临床医学进展  >> Vol. 9 No. 11 (November 2019)

体重指数对胱抑素C公式法估算肾小球滤过率的影响
Effect of Body Mass Index on Evaluation of Glomerular Filtration Rate Using Equations Based on Cystatin C

DOI: 10.12677/ACM.2019.911193, PDF, HTML, XML, 下载: 287  浏览: 1,671  科研立项经费支持

作者: 郭淑英, 祝建辉, 赵 文:深圳市福田区第二人民医院肾内科,广东 深圳;曾牡云, 欧阳敏, 何 倩:深圳市福田区第二人民医院体检科,广东 深圳

关键词: 体重指数胱抑素C肾小球滤过率Body Mass Index Cystatin C Glomerular Filtration Rate

摘要: 目的:探讨体重指数(BMI)对基于胱抑素C (CysC)公式法评估肾小球滤过率(eGFR)的影响。方法:收集我院体检科2018年1月至2018年12月体检的、资料完整的健康人群308例。BMI计算按公式BMI (kg/m2) = 体重(kg)/[身高(m)]2,BMI ≥ 28 kg/m2定义为肥胖,BMI 24.0~27.9 kg/m2定义为超重,BMI 18.5~23.9 kg/m2定义为正常。年龄 > 40岁定义为中老年人,年龄 ≤ 40岁定义为青年人。CKD定义及分期按KDOQI标准。采用胶体颗粒增强免疫比浊法检测血清CysC,>1.55 mg/L定义为CysC升高;采用苦味酸法检测血肌酐(Scr),血肌酐升高定义为:男 > 97 umol/L,女 > 81 umol/L。用慢性肾脏病流行病学合作研究公式(CKD-EPIScr-Scys, CKD-EPIScr, CKD-EPScys)、CG公式、中国改良MDRD公式估算GFR (eGFR)。用SPSS22.0统计软件进行统计学分析,以p < 0.05为差异有统计学意义。结果:1) 308例健康体检者中,女性48例(15.6%)。平均年龄37岁 ± 9.7岁(20岁~81岁)。平均BMI 24.6 ± 1.5 (21.0~30.1) kg/m2,其中肥胖6例,超重200例,BMI正常102例。平均Scr为72.5 ± 11.3 (41~102) umol/L,其中血肌酐升高6例。平均CysC 0.81 ± 0.13 (0.57~1.61) mg/L,其中CysC升高2例。5种公式估算的平均eGFR分别为:eGFR (CKD-EPIScr-Scys) 119.9 ± 13.5 ml/min/1.73m2,诊断CKD 2例(0.65%);eGFR (CKD-EPIScr) 110.3 ± 11.9 ml/min/1.73m2,诊断CKD 2例(0.65%);eGFR (CKD-EPIScys) 105.3 ± 20.5 ml/min/1.73m2,诊断CKD 12例(3.90%);eGFR (CG公式) 120.7 ± 20.1 ml/min/1.73m2,诊断CKD 2例(0.65%);eGFR (改良MDRD) 116.7 ± 20.1 ml/min/1.73m2,诊断CKD 0例(0%)。2) 与青年人比较,中老年人CysC水平明显升高(p = 0.000),CKD-EPIScr-Scys、CKD-EPIScr、CKD-EPIScys、CG公式、改良MDRD五种公式估算的GFR值均明显降低(p均为0.000)。3) 由于研究人群肥胖人数少,我们按三分位法把BMI分为三组:BMI < 24.0 kg/m2组、BMI 24.0~25.3 kg/m2组、BMI > 25.3 kg/m2组。结果显示,CysC水平及eGFR (CKD-EPIScr-Scys)、eGFR (CKD-EPIScys)在三组之间无显著差异(p分别为1.000,0.343,0.859)。但Scr水平及eGFR (CKD-EPIScr)、eGFR (改良MDRD)在三个BMI分组之间有显著差异(p分别为0.002,0.005,0.001),eGFR (CG公式)总体差异不显著(p = 0.07)。结论:健康体检人群血清CysC水平和基于CysC公式(CKD-EPIScr-Scys, CKD-EPScys)估算eGFR不受BMI影响。这可能与本研究肥胖例数少有关。CysC与肥胖之间关系的研究需要进一步改进肥胖的诊断标准比如采用体脂而不是BMI。
Abstract: Objective: To investigate the effect of body mass index (BMI) on the evaluation of glomerular filtration rate (eGFR) using equations based on the cystatin C (CysC). Methods: A total of 308 healthy people with complete medical records from January to December 2018 in our department of physical examination were collected. BMI calculation formula is BMI (kg/m2) = body weight (kg)/[height (m)]2, and BMI ≥ 28 kg/m2 is defined as obesity, BMI 24.0 - 27.9 kg/m2 as overweight, and BMI 18.5 - 23.9 kg/m2 as normal. Age > 40 years old is defined as middle-aged and elderly, and age ≤ 40 years old is defined as young people. The CKD definition and staging are based on the KDOQI standard. Serum CysC was detected by colloidal partical enhanced immunoturbidimetry; >1.55 mg/L was defined as elevated