Changes of respiratory microbiota associated with prognosis in pulmonary infection patients with invasive mechanical ventilation-supported respiratory failure

Background Respiratory failure (RF) is an important cause of intensive care unit (ICU) admission and mortality due to respiratory diseases. This study aimed to evaluate the clinical performance of metagenomic next-generation sequencing (mNGS) testing in pathogen diagnosis, medication guidance and to...

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Main Authors: Yong Sun, Kai Guo, Jing Tang, Junjie Zhao, Xiaojing Zhang, Youqin Yan, Lingmin Yuan, Yi Zhang, Canhu Qiu, Jian Luo, Weiwen Zhang, Honglong Fang, Juan Chen
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Annals of Medicine
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Online Access:https://www.tandfonline.com/doi/10.1080/07853890.2025.2514093
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Summary:Background Respiratory failure (RF) is an important cause of intensive care unit (ICU) admission and mortality due to respiratory diseases. This study aimed to evaluate the clinical performance of metagenomic next-generation sequencing (mNGS) testing in pathogen diagnosis, medication guidance and to explore dynamic changes in the respiratory microbiota associated with prognosis.Methods This multicenter retrospective study enrolled ICU patients from five hospitals who underwent invasive mechanical ventilation (IMV) and had pathogenic microorganisms identified by both mNGS and conventional microbiological tests (CMT) from December 2021 to April 2024. Patients were classified into two groups based on discharge outcomes: survivors (n=122) and non-survivors (n=35).Results Compared with the survivors, non-survivors had a significantly higher proportion of smokers, dyspnea, type I RF, blood urea nitrogen, and C-reactive protein (p < 0.05). All the above indicators were identified as independent risk factors for mortality, except for type I RF. mNGS showed a better performance for pathogen identification than CMT in both groups, and nearly 60% showed consistent results between the two methods. Among survivors, antibiotic adjustment was mainly based on mNGS results (35.25%), whereas non-survivors more frequently received adjustments based on mNGS and CMT results (34.29%). The richness and abundance of lung microorganisms in the non-survivors were significantly lower than those in the survivors (p < 0.05).Conclusions mNGS is a promising method for identifying pathogens in pulmonary infections in IMV-supported RF patients and for exploring changes in lung microbial composition to provide a reference for patient prognosis.
ISSN:0785-3890
1365-2060