en ارزیابی قدرت پیش بینی نوتروفیل پلاسما و ژلاتیناز در ارتباط لیپوکلین و سرم سیستاتین C برای تشخیص آسیب کلیه Clinical Medicine Clinical Medicine مقاله پژوهشی Original Research Article <p style="text-align: justify;"><span style="font-family:times new roman;"><span style="font-size:14px;"><span style="color:#008080;"><strong>Background & Objective:</strong></span> 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.<br> <span style="color:#008080;"><strong>Materials & Methods:</strong></span> 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.<br> <span style="color:#008080;"><strong>Results: </strong></span>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 (<em>P<0.05</em>). 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.&nbsp;<br> <span style="color:#008080;"><strong>Conclusion: </strong></span>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.</span></span></p> Kidney damage, NGAL, Cystatin C, AUC, Iranian population 29 34 http://journal.zums.ac.ir/browse.php?a_code=A-10-4700-1&slc_lang=en&sid=1 Fatemeh Masaebi فاطمه مصائبی fatemeh.mb71@yahoo.com 5200319475328460047786 5200319475328460047786 No Dept. of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran Mehdi Azizimohammad Looha مهدی عزیزمحمدی لوها mehdi.looha@gmail.com 5200319475328460047787 5200319475328460047787 No Dept. of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran Malihe Nasiri ملیحه نصیری f_kazerouni@sbmu.ac.ir 5200319475328460047788 5200319475328460047788 No Faculty of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran Faranak Kazeruni فرانک کازرونی f_kazerouni@sbmu.ac.ir 5200319475328460047789 5200319475328460047789 No Dept. of Laboratory Medicine, School of Allied Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran Farid Zayeri فرید زیاری fzayeri@gmail.com 5200319475328460047790 5200319475328460047790 Yes Proteomics Research Center and Dept. of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran Fatemeh Gharishvandi فاطمه قریش‌وندی fatemehgharishvandi@gmail.com 5200319475328460047791 5200319475328460047791 No Dept. of Clinical Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran