Diagnostic performance and clinical utility of metagenomic next-generation sequencing in suspected pulmonary infections: a comparative study stratified by immune status.

Background: Pulmonary infections represent a significant global health concern, contributing substantially to morbidity and mortality worldwide. Metagenomic next-generation sequencing (mNGS) represents an advanced, comprehensive, and unbiased diagnostic approach for pathogen identification, effectively overcoming many limitations inherent in conventional diagnostic methods. This study aimed to systematically evaluate the clinical performance of mNGS in the etiological diagnosis of pulmonary infections, with a particular emphasis on its utility across diverse immune statuses. Methods: This retrospective study included 136 patients with suspected pulmonary infections admitted to the Department of Respiratory Medicine at Shandong Provincial Hospital from June 2023 to April 2025. Bronchoalveolar lavage fluid (BALF) samples were collected from all patients and concurrently subjected to mNGS and conventional microbiological testing (CMT). The pathogen detection spectrum and diagnostic performance of mNGS were systematically compared against those of CMT. Results: mNGS exhibited a significantly higher overall pathogen detection rate compared to CMT (77.2% vs. 50.0%, P < 0.001). Regarding the pathogen spectrum, mNGS identified a broader array of microorganisms, encompassing 19 bacterial, 9 fungal, and 2 mycobacterial species, in contrast to the 11 bacterial, 5 fungal, and 1 mycobacterial species detected by CMT. Diagnostic performance analysis further revealed that mNGS sensitivity was significantly superior to that of CMT (74.6% vs. 46.7%, P < 0.001). Furthermore, mNGS demonstrated a distinct advantage in detecting mixed infections, with a detection rate of 19.1%, significantly exceeding that of CMT (8.8%, P < 0.05). Subgroup analysis indicated a significantly higher incidence of mixed infections in immunocompromised patients compared to immunocompetent patients (35.1% vs. 13.1%, P < 0.05). Additionally, immunocompromised patients were more frequently subjected to adjustments in antimicrobial therapy guided by mNGS results (56.8% vs. 35.4%, χ² = 5.094, P < 0.05). Conclusions: In conclusion, mNGS offers superior sensitivity and broader pathogen coverage for the etiological diagnosis of pulmonary infections compared to conventional microbiological testing. Its enhanced capability to detect mixed infections significantly improves diagnostic accuracy in immunocompromised patients and effectively facilitates the dynamic optimization of antimicrobial therapy. Serving as a powerful complement to traditional diagnostic methods, mNGS holds particular value for the rapid diagnosis of complex and immunosuppression-associated pulmonary infections.