评估肾小球疾病中基于生物标记物的 GFR 估算公式

Antara Mondal, Christina Kobe, Laura H. Mariani, J. Zee
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摘要

简介:肾小球滤过率(GFR肾小球滤过率(GFR)通常通过使用血清肌酐和/或胱抑素-C 等生物标志物的方程进行估算。这些不同的生物标志物对肾小球疾病患者肾小球滤过率估计值的影响尚不清楚。在这项研究中,我们比较了治疗肾小球肾病(CureGN)队列中患有肾小球疾病的儿童和成人的不同 GFR 估算方程:方法: 将 CureGN 研究参与者所有可用的胱抑素-C 测量值与当天的血清肌酐测量值进行比对,以估算 GFR。为了探讨从 "25 岁以下"(U25)和慢性肾脏病流行病学协作组(CKD-Epi)方程中获得的 eGFR 值之间的一致性强度,我们使用了类内相关系数。多变量线性混合效应模型用于确定哪些因素与 eGFR 值的差异独立相关:共有 928 个胱抑素-C 测量值与 N=332 名 CureGN 研究参与者(58% 为男性,69% 为白人/高加索人,20% 为黑人/非洲裔美国人)的当日血清肌酐测量值相匹配。在研究参与者 25 岁以下时收集的 628 次测量中,血清肌酐与胱抑素-C U25 方程的一致性为中等(0.731)。模型显示,eGFR 值越高,两个方程之间的差异越大(p <0.001)。在研究参与者至少 18 岁时收集的 253 次测量结果中,单独使用血清肌酐、单独使用胱抑素-C 或两者结合使用的 CKD-Epi 方程的一致性非常好(0.891-0.978)。年龄越小,CKD-Epi 方程之间的差异越大(p=0.06 至 p=0.016):结论:CKD-Epi 方程之间极好的一致性表明,成人继续仅使用血清肌酐估算 GFR 是合适的。与此相反,U25 方程之间的一致性仅为中等,这表明儿童和年轻人需要更频繁地测量胱抑素-C,尤其是随着 eGFR 的增加。
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Evaluation Of Biomarker-Based GFR Estimating Equations in Glomerular Disease
Introduction: Glomerular filtration rate (GFR) is typically estimated with equations that use biomarkers such as serum creatinine and/or cystatin-C. The impact of these different biomarkers on GFR estimates in glomerular disease patients is unclear. In this study, we compared the different GFR estimating equations in the Cure Glomerulonephropathy (CureGN) cohort of children and adults with glomerular disease. Methods: All available cystatin-C measurements from CureGN study participants were matched to same-day serum creatinine measurements to estimate GFR. To explore the strength of agreement between eGFR values obtained from the "Under 25” (U25) and Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) equations, we used intraclass correlation coefficients. Multivariable linear mixed effects models were used to determine which factors were independently associated with differences in eGFR values. Results: A total of 928 cystatin-C measurements were matched to same-day serum creatinine measurements from N=332 CureGN study participants (58% male, 69% White/Caucasian, 20% Black/African American). Among 628 measurements collected while study participants were under 25 years old, there was moderate agreement (0.731) in serum creatinine vs. cystatin-C U25 equations. Models showed that higher eGFR values were associated with larger differences between the two equations (p <0.001). Among 253 measurements collected while study participants were at least 18 years old, there was excellent agreement (0.891-0.978) among CKD-Epi equations using serum creatinine alone, cystatin-C alone, or the combination of both. Younger age was associated with larger differences between CKD-Epi equations (p=0.06 to p=0.016). Conclusion: Excellent agreement between CKD-Epi equations indicates continued use of serum creatinine only for GFR estimation could be appropriate for adults. In contrast, only moderate agreement between U25 equations indicates a need for more frequent measurement of cystatin-C among children and young adults, especially as eGFR increases.
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