Differential Diagnosis of Glycosuria Using Raman Spectroscopy

Author(s)

Sousa Vieira, E. E. ; Silveira Junior, L. ; Barrinha Fernandes, A. ; Bastos-Filho, TF ; Caldeira, EMD ; Frizera-Neto, A

• Document type: Journal article
• Source: XXVII BRAZILIAN CONGRESS ON BIOMEDICAL ENGINEERING, CBEB 2020; v. N/A, p. 6-pg., 2022-01-01.

Abstract

The aim of this research was to detect spectral differences in glycemic components. Urine samples were collected from 40 patients who were divided into a control group and a diabetic and hypertensive group. The samples were obtained in the morning, fasting, and stored a freezer at - 80 degrees C until spectral analysis. Spectral data collection was performed using a dispersive Raman spectrometer (Dimension P-1 model, Lambda Solutions, Inc., MA, USA). The equipment uses a stabilized multimode diode laser operating at 830 nm, with about 300 mW power output, and time integration to collect the Raman signal was adjusted to 5 s. The mean Raman spectra displaced from the urine of patients in the study groups (CT and DM & HBP) were identified at the range of 516 and 1127 cm(-1). Comparative analysis of mean urine spectra showed a significant difference (p < 0.05) between the groups, the Student's t-test was used to compare the mean Raman spectra of the groups. The comparative analysis of peak intensities at 516 and 1127 cm(-1) in the urine of diabetic control and hypertensive patients revealed that it was higher in the DM & HBP group than in the CT group, however, with no significant difference (p > 0.05). To quantify the glucose in urine and discriminate the groups, a model was developed to estimate the concentration using a quantitative regression model based on partial least squares (PLS). According to the data obtained, there was an excellent correlation (r = 0.98) between the concentrations estimated by the model and the concentrations determined by colorimetric analysis. Discriminant analysis (DA) based on a regression model (PLS) proved to be promising as it discriminated the control group without errors, and the rate in the DM & HBP group was 89.1%. Raman spectroscopy can be a potentially useful tool for testing glucose in urine. (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