Open Access
1 March 2016 Quantifying creatinine and urea in human urine through Raman spectroscopy aiming at diagnosis of kidney disease
Cassiano Junior Saatkamp, Maurício Liberal de Almeida, Jeyse Aliana Martins Bispo, Antonio Luiz Barbosa Pinheiro, Adriana Barrinha Fernandes, Landulfo Silveira Jr.
Author Affiliations +
Funded by: FAPESP, São Paulo Research Foundation (FAPESP), São Paulo Research Foundation, São Paulo Research Foundation—FAPESP, Instituto Esperança de Educação Superior (IESPES)
Abstract
Due to their importance in the regulation of metabolites, the kidneys need continuous monitoring to check for correct functioning, mainly by urea and creatinine urinalysis. This study aimed to develop a model to estimate the concentrations of urea and creatinine in urine by means of Raman spectroscopy (RS) that could be used to diagnose kidney disease. Midstream urine samples were obtained from 54 volunteers with no kidney complaints. Samples were subjected to a standard colorimetric assay of urea and creatinine and submitted to spectroscopic analysis by means of a dispersive Raman spectrometer (830 nm, 350 mW, 30 s). The Raman spectra of urine showed peaks related mainly to urea and creatinine. Partial least squares models were developed using selected Raman bands related to urea and creatinine and the biochemical concentrations in urine measured by the colorimetric method, resulting in r=0.90 and 0.91 for urea and creatinine, respectively, with root mean square error of cross-validation (RMSEcv) of 312 and 25.2  mg/dL, respectively. RS may become a technique for rapid urinalysis, with concentration errors suitable for population screening aimed at the prevention of renal diseases.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE) 1083-3668/2016/$25.00 © 2016 SPIE
Cassiano Junior Saatkamp, Maurício Liberal de Almeida, Jeyse Aliana Martins Bispo, Antonio Luiz Barbosa Pinheiro, Adriana Barrinha Fernandes, and Landulfo Silveira Jr. "Quantifying creatinine and urea in human urine through Raman spectroscopy aiming at diagnosis of kidney disease," Journal of Biomedical Optics 21(3), 037001 (1 March 2016). https://doi.org/10.1117/1.JBO.21.3.037001
Published: 1 March 2016
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Cited by 82 scholarly publications and 1 patent.
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KEYWORDS
Urea

Raman spectroscopy

Statistical analysis

Magnesium

Remote sensing

Kidney

Biological research

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