Assessing the Prediction Power of Plasma Neutrophil Gelatinase-Associated Lipocalin and Serum Cystatin C for Diagnosis Kidney Damage

Background & Objective: Chronic Kidney Disease (CKD) has been recognized as a serious public health threat. The early detection of kidney damage in CKD is a useful way to reduce the disease burden. This study aimed to determine the power of Neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C (Cys-C) to predict the kidney damage in Iranian patients. Materials & Methods: This study was conducted at Shohadaye Tajrish Hospital on 72 renal patients. The estimated glomerular filtration rate (GFR) was assumed as the gold standard method. The NGAL and Cys-C were used as predictors and estimated GFR was used as a response variable. Three logistic regression models were fitted to investigate the impact of single and multiple markers for the prediction of GFR status. Results: The regression models with NGAL and Cys-C as single predictors, and with both of them as multivariate predictors, were fitted to the data. The markers except for Cys-C were significantly related to the renal damage in all models (P<0.05). The obtained odds ratio for the model with NGAL, Cys-Cand both NGAL and Cys-C were 1.142, 1.004 and 1.125, respectively. The sensitivity and specificity of the models with NGAL, Cys-C and both of them were 96.00 and 100.00; 64.00 and 97.87; and 96.00 and 100, respectively.  Conclusion: Our findings revealed that the NGAL biomarker as a single predictor could result in high predictor power for classifying the patients with and without kidney damage. Thus, the clinicians can use this marker for the early prediction of this renal problem.

Assessing the Prediction Power of Plasma Neutrophil Gelatinase-Associated Lipocalin and Serum Cystatin C for Diagnosis Kidney Damage Keywords:

Kidney damage , NGAL , Cystatin C , AUC , Iranian population