尿白蛋白与肌酐比值使用当日测量:公式的验证

G. Résimont, L. Vranken, H. Pottel, F. Jouret, J. Krzesinski, E. Cavalier, P. Delanaye
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引用次数: 3

摘要

慢性肾脏疾病的严重程度由肾小球滤过率(GFR)和蛋白尿(ACR)定义,并与心血管结局和终末期肾衰竭相关。然而,在记录中,蛋白尿(PCR)比ACR更常见。最近,人们建立了从PCR中估计ACR的方程。我们调查了他们在我们人群中的表现。方法回顾性分析我院当日ACR和PCR检测结果,并按KDIGO A1-A2-A3分类进行分级。Roche Cobas (R)分析仪收集了2,633份尿液分析(2018年5月至2019年5月),Abbott Alinity (A)分析仪收集了2,386份尿液分析(2019年5月至2020年3月)。我们比较了由Weaver’s和Sumida’s方程得出的mACR和eACR的KDIGO分期。结果中位年龄为63[52;71]/64[53;72]岁,其中43/42%为女性;78/74%患有糖尿病;mACR-A1占65.6%/64.2%,A2占25.5%/25.5%,A3占8.8%/10.3% (R/A法)。两个方程给出了eACR的KDIGO分期分布相似。无论分析人员或方程式如何,总体一致性都高于88%。根据多级AUC(多项逻辑回归模型),方程之间的性能等效。结论mACR和eACR之间的一致性良好,与公式或分析器无关。在KDIGO A1分类中,没有患者的ACR为a3。虽然ACR应在临床需要时测量,但可以通过这些方程从PCR中合理估计,用于流行病学回顾性研究或研究目的。
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Estimating urine albumin to creatinine ratio from protein to creatinine ratio using same day measurement: validation of equations
Abstract Objectives Severity of chronic kidney disease is defined by glomerular filtration rate (GFR) and albuminuria (ACR) by the KDIGO and are related to cardiovascular outcomes and end-stage-kidney-failure. However, proteinuria (PCR) is more often available than ACR in records. Recently, equations were developed to estimate ACR from PCR. We investigated their performances in our population. Methods In the academic medical hospital of Liège, we retrospectively analysed same day measurement of ACR and PCR and staged them according to the KDIGO A1-A2-A3 categories. Analyser Roche Cobas (R) gathered 2,633 urinalysis (May 2018-May 2019) and analyser Abbott Alinity (A) 2,386 urinalysis (May 2019-March 2020). We compared the KDIGO staging of mACR and eACR obtained from Weaver’s and Sumida’s equations. Results Median age was 63 [52;71]/64 [53;72] years old, 43/42% were female; 78/74% had diabetes; proportion of mACR-A1 was 65.6%/64.2%, A2 was 25.5%/25.5% and A3 was 8.8%/10.3% (Method R/A, respectively). Both equations gave similar distribution of KDIGO staging of eACR. Overall agreements were higher than 88% regardless of the analyser or of the equation. Performances in between equations were equivalent according to the multi-level AUC (multinomial logistic regression model). Conclusions Good concordance was observed between mACR and eACR regardless of the equation or of the analyser. No patient with an A3-measured ACR was estimated within the KDIGO A1 category. Though ACR should be measured when clinically needed, it may be reasonably estimated from the PCR through these equations, for epidemiologic retrospective studies or research purposes.
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