Cargando…
Metagenomic next-generation sequencing indicates more precise pathogens in patients with pulmonary infection: A retrospective study
BACKGROUND: Timely identification of causative pathogens is important for the diagnosis and treatment of pulmonary infections. Metagenomic next-generation sequencing (mNGS), a novel approach to pathogen detection, can directly sequence nucleic acids of specimens, providing a wide range of microbial...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585196/ https://www.ncbi.nlm.nih.gov/pubmed/36275015 http://dx.doi.org/10.3389/fcimb.2022.977591 |
Sumario: | BACKGROUND: Timely identification of causative pathogens is important for the diagnosis and treatment of pulmonary infections. Metagenomic next-generation sequencing (mNGS), a novel approach to pathogen detection, can directly sequence nucleic acids of specimens, providing a wide range of microbial profile. The purpose of this study was to evaluate the diagnostic performance of mNGS in the bronchoalveolar lavage fluid (BALF) of patients with suspected pulmonary infection. METHODS: From April 2019 to September 2021, 502 patients with suspected pneumonia, who underwent both mNGS of BALF and conventional microbiological tests (CMTs), were classified into different groups based on comorbidities. The diagnostic performances of mNGS and CMTs were compared. Comprehensive clinical analysis was used as the reference standard. RESULTS: The diagnostic accuracy and sensitivity of mNGS were 74.9% (95% confidence interval [CI], 71.7-78.7%) and 72.5% (95% CI, 68.2-76.8%) respectively, outperformed those of CMTs (36.9% diagnostic accuracy, 25.4% sensitivity). For most pathogens, the detection rate of mNGS was higher than that of CMTs. Polymicrobial infections most often occurred in immunocompromised patients (22.1%). Only 2.3% patients without underlying diseases developed polymicrobial infections. Additionally, the spectrums of pathogens also varied among the different groups. We found the positive predictive values (PPV) to be dependent upon both the pathogen of interest as well as the immunologic status of the patient (e.g., the PPV of Mycobacterium tuberculosis was 94.9% while the PPV of Pneumocystis jirovecii in immunocompetent individuals was 12.8%). This information can help physicians interpret mNGS results. CONCLUSION: mNGS of BALF can greatly enhance the accuracy and detection rate of pathogens in patients with pulmonary infections. Moreover, the comorbidities and types of pathogens should be taken consideration when interpreting the results of mNGS. |
---|