RESUMO
Background. Precise estimation of the glomerular filtration rate (GFR) and the identification of markers of progression are important. We compared creatinine, cystatin, and combined CKD-EPI equations with (99m)Tc-DTPA scintigraphy to measure GFR and proteinuria as markers of progression. Methods. Cross-sectional, observational study including 300 subjects. CKD was classified by (99m)Tc-DTPA scintigraphy. Determinations. Creatinine, 24-hour creatinine clearance, cystatin, Hoek formula, and creatinine, cystatin, and combined CKD-EPI equations. Results. In the global assessment, creatinine CKD-EPI and combined CKD-EPI equations yielded the highest correlations with (99m)Tc-DTPA: ρ = 0.839, P < 0.0001 and ρ = 0.831, P < 0.0001. Intergroup analysis versus (99m)Tc-DTPA: control G, creatinine clearance ρ = 0.414, P = 0.013; G3, combined CKD-EPI ρ = 0.5317, P < 0.0001; G4, Hoek ρ = 0.618, P < 0.0001, combined CKD-EPI ρ = 0.4638, P < 0.0001; and G5, creatinine clearance ρ = 0.5414, P < 0.0001, combined CKD-EPI ρ = 0.5288, P < 0.0001. In the global assessment, proteinuria displayed the highest significant correlations with cystatin ( ρ = 0.5433, P < 0.0001) and cystatin-based equations (Hoek: ρ = -0.5309, P < 0.0001). When GFR < 60 mL/min: in stage 3, proteinuria-cystatin ( ρ = 0.4341, P < 0.0001); proteinuria-Hoek ( ρ = -0.4105, P < 0.0001); in stage 4, proteinuria-cystatin ( ρ = 0.4877, P < 0.0001); proteinuria-Hoek ( ρ = -0.4877, P = 0.0026). Conclusions. At every stage of GFR < 60 mL/min, cystatin-based equations displayed better correlations with (99m)Tc-DTPA. Proteinuria and cystatin-based equations showed strong associations and high degrees of correlation.
RESUMO
BACKGROUND: In chronic kidney disease (CKD), accurate estimation of the glomerular filtration rate (GFR) is mandatory. Gold standard methods for its estimation are expensive and time-consuming. We compared creatinine- versus cystatin C-based equations to measure GFR, employing (99m)Tc-DTPA scintigraphy as the gold standard. METHODS: This was a prospective cross-sectional observational study including 300 subjects. CKD was defined according to K/DOQI guidelines, and patients were separated into groups: stage 1 (G1), n=26; stage 2 (G2), n=52; stage 3 (G3), n=90; stage 4 (G4), n=37; stage 5 (G5), n=60; and control group, n=35. Creatinine-based estimates were from 24-hour creatinine clearance using the Walser formula, Cockcroft-Gault, MDRD-4 and CKD-EPI; cystatin C equations used were Larsson, Larsson modified equation, Grubb and Hoek. RESULTS: Age and body mass index were different among groups; proteinuria, hypertension, diabetes and primary glomerulopathies significantly increased as CKD worsened. In the global assessment, CKD-EPI and Hoek gave the highest correlations with (99m)Tc-DTPA: rho=0.826, p<0.001 and rho=0.704, p<0.001, respectively. Most significant linear regressions obtained: CKD-EPI vs. (99m)Tc-DTPA, Hoek vs. (99m)Tc-DTPA and CKD-EPI vs. Hoek. However, important differences emerged when each group was analyzed separately. Best significant correlations obtained with (99m)Tc-DTPA: control group, creatinine clearance rho=0.421, p=0.012; G1, Crockoft-Gault rho=0.588, p=0.003; G2, CKD-EPI rho=0.462, p<0.05; G3, CKD-EPI rho=0.508, p<0.001; G4, Hoek rho=0.618, p<0.001; G5, CKD-EPI rho=0.604, p<0.001. CONCLUSIONS: At GFR <60 ml/min, CKD-EPI and Hoek equations appeared to best correlate with (99m)TcDTPA. In controls and at early stages of CKD, creatinine-based equations correlated better with (99m)Tc-DTPA, with CKD-EPI being the one with the best degree of agreement.