Vaginal infections, medically termed vaginitis, encompass a spectrum of symptomatic presentations arising from disturbances within the vaginal microflora. The conventional diagnostic approach relies on microscopic examination of wet preparation of vaginal discharge, considered the ‘gold standard’ in clinical practice. Complementary to this, culture-based methodologies are often employed to reinforce diagnostic accuracy. However, challenges such as subjectivity in result interpretation, resource-intensive requirements regarding skilled personnel, and reagent utilization underscore the need for alternative diagnostic strategies.In this article, we demonstrate surface-enhanced Raman spectroscopy (SERS) and partial least squares regression (PLSR) techniques to elucidate the molecular signatures present in vaginal fluids, accounting for various influencing factors, including disruptions in the natural microflora, vaginal irrigation practices, and contraceptive usage. Furthermore, we investigated the spectral manifestations associated with vulvovaginal candidiasis (VVC) relative to control samples. Each clinical specimen underwent meticulous characterization encompassing microbial composition, pH levels, purity, and other pertinent parameters.Our findings unveil significant associations between extraneous inflammatory factors such as vaginal irrigation and diminished sample purity with alterations in SERS signals. Conversely, the day of the menstrual cycle phase exhibits negligible influence on spectral profiles. Notably, VVC samples demonstrated diverse spectral responses correlating with the abundance of pathogenic bacteria. These explorations hold promise in paving the path towards developing a novel intrinsic framework for the diagnosis of vaginitis.
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