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Activity Number: 360 - Contributed Poster Presentations: Section on Bayesian Statistical Science
Type: Contributed
Date/Time: Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
Sponsor: International Society for Bayesian Analysis (ISBA)
Abstract #314424
Title: A Bayesian Estimation of Occurrence of Chronic Kidney Disease Using Urinalysis Test Data in Lagos, Nigeria
Author(s): Obafemi Adegoke Keshinro*
Companies: University of Lagos, Nigeria
Keywords: Bayes’ Theorem; Conditional Probabilities; Sensitivity; Specificity; Predictive Values
Abstract:

The Kidney is a vital organ in our body system, it performs many crucial functions including: maintaining overall fluid balance, regulating and filtering minerals from blood, filtering waste materials from food, medications and toxic substances, etc. The kidney has a type of disease that may affect its functions over a period of months or years, this is referred to as Chronic Kidney Disease (CKD). The most common causes of CKD as at 2015 are diabetes mellitus, hypertension and glomerulonephritis. Among patients with possible kidney related problems in selected General Hospitals in Lagos, random selection of the urinalysis tests of patients are to be considered for this study. Under different categories and stages of CKD, Bayes’ theorem will be used to update prior believe about these patients that visited a nephrology clinic of being nephrotic. The theorem would equally be used to compute probabilities of prevalence, sensitivity, specificity and predictive values for occurrence of CKD under different categories and stages. The results is expected to reveal whether CKD is more prevalent in female than male counterpart as well as among the working population. Recommendations would be made on what can be done on the parts of the government and the stakeholders in the health sector to create better awareness on kidney health and CKD.


Authors who are presenting talks have a * after their name.

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