CysC; serum creatinine (Scr) was detected by picric acid method, and elevated creatinine was defined as: male >97 umol/L, female > 81 umol/L. GFR (eGFR) was estimated using the Chronic Kidney Disease and Epidemiology (CKD-EPI) equation using creatinine (CKD-EPIScr), cystatin (CKD-EPIScys) and the combination of cystatin and creatinine (CKD-EPIScr-Scys), CG equation, and China’s modified MDRD equation. Statistical analysis was performed using SPSS 22.0 statistical software, and the difference was statistically significant at p < 0.05. Results: 1) Of the 308 healthy subjects, 48 (15.6%) were women. The average age is 37 ± 9.7 years old (20 ± 81). The average BMI was 24.6 ± 1.5 kg/m2 (21.0 - 30.1), including 6 cases of obesity, 200 cases of overweight and 102 cases normal. The average Scr was 72.5 ± 11.3 umol/L (41 - 102), and serum creatinine was increased in 6 cases. The average CysC was 0.81 ± 0.13 mg/L (0.57 - 1.61), and CysC was increased in 2 cases. The average eGFR is estimated by the five equations respectively: eGFR (CKD-EPIScr-Scys) 119.9 ± 13.5 ml/min/1.73m2, 2 cases with diagnosed CKD (0.65%); eGFR (CKD-EPIScr) 110.3±11.9 ml/min/1.73m2, 2 cases with diagnosed CKD (0.65%); eGFR (CKD-EPIScys) 105.3 ± 20.5 ml/min/1.73m2, 12 cases with diagnosed CKD (3.90%); eGFR (CG) 120.7 ± 20.1 ml/min/1.73m2, 2 cases with diagnosed CKD (0.65%); eGFR (modified MDRD) 116.7 ± 20.1 ml/min/1.73m2, 0 case with diagnosed CKD (0%). 2) Compared with young people, the CysC level of middle-aged and elderly people was significantly increased (p = 0.000), and the GFR was significantly decreased (p = 0.000) estimated by the five equations of CKD-EPIScr-Scys, CKD-EPIScr, CKD-EPIScys, CG and modified MDRD. 3) Because of the small number of obese people in the study population, we divided them into three groups based on BMI tertiles: BMI < 24.0 kg/m2 group, BMI 24.0 - 25.3 kg/m2 group, and BMI > 25.3kg/m2 group. The results showed that CysC levels and eGFR estimated by CKD-EPIScr-Scys and CKD-EPIScys were not significantly different among the three groups (p = 1.000, 0.343, 0.859, respectively). However, among the three groups, there were significant differences in Scr levels and eGFR estimated by CKD-EPIScr and modified MDRD (p = 0.002, 0.005, 0.001, respectively), but no difference in eGFR estimated by CG (p = 0.07). Conclusions: In healthy subjects, serum CysC levels and eGFR estimated by the CysC-based equations (CKD-EPIScr-Scys, CKD-EPScys) are not affected by BMI. This may be related to the small number of obese cases in this study. The study of the relationship between CysC and obesity requires further improvement in the diagnostic criteria for obesity such as the use of body fat rather than BMI.

