# Assessing Renal Function in Chronic Kidney Disease: A Comparative Evaluation of Glomerular Filtration Rate Prediction Equations in the North-Central Region of Nigeria

## TL;DR

This study compares different equations for estimating kidney function in Nigerian patients with chronic kidney disease and finds them to be accurate when compared to a 24-hour urine test.

## Contribution

The study evaluates the performance of GFR prediction equations in a Nigerian CKD population and identifies the Cockcroft-Gault equation as the most precise.

## Key findings

- All three GFR equations (CG, MDRD, CKD-EPI) showed strong correlation with measured creatinine clearance.
- The Cockcroft-Gault equation had the least bias and highest precision in patients with GFR below 45 mL/min.
- Albuminuria was significantly associated with all GFR equations, and age correlated with CrCl and GFR estimates.

## Abstract

Background: The glomerular filtration rate (GFR) is considered the gold standard for assessing renal function. According to the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines, GFR estimation is often carried out using predictive equations that incorporate serum creatinine levels, along with demographic factors such as age, gender, race, and body size. However, these equations exhibit varying levels of accuracy across different populations, necessitating the evaluation of their performance and clinical relevance in diverse patient groups.

Objectives: This study aimed to evaluate the performance of three commonly used GFR estimation equations, the Cockcroft-Gault (CG), Modification of Diet in Renal Disease (MDRD), and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations, along with their race-modified versions, by comparing them with measured 24-hour creatinine clearance (CrCl) in adult patients with chronic kidney disease (CKD).

Methods: A cross-sectional descriptive study was conducted at Jos University Teaching Hospital (JUTH) between November 2019 and July 2020, involving 111 consecutively recruited CKD patients. Data collection included medical history, physical examination, laboratory investigations, calculation of CrCl, estimated glomerular filtration rate (eGFR) using different equations, and albumin-creatinine ratio (ACR). Statistical analysis was performed using SPSS version 20 (IBM Inc., Armonk, New York), with p-values <0.05 considered statistically significant.

Results: The mean age of participants was 51.1±15.5 years. Diabetes mellitus was the most common cause of CKD, affecting 38% of the cohort. Among participants, 31% and 22% were classified as having stage 5 and stage 4 CKD, respectively. The median CrCl was 26 (9-56) mL/min. The median eGFR values across the equations were as follows: CG, 26 (11-60) mL/min/1.73m²; MDRD, 26 (11-60) mL/min/1.73m²; MDRD1, 22 (9-50) mL/min/1.73m²; CKD-EPI, 26 (10-62) mL/min/1.73m²; and CKD-EPI1, 22 (9-53) mL/min/1.73m². Strong positive correlations were observed between measured CrCl and the estimated GFR from each equation: CG (r=0.948, p=0.001), MDRD (r=0.940, p=0.001), MDRD1 (r=0.939, p=0.001), CKD-EPI (r=0.943, p=0.001), and CKD-EPI1 (r=0.942, p=0.001). Furthermore, significant correlations were found between the different GFR equations themselves, with the highest correlation observed between MDRD and CKD-EPI (r=0.999, p=0.001). The median ACR was 395.5 (45.3-2887.0) mg/g, and albuminuria was present in 82% of participants. All three GFR equations closely approximated the measured CrCl of 26 mL/min/1.73m². The equations performed optimally in patients with GFR values below 45 mL/min, with the CG equation exhibiting the least bias and the highest precision. Regression analysis revealed a significant association between albuminuria and all GFR equations and a notable association between age and CrCl, CG, and CKD-EPI estimates.

Conclusion: The CG, MDRD, and CKD-EPI equations demonstrated comparable accuracy to measured 24-hour CrCl in estimating GFR in Nigerian patients with CKD. These findings support the clinical use of these predictive equations for renal function assessment in CKD, though local validation in diverse populations is recommended for optimal clinical application.