Dastidar Rinini, Sikder Kunal, Das Barnali
Department of Biochemistry, Ramakrishna Mission Seva Pratishthan Hospital, 99 Sarat Bose Road, Kolkata, 700026 India.
Department of Biomedical Science and Technology, School of Biological Sciences, JIVAN, Ramakrishna Mission Vivekananda Educational and Research Institute, Belur Math, Howrah, 711202 India.
Indian J Clin Biochem. 2024 Jul;39(3):408-414. doi: 10.1007/s12291-023-01125-4. Epub 2023 Mar 20.
Chronic kidney disease (CKD) is one of the leading causes of mortality across the globe. Early diagnosis of the disease is important in order to prevent the adverse outcome related to CKD. Many laboratories adopt creatinine-based e-GFR equations which yields imprecise results leading to misdiagnosis of CKD. Emerging studies indicated cystatin C as a better renal marker than creatinine. The aim of the study is to compare the efficacy of CKD epidemiology collaboration (CKD-EPI) creatinine e-GFR equations with (CKD EPI) cystatin-based e-GFR equations alone and in combination with creatinine for early detection of CKD. A cross-sectional study employing 473 patients was conducted. Three estimating GFR equations were calculated based on creatinine and cystatin C. Pearson Correlation study was done to assess the correlation of creatinine and cystatin C with their respective GFRs. A predictive model was developed, and ROC curve was constructed to compare efficacy, sensitivity and specificity of the creatinine and cystatin C based equations. Cystatin C exhibited better negative correlation with GFR than creatinine in correlation study performed with three commonly employed eGFR equations including CKD EPI Creatine cystatin C combined equation (2021), cys C alone and CKD EPI creatinine (2021) equations respectively[r=(-) 0.801 vs. r=(-)0.786 vs. r=(-)0.773]. Predictive model demonstrated highest efficiency, sensitivity and specificity for creatinine-cystatin C combined equation (88%, 81% and 93%) followed by cystatin C alone equation (73%,63% and 82%) and creatinine-based equation (61%, 56% and 66% respectively). The study showed better performance of cystatin C based equations for early detection of advance stages in chronic kidney disease as compared to creatinine-based e-GFR equation.
慢性肾脏病(CKD)是全球主要的死亡原因之一。为预防与CKD相关的不良后果,疾病的早期诊断至关重要。许多实验室采用基于肌酐的估算肾小球滤过率(e-GFR)方程,其结果不准确,易导致CKD误诊。新出现的研究表明,胱抑素C是比肌酐更好的肾脏标志物。本研究的目的是比较CKD流行病学协作组(CKD-EPI)基于肌酐的e-GFR方程、单独基于胱抑素C的e-GFR方程以及二者联合用于早期检测CKD的效果。开展了一项纳入473例患者的横断面研究。基于肌酐和胱抑素C计算了三个估算肾小球滤过率的方程。进行了Pearson相关性研究,以评估肌酐和胱抑素C与其各自估算肾小球滤过率之间的相关性。建立了预测模型,并构建ROC曲线以比较基于肌酐和胱抑素C的方程的效果、敏感性和特异性。在分别使用三个常用的eGFR方程(包括CKD EPI肌酐-胱抑素C联合方程(2021)、单独的胱抑素C方程和CKD EPI肌酐(2021)方程)进行的相关性研究中,胱抑素C与估算肾小球滤过率的负相关性比肌酐更好[r = (-)0.801 vs. r = (-)0.786 vs. r = (-)0.773]。预测模型显示,肌酐-胱抑素C联合方程的效率、敏感性和特异性最高(分别为88%、81%和93%),其次是单独的胱抑素C方程(分别为73%、63%和82%)和基于肌酐的方程(分别为61%、56%和66%)。该研究表明,与基于肌酐的e-GFR方程相比,基于胱抑素C的方程在早期检测慢性肾脏病晚期阶段方面表现更好。