Shaw R A, Kotowich S, Mantsch H H, Leroux M
Institute for Biodiagnostics, National Research Council of Canada, Winnipeg, Manitoba, Canada.
Clin Biochem. 1996 Feb;29(1):11-19. doi: 10.1016/0009-9120(95)02011-x.
To determine the feasibility of near-infrared analysis for quantitating urea, creatinine, and protein in urine. Practical advantages of this method include ease of sample presentation and the absence of reagents or disposables.
The near-infrared methods were developed by first measuring the spectra of 123 different urine samples and, using independent clinical analyses, determining the protein, creatinine, and urea levels in each. Calibration models relating near-infrared spectroscopic features to those independently determined concentrations were optimized, and each model then validated using a set of 50 additional samples.
Standard errors of calibration were 14.4 mmol/L, 0.66 mmol/L, and 0.20 g/L, and standard errors of prediction 16.6 mmol/L, 0.79 mmol/L, and 0.23 g/L, respectively, for urea, creatinine, and protein.
Near-infrared urea quantitation is as accurate as the reference method, enzymatic (urease) conductivity, used here for calibration. Creatinine analysis is slightly less accurate relative to the reference (Jaffe rate) method; however, these errors can be minimized by careful attention to factors affecting precision. The accuracy of the near-infrared protein analysis cannot approach that of the reference method; nevertheless, the technique is potentially useful for coarse screening and for quantifying protein levels above 0.3 g/L.
确定近红外分析法对尿液中尿素、肌酐和蛋白质进行定量分析的可行性。该方法的实际优势包括样品呈现简便,且无需试剂或一次性用品。
开发近红外方法时,首先测量了123份不同尿液样本的光谱,并通过独立的临床分析确定每份样本中的蛋白质、肌酐和尿素水平。将近红外光谱特征与那些独立测定的浓度相关联的校准模型进行了优化,然后使用另外50份样本对每个模型进行验证。
尿素、肌酐和蛋白质的校准标准误差分别为14.4 mmol/L、0.66 mmol/L和0.20 g/L,预测标准误差分别为16.6 mmol/L、0.79 mmol/L和0.23 g/L。
近红外尿素定量分析与用于校准的参考方法(酶法(脲酶)电导率法)一样准确。相对于参考(贾菲速率)法,肌酐分析的准确性略低;然而,通过仔细关注影响精密度的因素,这些误差可以降至最低。近红外蛋白质分析的准确性无法达到参考方法的水平;尽管如此,该技术对于粗筛以及定量高于0.3 g/L的蛋白质水平可能是有用的。