COMPARISON OF ESTIMATED GLOMERULAR FILTRATION RATE IN MEXICAN KIDNEY TRANSPLANT RECIPIENTS: A COMPARATIVE ANALYSIS OF MDRD AND CKD-EPI EQUATIONS

Introduction:

Accurate assessment of GFR is critical in the post-transplant monitoring of kidney transplant recipients (KTR). While various studies have compared creatinine-based eGFR equations in KT patients, specific data for the Mexican population remains sparse. This study aims to compare the performance of the two most widely used creatinine-based eGFR equations: MDRD and CKD-EPI 2021 equation, in a cohort of Mexican KT recipients.

Methods:

We conducted a retrospective analysis of 401 KT recipients under follow-up during Jan 2023 to June 2024. Demographic data, serum creatinine levels, and eGFR (mL/min/1.73 m²) were collected. eGFR was calculated using both MDRD and CKD-EPI equations, with race classified as “not African-American.” Patients were categorized by CKD stage according to the eGFR values derived from both equations.

Results:

A total of 1,203 eGFR values were analyzed. The cohort had a mean age of 37.33 years (SD ± 10.59), with 68% being male. The mean time from transplantation to GFR evaluation was 10.43 years (± 6.43 years). The mean eGFR calculated using the MDRD equation was 61.78 ± 22.57 mL/min/1.73 m², while the CKD-EPI equation yielded a mean eGFR of 71.47 ± 24.52 mL/min/1.73 m². No significant differences were observed in eGFR values when analyzed by gender or age group. Correlation analysis revealed a low negative correlation between MDRD eGFR and gender (R=-0.21, p=0.038) and a strong positive correlation between the MDRD and CKD-EPI equations (R=0.975, p<0.01). On figure 1, the Bland-Altman plot demonstrated the agreement between the two eGFR equations, showing a bias with its 95% confidence interval, indicating that CKD-EPI tends to provide higher eGFR values compared to MDRD.

Conclusions:

While there is a strong correlation between MDRD and CKD-EPI equations in estimating GFR in Mexican KT recipients, the observed differences suggest that further validation is necessary. Specifically, we need to determine whether elevated creatinine levels reliably predict outcomes in this population or if other biomarkers should be prioritized to enhance the predictive power of eGFR in clinical practice.

I have no potential conflict of interest to disclose.

I did not use generative AI and AI-assisted technologies in the writing process.