文章引用: 郭淑英, 祝建辉, 曾牡云, 欧阳敏, 何倩, 赵文. 体重指数对胱抑素C公式法估算肾小球滤过率的影响[J]. 临床医学进展, 2019, 9(11): 1247-1254. https://doi.org/10.12677/ACM.2019.911193

1. 引言

慢性肾脏病(chronic kidney disease, CKD)已经成为一个公共卫生问题。在成人CKD的鉴别、分类和治疗中,准确估计肾小球滤过率(glomerular filtration rate, GFR)至关重要。长期以来,国内外学者通过基于血清肌酐(serum creatinine, Scr)的公式法估算GFR (estimated GFR, eGFR),如CG公式,MDRD公式。近十余年来,基于血清胱抑素C (cystatin C, CysC)的公式法估算GFR备受关注。CysC具有较低的分子量,由肾小球滤过膜自由过滤,不被肾小管重新吸收、分泌或代谢,而且它不依赖于肌肉,因此被认为是评价GFR的一个良好的生物标志物。2012年改善全球肾脏病预后组织(KDIGO)建议 [1],在没有其他肾脏损伤证据时,基于CysC的GFR估算公式计算的eGFR对诊断和处治CKD具有重要意义。该系列公式在世界范围内得到广泛应用,并指导各个国家对CKD的统计和管理。近年来有研究 [2] [3] 发现,肥胖影响血清CysC水平,体重指数(body mass index, BMI),影响公式法对CKD发病率的评估,但结论并不一致 [4]。本研究旨在探讨BMI对基于CysC公式法评估GFR的影响。

2. 研究方法

2.1. 研究对象

收集我院体检科2018年1月至2018年12月体检的、资料完整的健康人群308例。排除标准:有明确慢性肾脏病、甲状腺疾病病史;体检时有明显感染;有严重心衰、严重心律失常、心肌梗塞急性期、出血性或缺血性卒中急性期;资料不全的。本研究已获我院医学伦理委员会批准,所有研究对象均签署知情同意书。

2.2. BMI计算及肥胖和超重定义

BMI计算公式 [5] :BMI (kg/m2) = 体重(kg)/[身高(m)]2。根据中国成人肥胖症防治专家共识 [6],BMI ≥ 28 kg/m2定义为肥胖,BMI 24.0~27.9 kg/m2定义为超重,BMI 18.5~23.9 kg/m2定义为正常。

2.3. 年龄划分标准

青年18~40岁;中年41~65岁;老年66岁以后。在本研究中,年龄 > 40岁定义为中老年人,年龄 ≤ 40岁定义为青年人。

2.4. CKD定义及分期

按KDOQI标准 [7]。CKD定义:肾脏损伤(肾脏结构或功能异常,包括病理学检查异常或血、尿成分异常或影像学检查异常)或GFR < 60 ml/min/1.73m2,时间大于3个月。CKD1-5期分期标准:1期GFR ≥ ml/min/1.73m2,2期GFR60-89 ml/min/1.73m2,3期GFR30-59 ml/min/1.73m2,4期GFR15-29 ml/min/1.73m2,5期GFR < 15 ml/min/1.73m2

2.5. 观察指标

2.5.1. 血清CysC (Scys) (mg/L)检测

采用胶体颗粒增强免疫比浊法,试剂盒购自北京利德曼生化股份有限公司,仪器为日立Hitachi 7180生化分析仪。Scys升高定义为:>1.55 mg/L。

2.5.2. Scr (mg/dl)检测

采用苦味酸法检测。血肌酐升高定义为:男 > 97 umol/L,女 > 81 umol/L。

2.5.3. eGFR (ml/min/1.73m2)

GFR估算公式采用以下公式(具体如下)。其中CG公式得出的eGFR需要用体表面积进行校正[×(BSA/1.73)]。根据Stevenson公式计算体表面积(BSA),BSA (m2) = 0.0061 × 身高(cm) + 0.0128 × 体重(kg) − 0.1529。

1) CKD-EPIScr-Scys公式 [8]

女:Scr ≤ 0.7 mg/dl,CysC ≤ 0.8 mg/L:GFR = 130 × (Scr/0.7)−0.248 × (Scys/0.8)−0.375 × 0.995Age [×1.08 if black]

女:Scr ≤ 0.7 mg/dl,CysC > 0.8 mg/L:GFR = 130 × (Scr/0.7)−0.248 × (Scys/0.8)−0.711 × 0.995Age [×1.08 if black]

女:Scr > 0.7 mg/dl,CysC ≤ 0.8 mg/L:GFR = 130 × (Scr/0.7)−0.601 × (Scys/0.8)−0.375 × 0.995Age [×1.08 if black]

女:Scr > 0.7 mg/dl,CysC > 0.8 mg/L:GFR = 130 × (Scr/0.7)−0.601 × (Scys/0.8)−0.711 × 0.995Age [×1.08 if black]

