Infrared spectroscopy and multivariate analysis applied to the differential diagnosis of leptospirosis and dengue

Abstract

Dengue and leptospirosis are considered systemic and very dynamic illnesses in which a patient can rapidly progress from mild to severe conditions. Both diseases present very similar acute initial symptoms, a fact that may result in a challenging differential diagnosis at the initial phases. Herein, we present the application of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy combined with multivariate analysis to perform differential diagnosis of leptospirosis and dengue by analysing blood plasma. The spectra of 114 samples from patients in different phases of infection (n = 43 for leptospirosis and n = 71 for dengue) were analysed by either linear or quadratic discrimination in association with genetic algorithms, successive projection algorithms and principal component analysis for feature selection/extraction. The best model, GA-QDA, achieved outstanding results in terms of maximum (100%) sensitivity, specificity and accuracy for classifying both classes by using only 31 spectral variables. The ANOVA calculations, at a confidence level of 95%, highlighted a set of 10 variables selected by the GA-QDA model (1296 cm-1, 1612 cm-1, 1673 cm-1, 1677 cm-1, 1678 cm-1, 1689 cm-1, 1694 cm-1, 1711 cm-1, 1713 cm-1 and 1719 cm-1) with significant differences in the absorbance means between the Leptospirosis and Dengue classes. These specific wavenumbers represent the most useful spectral information accounting for the biochemical changes that mark a specific infection. These remarkable results obtained in this pilot study highlight the viability of this methodology to be applied in clinical practice to serve as a simple and accurate test for discriminating between the two illnesses.