Kravets N. Ya.

MICROBIOLOGICAL PREDICTORS OF CLINICAL COURSE OF ACUTE TONSILLITIS: APPLICATION OF LINEAR DISCRIMINANT ANALYSIS

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About the author:

Kravets N. Ya.

Heading:

MICROBIOLOGY

Type of article:

Scientific article

Annotation:

Acute tonsillitis is one of the most common infectious diseases affecting the ears, nose and throat (ENT) organs. The difficulty in distinguishing between viral and bacterial causes affects the choice of treatment. Despite progress in studying the disease, the lack of standardised approaches to predicting complications means personalised methods are necessary, including those based on the microbial profile. The aim of the study is to identify microbiological predictors of the clinical course of acute tonsillitis by analysing the microbiota of the palatine tonsils, to determine the relationship between the bacterial profile and key clinical signs (pain intensity and duration of the disease), and to build models for classifying forms of tonsillitis using linear discriminant analysis. Rapid immunochromatographic tests and bacteriological analysis of smears were used to identify the etiological agent of acute tonsillitis. Statistical modelling methods were employed in the study, including linear discriminant analysis. Clinical assessment was performed using the Centor scale, the Centor/McIsaac scale, and the visual analogue scale (VAS) for pain. The results of this study reveal the relationship between the clinical manifestations of acute tonsillitis and its viral and bacterial aetiology. The characteristic taxonomic composition of the oropharyngeal microbiota was identified, with certain groups of microorganisms proving dominant. Linear discriminant analysis enabled us to identify key microbiological and clinical predictors affecting the duration of the disease and pain intensity.

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Bibliography:

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Publication of the article:

«Bulletin of problems biology and medicine», 2025 Issue 3,178, 350-357 pages, index UDC 616.322:094-002.07:519.237.5

DOI:

10.29254/2077-4214-2025-3-178-350-357