男:Scr ≤ 0.9 mg/dl,CysC ≤ 0.8 mg/L:GFR = 135 × (Scr/0.9)−0.207 × (Scys/0.8)−0.375 × 0.995Age [×1.08 if black]

男:Scr ≤ 0.9 mg/dl,CysC > 0.8 mg/L:GFR = 135 × (Scr/0.9)−0.207 × (Scys/0.8)−0.711 × 0.995Age [×1.08 if black]

男:Scr > 0.9 mg/dl,CysC ≤ 0.8 mg/L:GFR = 135 × (Scr/0.9)−0.601 × (Scys/0.8)−0.375 × 0.995Age [×1.08 if black]

男:Scr > 0.9 mg/dl,CysC > 0.8 mg/L:GFR = 135 × (Scr/0.9)−0.601 × (Scys/0.8)−0.711 × 0.995Age [×1.08 if black]

2) CKD-EPIScr公式 [9]

女:Scr ≤ 0.7 mg/dl:GFR = 144 × (Scr/0.7)0.329 × (0.993)Age × (1.159 if black)

女:Scr > 0.7 mg/dl:GFR = 144 × (Scr/0.7)1.209 × (0.993)Age × (1.159 if black)

男:Scr ≤ 0.9 mg/dl:GFR = 141 × (Scr/0.9)0.411 × (0.993)Age × (1.159 if black)

男:Scr > 0.9 mg/dl:GFR = 141 × (Scr/0.9)1.209 × (0.993)Age × (1.159 if black)

3) CKD-EPScys公式 [8]

男或女,CysC ≤ 0.8 mg/L:GFR = 133 × (Scys /0.8)0.499 × 0.996Age [×0.932 if female]

男或女,CysC > 0.8 mg/L:GFR = 133 × (Scys /0.8)2.382 × 0.996Age [×0.932 if female]

4) CG公式 [10] :eGFR = (140 − 年龄) × 体重/72 × 肌酐(mg/dl) [×0.85 if female]

5) 中国改良MDRD公式 [11] :eGFR (ml/min/1.73m2) = 175 × [肌酐(mg/dl)] −1.234 × [年龄(岁)] −0.179 × 性别(男性 = 1,女性 = 0.79)

2.6. 统计学分析方法

对上述实验数据用SPSS22.0统计软件进行统计学分析。发生率采用率的显著性检验,计量资料采用T检验、非参数检验、单因素ANOVA方差分析。p < 0.05为有统计学意义。

3. 结果

3.1. 一般情况

308例健康体检者中,女性48例(15.6%)。年龄20岁~81岁,平均年龄37岁 ± 9.7岁(20岁~81岁)。平均BMI 24.6 ± 1.5 (21.0~30.1) kg/m2,其中肥胖6例,超重200例,BMI正常102例。平均Scr为72.5 ± 11.3 (41~102) umol/L,其中血肌酐升高6例。平均CysC 0.81 ± 0.13 (0.57~1.61) mg/L,其中CysC升高2例。5种公式估算的平均eGFR及诊断为CKD的比率分别为:eGFR(CKD-EPIScr-Scys) 119.9 ± 13.5 (43.8~135.1) ml/min/1.73m2,诊断CKD 2例(0.65%);eGFR (CKD-EPIScr) 110.3 ± 11.9 (56.3~130.9) ml/min/1.73m2,诊断CKD 2例(0.65%);eGFR (CKD-EPIScys) 105.3 ± 20.5 (16.9~131.7) ml/min/1.73m2,诊断CKD 12例(3.90%);eGFR (CG公式) 120.7 ± 20.1 (51.9~187.2) ml/min/1.73m2,诊断CKD 2例(0.65%);eGFR (改良MDRD) 116.7 ± 20.1 (67.1~186.1) ml/min/1.73m2,诊断CKD 0例(0%)。

3.2. 不同年龄人群CysC水平及公式法评估eGFR情况

与青年人比较,中老年人CysC水平明显升高(p = 0.000),CKD-EPIScr-Scys、CKD-EPIScr、CKD-EPIScys、CG公式、改良MDRD五种公式估算的GFR值均明显降低(p均为0.000);而两个人群的BMI、BSA、Scr无明显差异(p分别为0.932,0.074,0.925)。中老年人女性比例明显大于青年人(p = 0.000)。详见表1

