Abstract
The microbiome of healthy female reproductive tract is dominated by bacteria producing lactic acid and hydrogen peroxide, which provide infection control by maintaining a low pH level. Qualitative and quantitative changes in the bacterial composition of the vaginal microbiome can lead to the pathology occurrence — bacterial vaginosis (BV). BV increases the risk of contracting sexually transmitted infections, such as HIV, gonococcal, chlamydial, papillomavirus infections, as well as negatively affects a woman's reproductive health. In pregnant women, BV can lead to chorioamnionitis and adverse pregnancy outcomes, including premature rupture of membranes and premature birth. Conventionally, clinical and microscopic methods have been used to diagnose BV. However, these methods require qualified personnel, time expenditure and are characterized by low sensitivity and specificity. Modern diagnostic capabilities, including highly sensitive and specific methods based on the identification of new biomarkers in the vaginal microbiome and vaginal metabolome, can significantly improve the BV diagnosis. The analytical review discusses promising areas of BV laboratory diagnostics. Besides, computer algorithms (AI) can be used to automate the BV diagnosis based on microscopy results. KEYWORDS: bacterial vaginosis, laboratory diagnostics, vaginal microbiome, artificial intelligence. FOR CITATION: Khryanin A.A. Bacterial vaginosis biomarkers: analytical review. Russian Journal of Woman and Child Health. 2023;6(4):374– 379 (in Russ.). DOI: 10.32364/2618-8430-2023-6-4-8.
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