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1 型糖尿病患者估算肾小球滤过率和实测肾小球滤过率的纵向变化。

Longitudinal changes in estimated and measured GFR in type 1 diabetes.

机构信息

Division of Nephrology and Kidney Research Institute, University of Washington, Seattle, Washington;

出版信息

J Am Soc Nephrol. 2014 Apr;25(4):810-8. doi: 10.1681/ASN.2013050557. Epub 2013 Dec 5.

Abstract

Estimation of GFR from serum concentrations of creatinine and cystatin C has been refined using cross-sectional data from large numbers of people. However, the ability of the improved estimating equations to identify changes in GFR within individuals over time has not been rigorously evaluated, particularly within the normal range of GFR. In cross-sectional and longitudinal analyses of 1441 participants in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study with type 1 diabetes, we compared GFR estimated from creatinine (eGFR(Cr)), cystatin C (eGFR(Cys)), or both (eGFR(Cr+Cys)) with iothalamate GFR (iGFR), including changes in each over time. Mean (SD) iGFR was 122.7 (21.0) ml/min per 1.73 m(2). In cross-sectional analyses, eGFR(Cr+Cys) estimated iGFR with the highest correlation (r=0.48 versus 0.39-0.42), precision, and accuracy. In longitudinal analyses, change in eGFR(Cr+Cys) best estimated change in iGFR; however, differences between estimates were small, and no estimate accurately classified change in iGFR. Over a median 23 years of follow-up, mean rate of change in eGFR was similar across estimates of eGFR(Cr), eGFR(Cys), and eGFR(Cr+Cys) (-1.37, -1.11, and -1.29 ml/min per 1.73 m(2) per year, respectively). Associations of BP and hemoglobin A1c with change in eGFR were strongest for eGFR(Cys) and eGFR(Cr+Cys). Together, these results suggest that the addition of cystatin C to creatinine to estimate GFR may improve identification of the causes and consequences of GFR loss in type 1 diabetes, but may not meaningfully improve the tracking of GFR in clinical care.

摘要

使用大量人群的横断面数据,对基于血清肌酐和胱抑素 C 浓度的肾小球滤过率(glomerular filtration rate,GFR)估算值进行了改进。然而,这些改进的估算方程在个体内随时间识别 GFR 变化的能力尚未经过严格评估,尤其是在 GFR 的正常范围内。在 1441 例 1 型糖尿病患者的糖尿病控制和并发症试验(Diabetes Control and Complications Trial,DCCT)/糖尿病干预和并发症的流行病学(Epidemiology of Diabetes Interventions and Complications,EDIC)研究的横断面和纵向分析中,我们比较了基于肌酐(eGFR(Cr))、胱抑素 C(eGFR(Cys))或两者(eGFR(Cr+Cys))的 GFR 估算值与碘海醇 GFR(iGFR),包括随时间的每个变化。平均(标准差)iGFR 为 122.7(21.0)ml/min per 1.73 m(2)。在横断面分析中,eGFR(Cr+Cys) 与 iGFR 相关性最高(r=0.48 比 0.39-0.42),精度和准确性最好。在纵向分析中,eGFR(Cr+Cys) 的变化最好地估计了 iGFR 的变化;然而,各估计值之间的差异较小,且没有一个估计值能准确地对 iGFR 的变化进行分类。在中位数 23 年的随访期间,eGFR(Cr)、eGFR(Cys) 和 eGFR(Cr+Cys) 的估计值之间的平均 GFR 变化率相似(分别为-1.37、-1.11 和-1.29 ml/min per 1.73 m(2) per year)。BP 和血红蛋白 A1c 与 eGFR 变化的相关性在 eGFR(Cys) 和 eGFR(Cr+Cys) 中最强。综上所述,这些结果表明,将胱抑素 C 添加到肌酐中估算 GFR 可能会改善 1 型糖尿病患者 GFR 丧失的原因和后果的识别,但可能不会显著改善临床护理中 GFR 的跟踪。

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