Table 1. CysC level and eGFR estimated by the CysC-based equations in different age groups

表1. 不同年龄人群CysC水平及公式法评估eGFR情况

3.3. 不同BMI分组CysC水平及公式法评估eGFR情况

由于研究人群肥胖人数少,我们按三分位法把BMI分为三组:BMI < 24.0 kg/m2组、BMI 24.0~25.3 kg/m2组、BMI > 25.3 kg/m2组。结果显示,CysC水平及eGFR (CKD-EPIScr-Scys)、eGFR (CKD-EPIScys)在三组之间无显著差异(p分别为1.000,0.343,0.859)。但Scr水平及eGFR (CKD-EPIScr)、eGFR (改良MDRD)在三个BMI分组之间有显著差异(p分别为0.002,0.005,0.001),eGFR (CG公式)在BMI 24.0~25.3 kg/m2组与BMI > 25.3 kg/m2组之间有差异(p < 0.05),然而总体差异不显著(p = 0.07)。详见表2

Table 2. CysC level and eGFR estimated by the CysC-based equations among three groups based-on BMI

表2. 3组BMI分组CysC水平及公式法评估eGFR情况

4. 讨论

本研究结果显示,中老年人血清CysC水平显著高于青年人(p < 0.001),不管基于Scr的公式(CG公式、MDRD公式、CKD-EPIScr)还是基于CysC的公式(CKD-EPIScys)或基于二者的公式(CKD-EPIScr-Scys),估算的中老年人GFR值均显著低于青年人(p < 0.001),提示CysC随年龄增长升高,GFR随年龄增长而降低,与文献结果 [12] [13] 一致。

虽然CysC被认为不受性别、年龄或肌肉重量的影响,但现在的研究表明它已与年龄、性别、身高、体重、BMI相关。大样本前瞻性研究 [14] 显示,与正常体质量人群相比,肥胖人群血清CysC水平显著增加。Panaich等 [15] 及Shankar等 [2] 研究发现,在成年人群中,血清CysC水平与BMI呈显著正相关。Vupputuri S等 [3] 使用CysC方程和MDRD研究方程估算eGFR第3~4期CKD患病率,发现在高BMI时二者差异逐渐增大,提示基于CysC方程式可能导致超重和肥胖成人CKD患病率过高估计。

本研究把BMI按三分位分为<24.0 kg/m2、24.0~25.3 kg/m2、>25.3 kg/m2三组。通过单因素方差分析,三组之间CysC并无显著差异,三组之间基于CysC公式估算的eGFR亦无显著差异。越来越多的肥胖与CysC相关研究发现,血清CysC升高和估算的肾功能下降与体脂关系密切,而不是BMI。Lemoine S等 [4] 的研究纳入166名肥胖的1~5期CKD患者,采用体表面积校正测量的GFR (mGFR)和CKD-EPIScr、CKD-EPIScys、CKD-EPIScr-Scys公式估算eGFR,结果发现mGFR与CKD-EPIScr-Scys之间的偏差显著低于CKD-EPIScr (p = 0.001),相对CKD-EPIScr和CKD-EPIScys,CKD-EPIScr-Scys准确性显著提高(p = 0.04和0.03);只有腰围(WC)与胱抑素C呈显著正相关(p < 0.0001),而体重指数(BMI; p = 0.3)则无显着性差异(P > 0.05);CKD-EPIScr-Scys偏倚与WC有关。von Scholten BJ等 [16] 研究了19例肥胖患者在胃旁路手术后体重减轻对测定和估算GFR的影响,在术前、术后6个月利用51Cr-EDTA清除测定GFR (mGFR),同时用MDRD、CKD-EPIScr、CKD-EPIScys和CKD-EPIScr-Scys四种方程计算GFR,结果:术后6个月体重减轻27 kg,mGFR由122 ± 24降至113 ± 21 ml/min (p = 0.024),但体表面积校正后的mGFR未见明显改变(p = 0.52)。CKD-EPIScr增加12 ml/min/1.73m2,MDRD增加13 ml/min/1.73m2,p均 < 0.001,CKD-EPIScys增加2 ml/min/1.73m2 (p = 0.51);CysC的GFR估计值不受体重的影响。Madero M等 [17] 比较了CT和人体计量学测量肥胖与肾脏结果的关系,结果内脏腹部脂肪(VAT)、BMI和WC与发生CKD相关,当其他暴露变量包括在同一模型中时,只有VAT才是发生CKD (定义为基线GFR > 60 ml/min/1.73m2者,追踪eGFRScys ≤ 60 ml/min/1.73m2)的一个重要风险因素;当肌酐值用于估算eGFR变化时,任何衡量肥胖的指标都与肾脏的结果无关。这些都提示血清CysC水平和基于CysC公式评估的eGFR与体脂和体脂分布关系密切,而非体重、BMI。实际上,造成肾功能减退的是体脂增加,而不是体重 [18] [19]。这就要求我们使用更准确的肥胖诊断标准(体脂)来研究CysC与肥胖的关系,而不是传统的BMI。

