Characterization of microorganisms according to vaginal community state types microbiota: an observational study among women across Italy

This manuscript presents an observational analysis of vaginal microbiota profiles in an Italian clinical cohort (n≈203) assessed through a targeted molecular testing workflow (RT-PCR–based panel with a standardized interpretative algorithm). Samples were classified into vaginal Community State Types (CST) and stratified by dysbiosis severity (normal, partial dysbiosis, dysbiosis), enabling a population-level characterization of microbial patterns in real-world diagnostic practice. The study reports the prevalence of key microbial targets across CSTs and dysbiosis strata, explores co-detection patterns through association metrics, and investigates demographic and microbiological correlates of dysbiosis using logistic regression models. Results highlight age-related trends in dysbiosis distribution and identify specific microbial detections and co-detection profiles associated with non-eubiotic states, providing a hypothesis-generating framework for clinical interpretation of molecular panels in women’s health. Limitations include the cross-sectional design and the constrained availability of clinical covariates, which restrict causal inference and motivate future longitudinal and multi-center validation. Overall, the work contributes pragmatic evidence on CST-like profiling and dysbiosis stratification using targeted molecular diagnostics, with potential applications in clinical microbiology and gynecological practice.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-22
DOI
https://doi.org/10.5281/zenodo.19699519
Primary Topic
Reproductive tract infections research
Type
article
Field-Weighted Citation Impact
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article

Characterization of microorganisms according to vaginal community state types microbiota: an observational study among women across Italy

Daniele Armenia, Riccardo Giannico, Ettore Palma, S. Brizi et al.
Zenodo (CERN European Organization for Nuclear Research)
Reproductive tract infections research
article

Characterization of microorganisms according to vaginal community state types microbiota: an observational study among women across Italy

Daniele Armenia, Riccardo Giannico, Ettore Palma, S. Brizi, Yagaï Bouba, Martina Di Lullo, Graziella Calugi, Francesca Blandino, Noemi Meschino, Luca Forlani
article en

Abstract

This manuscript presents an observational analysis of vaginal microbiota profiles in an Italian clinical cohort (n≈203) assessed through a targeted molecular testing workflow (RT-PCR–based panel with a standardized interpretative algorithm). Samples were classified into vaginal Community State Types (CST) and stratified by dysbiosis severity (normal, partial dysbiosis, dysbiosis), enabling a population-level characterization of microbial patterns in real-world diagnostic practice. The study reports the prevalence of key microbial targets across CSTs and dysbiosis strata, explores co-detection patterns through association metrics, and investigates demographic and microbiological correlates of dysbiosis using logistic regression models. Results highlight age-related trends in dysbiosis distribution and identify specific microbial detections and co-detection profiles associated with non-eubiotic states, providing a hypothesis-generating framework for clinical interpretation of molecular panels in women’s health. Limitations include the cross-sectional design and the constrained availability of clinical covariates, which restrict causal inference and motivate future longitudinal and multi-center validation. Overall, the work contributes pragmatic evidence on CST-like profiling and dysbiosis stratification using targeted molecular diagnostics, with potential applications in clinical microbiology and gynecological practice.

Zenodo (CERN European Organization for Nuclear Research)
Saint Camillus International University of Health and Medical Sciences (IT), Eurofins (France) (FR), International Society of Nephrology (BE)
Gender equality
Openalex Percentile: Top 7%
Reproductive tract infections research
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