Department of Chemical Pathology and NHLS, University of the Witwatersrand, Johannesburg, South Africa.
Nephrol Dial Transplant. 2011 May;26(5):1553-8. doi: 10.1093/ndt/gfq621. Epub 2010 Oct 20.
Serum creatinine (S-Cr)-based prediction equations are commonly used for estimating glomerular filtration rate (GFR). However, S-Cr concentration is also affected by other factors such as tubular secretion, muscle mass, diet, gender and age. Serum cystatin C (S-Cys C)-based prediction equations have been proposed as an improved potential alternative as S-Cys C levels are not influenced by many of the factors that affect creatinine concentration other than GFR. This may be of great benefit to patients with low muscle mass such as those infected with human immunodeficiency virus who are at increased risk for the development of renal impairment. The aim of this study was to develop and evaluate a S-Cys C-based prediction equation for different stages of renal disease in black South Africans.
One hundred patients with varying degrees of renal function were enrolled in the study. The plasma clearance of (51)Cr-EDTA, a gold standard method, was used to measure GFR (mGFR). In addition, serum was analysed for S-Cr and S-Cys C on each participant. This dataset was split into a development dataset (n = 50) and a test dataset (n = 50). The development dataset was used to formulate a S-Cys C- and S-Cr-based prediction equation using multiple linear regression analysis. These equations together with the four-variable MDRD and CKD-EPI equation were then tested on the test dataset.
In the test dataset, accuracy within 15% of measured GFR was 68% for the S-Cys C equation and 48% for the S-Cr equation. Root mean square error for S-Cr eGFR was 10.7 mL/min/1.73 m(2) for those patients with mGFR < 60 mL/min/1.73 m(2) and 25.5 mL/min/1.73 m(2) for those patients with mGFR > 60 mL/min/1.73 m(2). Root mean square error for S-Cys C eGFR was 10.2 mL/min/1.73 m(2) for those patients with mGFR < 60 mL/min/1.73 m(2) and 11.9 mL/min/1.73 m(2) for those patients with mGFR > 60 mL/min/1.73 m(2).
In this study, S-Cys C-based prediction equations appear to be more precise than those of S-Cr for those patients with mGFR > 60 mL/min/1.73 m(2) and may therefore be of benefit in the earlier detection of renal impairment.
血清肌酐(S-Cr)为基础的预测方程通常用于估算肾小球滤过率(GFR)。然而,S-Cr 浓度也受到其他因素的影响,如肾小管分泌、肌肉量、饮食、性别和年龄。血清胱抑素 C(S-Cys C)为基础的预测方程已被提出作为一种改进的潜在替代方法,因为 S-Cys C 水平不受除 GFR 以外许多影响肌酐浓度的因素的影响。这对于肌肉量低的患者(如感染人类免疫缺陷病毒的患者)可能有很大的益处,这些患者有发生肾功能损害的风险增加。本研究的目的是为南非黑人的不同阶段的肾病开发和评估一种基于 S-Cys C 的预测方程。
100 名肾功能不同的患者参加了这项研究。使用(51)Cr-EDTA 的血浆清除率,一种金标准方法,来测量肾小球滤过率(mGFR)。此外,对每个参与者的血清进行 S-Cr 和 S-Cys C 的分析。该数据集分为开发数据集(n=50)和测试数据集(n=50)。使用多元线性回归分析,从开发数据集制定了一个基于 S-Cys C 和 S-Cr 的预测方程。然后在测试数据集上测试这些方程以及四个变量的 MDRD 和 CKD-EPI 方程。
在测试数据集,基于 S-Cys C 的方程在测量 GFR 的 15%以内的准确度为 68%,而基于 S-Cr 的方程的准确度为 48%。对于 mGFR < 60 mL/min/1.73 m(2)的患者,S-Cr eGFR 的均方根误差为 10.7 mL/min/1.73 m(2),对于 mGFR > 60 mL/min/1.73 m(2)的患者,S-Cr eGFR 的均方根误差为 25.5 mL/min/1.73 m(2)。对于 mGFR < 60 mL/min/1.73 m(2)的患者,基于 S-Cys C 的方程在测量 GFR 的 15%以内的准确度为 10.2 mL/min/1.73 m(2),对于 mGFR > 60 mL/min/1.73 m(2)的患者,准确度为 11.9 mL/min/1.73 m(2)。
在这项研究中,对于 mGFR > 60 mL/min/1.73 m(2)的患者,基于 S-Cys C 的预测方程似乎比基于 S-Cr 的预测方程更精确,因此可能有助于更早地发现肾功能损害。