在肥胖患者中,血清CysC升高是脂肪增多的结果还是肥胖相关肾损害的早期标志?在前脂肪细胞分化成熟过程中,CysC大量表达,抑制抵抗肥胖的组织蛋白酶S活性,促进肥胖 [20]。也有证据表明脂肪细胞分泌CysC [21]。Bostan Gayret Ö等 [22] 研究表明,血清CysC和尿NGAL、尿OPN可作为评价儿童肥胖对肾脏作用的良好指标。Önerli Salman D等 [23] 研究表明,CysC可以作为一个比Cr更早的生物标志物来检测肥胖儿童,尤其是代谢综合征(Mets)儿童的肾功能受损。以CysC为基础的Mets患者EGFR的降低,而不是基于Cr公式的降低,可能代表了肾损害的早期阶段。CysC与肥胖之间的关系有待进一步基础和临床研究。

总之,本研究提示,健康体检人群血清CysC水平和基于CysC公式(CKD-EPIScr-Scys, CKD-EPScys)估算eGFR不受BMI影响。CysC与肥胖之间关系的研究需要进一步改进肥胖的诊断标准,比如采用体脂而不是BMI。

本研究的局限性:1) 样本量少,样本中诊断肥胖患者比例少,只有6例BMI > 28 kg/m2,存在选择偏倚;BMI分组时不是依据指南或共识标准。2) 没有采用体脂这一诊断肥胖更准确的指标。3) eGFR没有测量GFR (mGFR)这一“金标准”对照。进一步研究可扩大样本量,增加人体成分分析中体脂指标,观察健康体检人群CysC和基于CysC公式估算eGFR与肥胖之间关系。

