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

• Published in: Annals of medicine (Helsinki) Vol. 57; no. 1; p. 2514093
• Main Authors: Sun, Yong, Guo, Kai, Tang, Jing, Zhao, Junjie, Zhang, Xiaojing, Yan, Youqin, Yuan, Lingmin, Zhang, Yi, Qiu, Canhu, Luo, Jian, Zhang, Weiwen, Fang, Honglong, Chen, Juan
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis 01.12.2025; Taylor & Francis Group
• Subjects: Aged; Anti-Bacterial Agents - therapeutic use; Female; High-Throughput Nucleotide Sequencing; Humans; Infectious Diseases; Intensive Care Units - statistics & numerical data; Invasive mechanical ventilation; lung microbial; Male; metagenomic next-generation sequencing; Microbiota - genetics; Middle Aged; Prognosis; pulmonary infection; Respiration, Artificial - adverse effects; Respiration, Artificial - methods; respiratory failure; Respiratory Insufficiency - microbiology; Respiratory Insufficiency - mortality; Respiratory Insufficiency - therapy; Respiratory Tract Infections - microbiology; Respiratory Tract Infections - mortality; Retrospective Studies; Risk Factors; respiratory failure; pulmonary infection; metagenomic next-generation sequencing; Invasive mechanical ventilation; lung microbial
• ISSN: 0785-3890; 1365-2060; 1365-2060
• DOI: 10.1080/07853890.2025.2514093

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. 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 ( =122) and non-survivors ( =35). Compared with the survivors, non-survivors had a significantly higher proportion of smokers, dyspnea, type I RF, blood urea nitrogen, and C-reactive protein ( < 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 ( < 0.05). 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.