Assessment of Albuminuria, Estimated-Glomerular Filtration Rate And Uric Acid As Markers For Chronic Kidney Disease among Family Members of Sudanese Renal Failure Patients On Hemodialysis
Background: Chronic kidney disease (CKD) is a global public health problem that increased rapidly throughout the world, and it was recommended that it should be discovered earlier especially among high risk population.
Objective: To assess albuminuria, estimated glomerular filtration rate (eGFR) and uric acid as markers for CKD among first degree relatives (FDRs) of hemodialysis patients.
Materials and methods: This is an analytical, case control study conducted at Khartoum state during May 2015 to May 2018, targeting 135 FDRs of end stage renal disease (ESRD) Sudanese patients on hemodialysis and other 161 healthy individuals serving as control group. Their plasma was prepared and analyzed for creatinine, uric acid, calcium, phosphate, and alkaline phosphatase. Also spot random urine sample was collected and analyzed for creatinine and micro albumin, from which albumin to creatinine ratio (ACR) was calculated. The plasma parameters were analyzed by Mendray BS 200 auto analyzer, while urine parameters were analyzed by using Cobas auto analyzer.
Results: The mean levels of ACR and urine micro albumin were significantly increased while the mean levels of e-GFR and urine creatinine were significantly reduced in FDRs when compared to control group (The means ± SD were: 10 ± 4.4, 123.1 ± 68.2, 93.1 ± 25.6 and153.3 ± 115.3 versus 0.92±0.10, 14.9±2.05, 99.4±22.5 and 190.3±108.8, the p values were: 0.024, 0.001, 0.027 and 0.005 respectively). But there were no significant differences between means levels of calcium, phosphorus, uric acid and alkaline phosphatase when compared in FDRs versus control group. The correlation analysis showed significant positive correlation of serum uric acid with serum creatinine(r= 0.587, P value = 0.000).
Conclusion: Albuminuria which was detected by ACR was significantly increased among FDRs of hemodialysis patients, while the eGFR was reduced, hence they are prone to develop CKD.
2. Sayanthooran S, Magana-Arachchi DN, Gunerathne L, Abeysekera T. Potential diagnostic biomarkers for chronic kidney disease of unknown etiology (CKDu) in Sri Lanka: a pilot study. BMC nephrology. 2017 Dec; 18(1):31.
3. Elsharif ME, Elsharif EG. Causes of end-stage renal disease in Sudan: a single-center experience. Saudi Journal of Kidney Diseases and Transplantation. 2011 Mar 1; 22(2):373.
4. Abu-Aisha H, Elhassan A, Khamis A, Abu-Elmaali A. Chronic kidney disease in police forces households in Khartoum, Sudan: pilot re-port. Arab Journal of Neph-rology and Transplantation. 2009;2(2):21-6.
5. Naicker S. End-stage renal disease in Sub-Saharan Afr-ica. Kidney International Sup-plements. 2013 May 1; 3(2):161-3.
6. Ma YC, Zuo L, Chen JH, Luo Q, Yu XQ, Li Y, Xu JS, Huang SM, Wang LN, Huang W, Wang M. Improved GFR estimation by combined creatinine and cystatin C measurements. Kidney inter-national. 2007 Dec 2; 72(12): 1535-42.
7. Jaar BG, Khatib R, Plantinga L, Boulware LE, Powe NR. Principles of screening for chronic kidney disease. Clinical Journal of the Amer-ican Society of Nephrology. 2008 Mar 1;3(2):601-9.
8. Guy M, Borzomato JK, Newall RG, Kalra PA, Price CP. Protein and albumin-to-creatinine ratios in random urines accurately predict 24 h protein and albumin loss in patients with kidney disease. Annals of clinical bioche-mistry. 2009 Nov; 46(6):468-76.
9. Swartz JE, Perry E, Joy S, and Swartz RD. Using Peer Mentors to screen for CKD at dialysis units: Targeting high‐risk family members. Dialysis & Transplantation. 2011 Jun; 40(6):246-51.
10. Satko SG, Freedman BI, Moossavi S. Genetic factors in end-stage renal disease. Kidney international. 2005 Apr 1; 67:S46-9.