RESUMEN
Abstract Introduction: GFR is estimated by using creatinine and cystatin C to determine renal dysfunction. Our aim was to evaluate estimated GFR (eGFR) based on cystatin C in type 2 diabetic patients with diabetic nephropathy (DN). Methods: Study group included 52 controls (46% male, age: 54.5±12.4) and 101 diabetic patients (46.5% male, age: 58.2±11). The diabetics were divided into three subgroups according to 24-hour urine albumin: normal to mildly increased (A1) (n=51), moderately increased (A2) (n=25), severely increased (A3) (n=25) albuminuria. Creatinine clearance (CrCl) was determined. Correlations between CrCl and eGFRs estimated according to the CKD-EPI, MDRD, and Cockcroft-Gault (CG) formulas, and ROC curves were evaluated. Data were analyzed using SPSS 22.0. Results: Only CKD-EPI-cys eGFR was significantly lower in the A1 group than the controls (p=0.021). All GFRs were lower in the A3 group than the control (CKD-EPI-cr, MDRD, CKD-EPI-cys, CKD-EPI-cr-cys: p=0.0001, CG and CrCl: p=0.001) and A1 (for all GFRs p=0.0001) groups. CKD-EPI-cr (p=0.004), MDRD (p=0.01), CG (p=0.037), CKD-EPI-cys (p=0.033), and CKD-EPI-cr-cys (p=0.016) eGFRs in the A2 group were significantly different from the A1 group. All eGFRs showed a moderate correlation with CrCl in the A1group (CKD-EPI-cr and CKD-EPI-cr-cys: r=0.49, p=0.0001, MDRD: r=0.44, p=0.001, CG r=0.48, p=0.0001: CKD-EPI-cys r=0.40, p=0.004). The area under the CKD-EPI-cys ROC curve was the highest and found to be 0.847 (95%CI 0.763-0.931, p=0.0001). Conclusions: Our results showed that the CKD-EPI-cys eGFR can be useful in detecting the early stage of DN and more predictive than the others for prediction of DN.
Resumo Introdução: A TFG é estimada usando creatinina e cistatina C para determinar a disfunção renal. Nosso objetivo foi avaliar a TFG estimada (TFGe) com base na cistatina C em pacientes com diabetes do tipo 2 com nefropatia diabética (ND). Métodos: O grupo de estudo incluiu 52 controles (46% homens, idade: 54,5±12,4) e 101 pacientes diabéticos (46,5% homens, idade: 58,2±11). Os diabéticos foram divididos em três subgrupos de acordo com a albumina na urina de 24 horas: albuminúria normal a levemente aumentada (A1) (n=51), moderadamente aumentada (A2) (n=25) e severamente aumentada (A3) (n=25). Foi determinado o clearance de creatinina (Clcr). As correlações entre Clcr e TFGe calculadas de acordo com as fórmulas CKD-EPI, MDRD, e Cockcroft-Gault (CG), e as curvas ROC foram avaliadas. Os dados foram analisados usando o SPSS 22.0. Resultados: Somente a TFGe CKD-EPI-cis foi significativamente menor no grupo A1 do que nos controles (p=0,021). Todas as TFGs foram mais baixas no grupo A3 do que no grupo controle (CKD-EPI-cr, MDRD, CKD-EPI-cis, CKD-EPI-cr-cis: p=0,0001, CG e Clcr: p=0,001) e no grupo A1 (para todas as TFGs p=0,0001). As TFGes CKD-EPI-cr (p=0,004), MDRD (p=0,01), CG (p=0,037), CKD-EPI-cis (p=0,033), e CKD-EPI-cr-cis (p=0,016) no grupo A2 foram significativamente diferentes do grupo A1. Todas as TFGes mostraram uma correlação moderada com Clcr no grupo A1 (CKD-EPI-cr e CKD-EPI-cr-cis: r=0,49, p=0,0001, MDRD: r=0,44, p=0,001, CG r=0,48, p=0,0001: CKD-EPI-cis r=0,40, p=0,004). A área sob a curva ROC CKD-EPI-cis foi a mais alta e foi considerada 0,847 (95%IC 0,763-0,931, p=0,0001). Conclusões: Nossos resultados mostraram que a TFGe CKD-EPI-cis pode ser útil na detecção do estágio inicial de ND e com maior valor de predição do que as outras para a predição da ND.
Asunto(s)
Humanos , Masculino , Femenino , Adulto , Persona de Mediana Edad , Anciano , Diabetes Mellitus , Nefropatías Diabéticas , Insuficiencia Renal Crónica , Creatinina , Cistatina C , Tasa de Filtración GlomerularRESUMEN
INTRODUCTION: GFR is estimated by using creatinine and cystatin C to determine renal dysfunction. Our aim was to evaluate estimated GFR (eGFR) based on cystatin C in type 2 diabetic patients with diabetic nephropathy (DN). METHODS: Study group included 52 controls (46% male, age: 54.5±12.4) and 101 diabetic patients (46.5% male, age: 58.2±11). The diabetics were divided into three subgroups according to 24-hour urine albumin: normal to mildly increased (A1) (n=51), moderately increased (A2) (n=25), severely increased (A3) (n=25) albuminuria. Creatinine clearance (CrCl) was determined. Correlations between CrCl and eGFRs estimated according to the CKD-EPI, MDRD, and Cockcroft-Gault (CG) formulas, and ROC curves were evaluated. Data were analyzed using SPSS 22.0. RESULTS: Only CKD-EPI-cys eGFR was significantly lower in the A1 group than the controls (p=0.021). All GFRs were lower in the A3 group than the control (CKD-EPI-cr, MDRD, CKD-EPI-cys, CKD-EPI-cr-cys: p=0.0001, CG and CrCl: p=0.001) and A1 (for all GFRs p=0.0001) groups. CKD-EPI-cr (p=0.004), MDRD (p=0.01), CG (p=0.037), CKD-EPI-cys (p=0.033), and CKD-EPI-cr-cys (p=0.016) eGFRs in the A2 group were significantly different from the A1 group. All eGFRs showed a moderate correlation with CrCl in the A1group (CKD-EPI-cr and CKD-EPI-cr-cys: r=0.49, p=0.0001, MDRD: r=0.44, p=0.001, CG r=0.48, p=0.0001: CKD-EPI-cys r=0.40, p=0.004). The area under the CKD-EPI-cys ROC curve was the highest and found to be 0.847 (95%CI 0.763-0.931, p=0.0001). CONCLUSIONS: Our results showed that the CKD-EPI-cys eGFR can be useful in detecting the early stage of DN and more predictive than the others for prediction of DN.