Use of Fourier transform infrared spectroscopy and chemometric analysis to predict the bacilloscopic index in the saliva of leprosy patients.

Leprosy is an infectious disease caused by the Mycobacterium leprae complex. Although the diagnosis of this disease is clinical, additional tests are often needed. One of the most common tests is intradermal smear bacilloscopy, which detects the patient's bacillary load. However, bacilloscopy is an invasive test and its results are subjective. The aim of this study was to propose a methodology based on Fourier transform infrared (FTIR) spectroscopy to predict the bacilloscopic index in the saliva of leprosy patients. A total of 88 saliva samples were included, and the bacilloscopic index of the patients was previously defined by intradermal smear bacilloscopy. The saliva samples were analyzed by attenuated total reflection (ATR)-FTIR; a supervised analysis with partial least squares regression (PLS), after orthogonal signal correction (OSC), was used to predict the bacilloscopic index. The PLS model with three latent variables and one OSC component obtained a coefficient of determination greater than 0.9999 in both the calibration and prediction sets. The model was able to predict the bacilloscopic indexes with a minimum error, demonstrating its robustness. Thus, modeling with ATR/FTIR and multivariate calibration using one OSC component showed high accuracy and reproducibility, overcoming the limitations of intradermal smear bacilloscopy and proving to be a promising method in the clinical management of patients with leprosy.