Evaluation of risk stratification for acute kidney injury: a comparative analysis of EKFC, 2009 and 2021 CKD-EPI glomerular filtration estimating equations

Abstract

Background The adoption of the 2021 CKD-EPIcr equation for glomerular filtration rate (GFR) estimation provided a race-free eGFR calculation. However, the discriminative performance for AKI risk has been rarely validated. We aimed to evaluate the differences in acute kidney injury (AKI) prediction or reclassification power according to the three eGFR equations. Methods We performed a retrospective observational study within a tertiary hospital from 2011 to 2021. Acute kidney injury was defined according to KDIGO serum creatinine criteria. Glomerular filtration rate estimates were calculated by three GFR estimating equations: 2009 and 2021 CKD-EPIcr, and EKFC. In three equations, AKI prediction performance was evaluated with area under receiver operator curves (AUROC) and reclassification power was evaluated with net reclassification improvement analysis. Results A total of 187,139 individuals, including 27,447 (14.7%) AKI and 159,692 (85.3%) controls, were enrolled. In the multivariable regression prediction model, the 2009 CKD-EPIcr model (continuous eGFR model 2, 0.7583 [0.755–0.7617]) showed superior performance in AKI prediction to the 2021 CKD-EPIcr (0.7564 [0.7531–0.7597], < 0.001) or EKFC model in AUROC (0.7577 [0.7543–0.761], < 0.001). Moreover, in reclassification of AKI, the 2021 CKD-EPIcr and EKFC models showed a worse classification performance than the 2009 CKD-EPIcr model. (− 7.24 [− 8.21–− 6.21], − 2.38 [− 2.72–− 1.97]). Conclusion Regarding AKI risk stratification, the 2009 CKD-EPIcr equation showed better discriminative performance compared to the 2021 CKD-EPIcr equation in the study population. Graphical abstract

Comparative Analysis of Seven Equations for Estimated Glomerular Filtration Rate and Their Impact on Chronic Kidney Disease Categorization in Korean Patients at Local Clinics and Hospitals

“…The 2006 MDRD equation showed the lowest correlation coefficient with age in this study, aligning with previous studies conducted in healthy subjects [23]. The ranking from the highest to the lowest of the median (or mean) eGFR levels calculated from each equation is consistent with prior findings reported in the Korean population under various clinical settings, in other ethnic groups (non-black individuals) and in the Korea National Health and Nutrition Examination Survey 2019 data [5,11,13,[22][23][24][25][26][27]. Notably, the 2006 MDRD and 2021 EKFC equations yielded the lowest eGFR levels compared to the other equations, potentially leading to an underestimation of CKD grades in the Korean adult population [13,[22][23][24][25][26][27].…”

“…Although the eGFR levels calculated from the 2009 CKD-EPI Cr and 2021 CKD-EPI Cr equations appear comparable (Figure 3j), the agreement in CKD categories shows a higher proportion of underestimation compared to the 2009 CKD-EPI Cr equation. These findings align with previous recommendations regarding the cautious use of newly developed equations in Korean subjects, as the 2009 CKD-EPI Cr and 2012 CKD-EPI Cr & Cys-C equations demonstrated better performance in the Korean population [3,13,25]. This suggests that, while quantitative eGFR level differences were observed, the clinical impact on qualitative CKD categorization may differ from the impact on the quantitative levels [9,13,29].…”

“…A key strength of this study is its inclusion of a large cohort of adult Korean individuals from local clinics and hospitals across Korea, alongside the utilization of multiple equations for eGFR comparison [13,[22][23][24][25][26][27]. In this study, we confirm previous findings showing that eGFR decreases with age and that the proportion of decreased eGFR increases with age, underscoring the need for age-specific thresholds for CKD [2,13,[22][23][24][25][26][27]. The 2006 MDRD equation showed the lowest correlation coefficient with age in this study, aligning with previous studies conducted in healthy subjects [23].…”