), logistic regression, and data bootstrapping. 2023-07 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/60244/1/IRFANULLAH%20KHAN%20-%20TESIS%20cut.pdf Khan, Irfanullah (2023) Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly. PhD thesis, Universiti Sains Malaysia.
spellingShingle RS1-441 Pharmacy and materia medica
Khan, Irfanullah
Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly
title Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly
title_full Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly
title_fullStr Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly
title_full_unstemmed Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly
title_short Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly
title_sort developing the prognostic model of chronic kidney disease progression and elucidating the global prevalence of chronic kidney disease depression among elderly
topic RS1-441 Pharmacy and materia medica
url http://eprints.usm.my/60244/1/IRFANULLAH%20KHAN%20-%20TESIS%20cut.pdf
http://eprints.usm.my/60244/
url_provider http://eprints.usm.my/