Clinical application of metagenomic next-generation sequencing in the diagnosis of severe pneumonia pathogens
2025
Raojuan Huang | Ying Zhang | Caitao Dong | Jingdi Chen | Handong Zou | Yang Liu | Mengmeng Guo | Hang Gao | Quan Ke | Wei Wu
BackgroundSevere pneumonia is a significant cause of mortality among ICU patients. Metagenomic next-generation sequencing (mNGS) is an advanced, comprehensive, unbiased diagnostic tool for pathogen identification in infectious diseases. This study aimed to evaluate the clinical efficacy of mNGS for diagnosing severe pneumonia.MethodsThis study retrospectively analyzed 323 patients with suspected severe pneumonia admitted to the intensive care unit (ICU) of Wuhan University Renmin Hospital between January 2022 and December 2023. Bronchoalveolar lavage fluid (BALF) samples were collected from all 323 patients, and blood samples were obtained from 80 patients. Both mNGS and conventional microbial testing (CMT) were performed on the collected BALF and blood samples to analyze the pathogen spectrum. The diagnostic performance of mNGS and CMT was systematically evaluated and compared.ResultsThe overall positivity rate of mNGS was significantly greater than that of CMT (93.5% vs. 55.7%, p < 0.001). mNGS demonstrated significantly greater sensitivity than did CMT (94.74% vs. 57.24%, p < 0.001) but lower specificity (26.32% vs. 68.42%, p < 0.01). mNGS identified 36 bacterial species, 14 fungal species, 7 viral species, and 1 Chlamydia species, whereas CMT detected 21 bacterial species and 9 fungal species. According to the pathogen spectrum, Klebsiella pneumoniae, Acinetobacter baumannii, and Candida albicans were the predominant pathogens associated with severe pneumonia. The detection rate of mixed infections was significantly higher with mNGS than with CMT (62.8% vs. 18.3%, p < 0.001).ConclusionsCompared with CMT methods, mNGS has significant advantages in pathogen detection for severe pneumonia. Owing to its broad detection range and high sensitivity, mNGS serves as a valuable complementary approach to traditional culture-based methods.
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