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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Discrimination model applied to urinalysis of patients with diabetes and hypertension aiming at diagnosis of chronic kidney disease by Raman spectroscopy

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Author(s):
de Souza Vieira, Elzo Everton ; Martins Bispo, Jeyse Aliana ; Silveira, Jr., Landulfo ; Fernandes, Adriana Barrinha
Total Authors: 4
Document type: Journal article
Source: Lasers in Medical Science; v. 32, n. 7, p. 1605-1613, SEP 2017.
Web of Science Citations: 3
Abstract

Higher blood pressure level and poor glycemic control in diabetic patients are considered progression factors that cause faster decline in kidney functions leading to kidney damage. The present study aimed to develop a quantification model of biomarkers creatinine, urea, and glucose by means of selected peaks of these compounds, measured by Raman spectroscopy, and to estimate the concentration of these analytes in the urine of normal subjects (G\_N), diabetic patients with hypertension (G\_WOL) patients with chronic renal failure doing dialysis (G\_D). Raman peak intensities at 680 cm(-1) (creatinine), 1004 cm(-1) (urea), and 1128 cm(-1) (glucose) from normal, diabetic, and hypertensive and doing dialysis patients, obtained with a dispersive 830 nm Raman spectrometer, were estimated through Origin software. Spectra of creatinine, urea, and glucose diluted in water were also obtained, and the same peaks were evaluated. A discrimination model based on Mahalanobis distance was developed. It was possible to determine the concentration of creatinine, urea, and glucose by means of the Raman peaks of the selected biomarkers in the urine of the groups G\_N, G\_WOL, and G\_D (r = 0.9). It was shown that the groups G\_WOL and G\_D had lower creatinine and urea concentrations than the group G\_N (p < 0.05). The classification model based on Mahalanobis distance applied to the concentrations of creatinine, urea, and glucose presented a correct classification of 89% for G\_N, 86% for G\_WOL, and 79% for G\_D. It was possible to obtain quantitative information regarding important biomarkers in urine for the assessment of renal impairment in patients with diabetes and hypertension, and this information can be correlated with clinical criteria for the diagnosis of chronic kidney disease. (AU)

FAPESP's process: 09/01788-5 - Dispersive Raman spectroscopy using optical fibers "Raman probe" applied to the diagnosis of neoplasia in the skin and prostate
Grantee:Landulfo Silveira Junior
Support Opportunities: Regular Research Grants