Correlation Between Red Cell Distribution Width (RDW) and Chronic Kidney Disease Patients in Semarang, Indonesia

Background: Chronic Kidney Disease (CKD) describes abnormal structural and functional kidney conditions that mark a decrease in GFR. Erythropoietin producing peritubular cells are partially or completely damaged by the severity of kidney disease, causing inadequate erythropoiesis and anemia. Anemia is one of the factors causing erythrocyte size variations assessed by the red cell distribution width (RDW). The relationship between GFR kidney function and RDW is currently little studied, this encourages researchers to conduct a study of the correlation between GFR and RDW in patients with chronic kidney disease. Methods: Retrospective observational analytic study with cross sectional approach was conducted in 45 chronic kidney disease patients in RSUP dr. Kariadi Semarang in December 2018-January 2019. Data include age, weight, urea and creatinine serum, and RDW. Calculation of GFR values using the Cockroft Gault formula. Statistical tests using Spearman’s correlation, p 0.05 were considered significant. Results: The median (minimum-maimum) GFR and RDW are respectively 20 (6-35) mL/min /1.73 m2; 15.7 (12.8-20.6)%. The correlation test of GFR with RDW is r = -0.468 with p=0.001. Ureum, creatinine and RDW have significant different in chronic kidney disease between stadium 3, 4, and 5 (p=0.001). Conclusion: There is a moderate negative correlation between GFR and RDW in patients with chronic kidney disease. Red cell Distribution Width (RDW) can be used as a alternative parameter to evaluate declining of kidney function in patients with chronic kidney disease stage 3-5.

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Publication Details

Journal
Medicina Moderna - Modern Medicine
Published
2024-12-31
DOI
https://doi.org/10.31689/rmm.2024.31.4.345
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
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article
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article

Correlation Between Red Cell Distribution Width (RDW) and Chronic Kidney Disease Patients in Semarang, Indonesia

Devi Elvina Rachma, Agustina Ari Murti Budi Hastuti, Edward Kurnia Setiawan Limijadi
Medicina Moderna - Modern Medicine
Inflammatory Biomarkers in Disease Prognosis
article

Correlation Between Red Cell Distribution Width (RDW) and Chronic Kidney Disease Patients in Semarang, Indonesia

Devi Elvina Rachma, Agustina Ari Murti Budi Hastuti, Edward Kurnia Setiawan Limijadi
article en

Abstract

Background: Chronic Kidney Disease (CKD) describes abnormal structural and functional kidney conditions that mark a decrease in GFR. Erythropoietin producing peritubular cells are partially or completely damaged by the severity of kidney disease, causing inadequate erythropoiesis and anemia. Anemia is one of the factors causing erythrocyte size variations assessed by the red cell distribution width (RDW). The relationship between GFR kidney function and RDW is currently little studied, this encourages researchers to conduct a study of the correlation between GFR and RDW in patients with chronic kidney disease. Methods: Retrospective observational analytic study with cross sectional approach was conducted in 45 chronic kidney disease patients in RSUP dr. Kariadi Semarang in December 2018-January 2019. Data include age, weight, urea and creatinine serum, and RDW. Calculation of GFR values using the Cockroft Gault formula. Statistical tests using Spearman’s correlation, p 0.05 were considered significant. Results: The median (minimum-maimum) GFR and RDW are respectively 20 (6-35) mL/min /1.73 m2; 15.7 (12.8-20.6)%. The correlation test of GFR with RDW is r = -0.468 with p=0.001. Ureum, creatinine and RDW have significant different in chronic kidney disease between stadium 3, 4, and 5 (p=0.001). Conclusion: There is a moderate negative correlation between GFR and RDW in patients with chronic kidney disease. Red cell Distribution Width (RDW) can be used as a alternative parameter to evaluate declining of kidney function in patients with chronic kidney disease stage 3-5.

Medicina Moderna - Modern MedicineVol. 31(4)
Openalex Percentile: Top 58%
Inflammatory Biomarkers in Disease Prognosis
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