Glomerular Filtration Rate by CKD-EPI Creatinine Cystatin C Equation for Diagnosis of Chronic Kidney Disease in Adults Compared with 99Tc-DTPA Scan
Year: 2025
Type: article
Study design: Observational Study
Abstract: Introduction: Kidney disease patients can have varying degrees of clinical presentation. Not all patients with kidney diseases show traditional symptoms, thus it is necessary to test renal functions to assess how well the kidneys are working. The utilization of CKD-EPI equations provides an easy and reproducible method to determine eGFR. According to the literature, CKD-EPI Cr-Cys C equations seem to be superior to all other equations, hence we evaluated the diagnostic accuracy of the aforementioned equation, and compared it with measured GFR by 99Tc-DTPA scan. Material and method: A cross-sectional study was conducted at two centers. The samples were collected at Atomic Energy Medical Center, Jinnah Postgraduate Medical Centre, Karachi, and then analyzed at the department of chemical pathology, PNS SHIFA Hospital Karachi. 122 patients were enrolled during a period of 9 months. The eGFR was calculated using the 2012 CKD-EPI Cr-Cys C equation. Serum Creatinine was measured by kinetic colorimetric assay whereas Serum Cystatin C was measured by Particle enhanced immunoturbidimetric assay (PENIA) method. GFR was measured by the Gates method using the 99Tc-DTPA renal scan method. Result: The CKD EPI Cr-CysC equation was found to have a sensitivity of 80%, specificity of 93.5%, a positive predictive value of 92%, a negative predictive value of 83%, and diagnostic accuracy of 87%. Effect modifiers like age, gender, and duration of disease were stratified. Conclusion: The diagnostic accuracy of the CKD EPI Cr-Cys C equation showed high comparability with measured GFR in the general population for the diagnosis of CKD. Thus, The CKD EPI Cr-Cys C equation is a good alternative marker to mGFR in patients being screened for CKD.
Authors: Saba Aman, Noorulain Fareed, Mustajab Mujtaba, Sanam Haneef, Qurratulain, Uzma Ansari
Language: English
Subfield: Nephrology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4414560212
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