Application of metagenomic next-generation sequencing in pathogen detection of lung infections - Song Chen; Song Chen; Tanglin Ouyang; Tanglin Ouyang; Kaiyang Wang; Xuan Hou; Xuan Hou; Rong Zhang; Rong Zhang; Meiyong Li; Haibin Zhang; Qinghua He; et al. (Frontiers in Cellular and Infection Microbiology)
BackgroundMetagenomic next-generation sequencing (mNGS) has been widely reported to provide crucial information for the diagnosis and treatment of infectious diseases. In this study, we aimed to evaluate mNGS in pathogens diagnosis of lung infections.MethodsA total of 188 patients who were suspected of pulmonary infection and received medical treatment at the Second Affiliated Hospital of Nanchang University from August 2022 to December 2023 were enrolled in this study. Conventional microbiological tests (CMTs) and mNGS were employed for pathogens diagnosis.ResultsStatistical results indicated that mNGS were significantly better than CMTs in sensitivity, negative predictive value, and negative likelihood ratio. Remarkably, the positive detection rate of mNGS was significantly higher than that of CMTs (86.17% vs 67.55%, P < 0.01). Through mNGS, we identified 96 pathogens, comprising 59 bacteria, 18 fungi, 15 viruses, and 4 special pathogens. In contrast, CMTs detected 28 species, including 25 bacteria and 3 fungi. The effectiveness rate of antibiotic treatment decisions based on mNGS results was 40.60%. Out of 54 cases with positive treatment impacts, mNGS results contributed to the treatment and improved prognosis of 16 infections caused by atypical pathogens.ConclusionOur results proved the essential role of mNGS in lung infection diagnosis, enabling early detection and the prompt development of targeted anti-infection therapies. We recommended that the clinical application of mNGS can enhance treatment effectiveness and improve patient prognosis.