基金项目

本研究受深圳市福田区卫生公益性科研项目资助(课题编号FTWS2015053)。

参考文献

[1] KDIGO (2013) KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney International Supplements, 3, 19-62.
[2] Shankar, A. and Teppala, S. (2011) Relationship between Body Mass Index and High Cystatin Levels among US Adults. The Journal of Clinical Hypertension, 13, 925-930.
https://doi.org/10.1111/j.1751-7176.2011.00548.x
[3] Vupputuri, S., Fox, C.S., Coresh, J., et al. (2009) Differen-tial Estimation of CKD Using Creatinine- versus Cystatin C-Based Estimating Equations by Category of Body Mass In-dex. American Journal of Kidney Diseases, 53, 993-1001.
https://doi.org/10.1053/j.ajkd.2008.12.043
[4] Lemoine, S., Panaye, M., Pelletier, C., et al. (2016) Cystatin C-Creatinine Based Glomerular Filtration Rate Equation in Obese Chronic Kidney Disease Patients: Impact of Deindexa-tion and Gender. American Journal of Nephrology, 44, 63-70.
https://doi.org/10.1159/000447365
[5] 中华医学会内分泌学分会肥胖学组. 中国成人肥胖症防治专家共识[J]. 中华内分泌代谢杂志, 2011, 27(9): 711-717.
[6] Khosla, T. and Lowe, C.R. (1967) Indices of Obesity Derived from Body Weight and Height. British Journal of Preventive & Social Medicine, 21, 122-128.
https://doi.org/10.1136/jech.21.3.122
[7] National Kidney Foundation (2002) K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification. American Journal of Kidney Diseases, 39, S1-S266.
[8] Inker, L.A., Schmid, C.H., Tighiouart, H., et al. (2012) Estimating Glomerular Filtration Rate from Serum Creatinine and Cystatin C. The New England Journal of Medi-cine, 367, 20-29.
https://doi.org/10.1056/NEJMoa1114248
[9] Levey, A.S., Stevens, L.A., Schmid, C.H., et al. (2009) A New Equation to Estimate Glomerular Filtration Rate. Annals of Internal Medicine, 150, 604-612.
https://doi.org/10.7326/0003-4819-150-9-200905050-00006
[10] Cockcroft, D.W. and Gault, M.H. (1976) Predic-tion of Creatinine Clearance from Serum Creatinine. Nephron, 16, 31-41.
https://doi.org/10.1159/000180580
[11] 全国eGFR课题协作组. MDRD方程在我国慢性肾脏病患者中的改良和评估[J]. 中华肾脏病杂志, 2006, 22(10): 589-595.
[12] Maahsd, M., Prentice, N., Mcfann, K., et al. (2011) Age and Sex Influence Cystatin C in Adolescents with and without Type1 Diabetes. Diabetes Care, 34, 2360-2362.
https://doi.org/10.2337/dc11-0829
[13] 曹聃, 张伟光, 张银平, 等. 不同年龄健康人肾脏滤过功能评价指标的生理范围及影响因素[J]. 中国中西医结合肾病杂志, 2017, 18(5): 409-412.
[14] Luc, G., Bard, J.M., Lesueur, C., et al. (2006) Plasma Cystatin-C and Development of Coronary Heart Disease: The PRIME Study. Atherosclerosis, 185, 375-380.
https://doi.org/10.1016/j.atherosclerosis.2005.06.017
[15] Panaich, S.S., Veeranna, V., Bavishi, C., et al. (2014) Association of Cystatin C with Measures of Obesity and Its Impact on Cardio-Vascular Events among Healthy US Adults. Metabolic Syndrome and Related Disorders, 12, 472-476.
https://doi.org/10.1089/met.2014.0018
[16] von Scholten, B.J., Persson, F., Svane, M.S., et al. (2017) Effect of Large Weight Reductions on Measured and Estimated Kidney Function. BMC Nephrology, 18, 52.
https://doi.org/10.1186/s12882-017-0474-0
[17] Madero, M., Katz, R., Murphy, R., et al. (2017) Comparison be-tween Different Measures of Body Fat with Kidney Function Decline and Incident CKD. Clinical Journal of the Ameri-can Society of Nephrology, 12, 893-903.
https://doi.org/10.2215/CJN.07010716
[18] Chen, Y.Y., Fang, W.H., Wang, C.C., et al. (2018) Changes of Per-cent Body Fat as a Useful Surrogate for Risk of Declined Renal Function. Scientific Reports, 8, 17289.
https://doi.org/10.1038/s41598-018-35601-2
[19] Kim, J.K., Song, Y.R., Kwon, Y.J., et al. (2014) Increased Body Fat Rather than Body Weight Has Harmful Effects on 4-Year Changes of Renal Function in the General Elderly Popula-tion with a Normal or Mildly Impaired Renal Function. Clinical Interventions in Aging, 9, 1277-1286.
https://doi.org/10.2147/CIA.S66714
[20] Taleb, S., Cancello, R., Clément, K. and Lacasa, D. (2006) Cathepsin S Promotes Human Preadipocyte Differentiation: Possible Involvement of Fibronectin Degradation. Endocrinology, 147, 4950-4959.
https://doi.org/10.1210/en.2006-0386
[21] Kratchmarova, I., Kalume, D.E., Blagoev, B., et al. (2002) A Proteomic Approach for Identification of Secreted Proteins during the Differentiation of 3T3-L1 Preadipocytes to Adipocytes. Mo-lecular & Cellular Proteomics, 1, 213-222.
https://doi.org/10.1074/mcp.M200006-MCP200
[22] Önerli Salman, D., Şıklar, Z., Çullas İlarslan, E.N., et al. (2019) Evaluation of Renal Function in Obese Children and Adolescents Using Serum Cystatin C Levels, Estimated Glomerular Filtration Rate Formulae and Proteinuria: Which Is Most Useful? Journal of Clinical Research in Pediatric Endocrinology, 11, 46-54.
https://doi.org/10.4274/jcrpe.galenos.2018.2018.0046
[23] Bostan Gayret, Ö., Taşdemir, M., Erol, M., et al. (2018) Are There Any New Reliable Markers to Detect Renal Injury in Obese Children? Renal Failure, 40, 416-422.
https://doi.org/10.1080/0886022X.2018.1489284