Clinical application of metagenomic next-generation sequencing technology in the diagnosis and treatment of pulmonary infection pathogens: A prospective single-center study of 138 patients

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Abstract

Introduction: Rapid and accurate pathogen identification is essential for the treatment of pneumonia. Metagenomic next-generation sequencing (mNGS) is a newly developed technology to obtain microbial nucleic acid sequence information quickly, efficiently, and without bias. Methods: We performed shotgun metagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF) for pathogen identification in pneumonia in a prospective study with 138 patients from a single center. We compared the results of mNGS with standard methods including culture, staining, and targeted PCR and evaluated the clinical applicability of mNGS. Results: Most of the patients (128/138, 92.75%) were cured or improved. One patient (1/138, 0.72%) died because of acute gastrointestinal bleeding, and 9 patients (9/138, 6.52%) showed no improvement. mNGS identified more bacteria (53 versus 27), fewer fungi (8 versus 31), and more viruses (16 versus 1) than standard methods. In total, treatment in 34 out of 138 cases (24.64%) was adjusted and optimized because of mNGS results. Positive mNGS results contributed to a definitive diagnosis in 23 cases (16.67%), which helped guide treatment decision by either adjusting the antibiotics without de-escalation or continuing the empirical treatment. mNGS also confirmed no active infection in 11 cases (7.97%) allowed for antibiotic de-escalation. Conclusion: This prospective clinical study evaluated the clinical utility of mNGS for the diagnosis of pneumonia and showed that mNGS of BALF provides valuable information for effective treatment.

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Li, N., Ma, X., Zhou, J., Deng, J., Gu, C., Fei, C., … Tao, F. (2022). Clinical application of metagenomic next-generation sequencing technology in the diagnosis and treatment of pulmonary infection pathogens: A prospective single-center study of 138 patients. Journal of Clinical Laboratory Analysis, 36(7). https://doi.org/10.1002/jcla.24498

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