Application of metagenomic next-generation sequencing in the diagnosis of pathogens in patients with diabetes complicated by community-acquired pneumonia

应用宏基因组二代测序技术诊断糖尿病合并社区获得性肺炎患者的病原体

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Abstract

To explore the clinical utility and optimal timing of metagenomic next-generation sequencing (mNGS) in diagnosing pathogens in patients with diabetes complicated by community-acquired pneumonia (CAP). The study included 50 hospitalized patients diagnosed with diabetes complicated by CAP who underwent conventional microbiological testing (CMT) and mNGS using bronchoalveolar lavage fluid. Among the 50 cases, 16% presented no respiratory symptoms. There were significant increases in inflammatory markers such as C-reactive protein, erythrocyte sedimentation rate, and interleukin-6, with patchy imaging changes being the most prevalent. The positive rates for pathogen detection by mNGS and CMTs were 78 and 21% (P < 0.05). The mNGS was significantly better than the CMTs in the detection of rare pathogens such as Anaerobes, Chlamydia psittaci, Legionella pneumophila, Mycobacterium bovis, Aspergillus fumigatus, and Pneumocystis japonicus (P < 0.05). After clinical interpretation, 85% (22/26) of viruses, 24% (9/37) of bacteria, and 25% (2/8) of fungi were non-pathogen organisms by mNGS. There was a significant difference in the rates of adjustment in anti-infection treatment strategies based on the pathogen detection results from CMTs and mNGS, which were 2 and 46%, respectively (P < 0.05). We found that mNGS was superior to CMTs in terms of the positive rate of pathogen detection, detecting mixed infection incidence, rare pathogen detection rates, and the adjustment of treatment strategies. However, mNGS results need to be interpreted in the context of the clinic.

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