Developing The Prognostic Model Of Chronic Kidney Disease Progression And Elucidating The Global Prevalence Of Chronic Kidney Disease Depression Among Elderly - Khan, Irfanullah (2023)
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.