Study of Serum Uric Acid in Different Stages of Chronic Kidney Disease
Shahida Akhter, A. S. M. Rizwan
Journal of Advances in Medicine and Medical Research · pp. 70–79 · Published 23 Mar 2021
10.9734/jammr/2021/v33i630862Abstract
Background: Hyperuricaemia is a metabolic marker of decreased renal function in chronic kidney disease (CKD). It increases cardiovascular, cerebrovascular and mortality risk in patients with CKD. Objectives: To estimate serum uric acid level in different stages of CKD. Methods: The present study was a cross sectional analytical study and was conducted in the Department of Physiology, Dhaka Medical College, Dhaka from July 2012 to June 2013 on 300 participants. They were divided into group A (150 control healthy participants) and group B (150 diagnosed cases of CKD). Serum creatinine and serum uric acid levels were measured by auto analyzer in Department of Pathology, Dhaka Medical College. Estimated glomerular filtration rate (eGFR) was calculated from serum creatinine level by Modification of Diet in Renal Disease (MDRD) equation. For statistical analysis unpaired Student “t” test, one way ANOVA test, Bonferroni test, Pearson’s correlation coefficient (r) test and Linear regression were performed using SPSS for windows version 20. Result: In this study, serum uric acid level was significantly (p<0.05) higher and eGFR were significantly lower in study groups than that of control group. There was gradual rise of serum uric acid level in CKD subjects from stage I to V. A significant inverse correlation was observed between serum uric acid level and eGFR. Serum uric acid level increased 0.048 mg/dl for each ml/min/1.73m2 decrease of eGFR. Conclusion: This study concludes that serum uric acid level increases gradually in accordance with the higher stages of CKD. There is a negative correlation of serum uric acid with eGFR in all stages of CKD which was statistically significant (p<0.05). Screening of serum uric acid level in different stages of CKD may be beneficial for assessing renal damage as well as prediction of co-morbidities associated with it.
Cited by 3
Fazlul Haque, Md. Samiul Islam, Nafsoon Rahman · iLABMED · 2026
Danilo Lemes Naves Gonçalves, Tiago Ricardo Moreira, Luciana Saraiva da Silva · Scientific Reports · 2022
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