4.7 Article

Metagenomic next-generation sequencing indicates more precise pathogens in patients with pulmonary infection: A retrospective study

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fcimb.2022.977591

关键词

metagenomic next-generation sequencing; bronchoalveolar lavage fluid; pulmonary infection; etiology diagnosis; comorbidities

资金

  1. National Natural Science Foundation of China
  2. [81860011]

向作者/读者索取更多资源

This study evaluated the diagnostic performance of metagenomic next-generation sequencing (mNGS) in patients with suspected pulmonary infection and found that mNGS can greatly enhance the accuracy and detection rate of pathogens. Comorbidities and types of pathogens should be taken into consideration when interpreting the results of mNGS.
BackgroundTimely 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. MethodsFrom 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. ResultsThe 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. ConclusionmNGS 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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据