Kidney function estimation equations: a narrative review
Document Type
Article
Publication Title
Irish Journal of Medical Science
Abstract
Glomerular filtration rate (GFR) as a marker of kidney function is important in health and disease management because decreased kidney function is associated with all-cause and cardiovascular mortality, progression of kidney disease, predisposition to acute kidney injury (AKI), and for drug dosage modification. While measured glomerular filtration rate (mGFR) is acknowledged as the most accurate method for evaluating kidney function, it is at present not feasible to be applied in the clinical arena. Estimated glomerular filtration rate (eGFR) is preferred due to its convenience, cost-effectiveness, and seamless integration into standard clinical practice for kidney function evaluation. The presence of multiple equations for eGFR with applications to differing populations makes their use challenging for clinicians. We reviewed available estimated glomerular filtration rate (GFR) equations and their application in different clinical settings both in normal and chronic kidney disease (CKD) patients. These formulae incorporate serum creatinine and/or serum cystatin C levels and correlate them with measured kidney function. Among the many available equations, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation is the most recommended due to its robustness and accuracy across diverse patient populations. Strengths and limitations of different eGFR equations are discussed emphasizing the importance of selecting the appropriate equation based on specific patient demographics and clinical scenarios. There is need for regional validation studies to ensure the global applicability of these equations, considering the variations in population characteristics.
First Page
725
Last Page
743
DOI
10.1007/s11845-025-03874-y
Publication Date
4-1-2025
Recommended Citation
Khader, Nisha Abdul; Kamath, Veena Ganesh; Kamath, Shobha Ullas; and Rao, Indu Ramachandra, "Kidney function estimation equations: a narrative review" (2025). Open Access archive. 13402.
https://impressions.manipal.edu/open-access-archive/13402