Clinical utility of metagenomic next-generation sequencing on bronchoalveolar lavage fluid in diagnosis of lower respiratory tract infections

Background In this study, we aimed to evaluate the clinical utility of Metagenomic Next-Generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) in diagnosis of Lower Respiratory Tract Infections (LRTIs). Methods In this study, we retrospectively analyzed 186 hospitalized patients who were suspected with LRTIs and performed mNGS (DNA) test of BALF simultaneously at The Fifth Affiliated Hospital of Sun Yat-Sen University from March 2023 to August 2023. Suspected LRTI was based on LRTI related clinical manifestations or imaging examination. Among them, 155 patients had undergone conventional culture and mNGS (DNA) testing simultaneously. Finally, 138 cases (89.03%,138/155) were diagnosed as LRTI and 17 cases (10.97%,17/155) were diagnosed as non-LRTI. Both detecting rate and diagnostic efficacy of mNGS and conventional culture were compared. Results The positive detection rates of pathogens between mNGS and conventional culture were significant different (81.29% VS 39.35%, P < 0.05). Compared with paired conventional culture result, the sensitivity of mNGS in diagnosis of LRTIs was more superior (88.41% VS 43.48%; P < 0.05), the specificity was opposite (76.47% VS 94.12%; P > 0.05). Furthermore, 77.54% and 35.51% of LRTI cases were being etiologically diagnosed by mNGS and culture respectively. Importantly, mNGS directly led to a change of treatment regimen in 58 (37.42%) cases, including antibiotic adjustment (29.68%) and ruling out active infection (7.74%). Moreover, treatment regimen remained unchanged in 97 (62.58%) cases, considering the current antibiotic therapy already covered the detected pathogens (36.13%) or empirical treatment was effective (11.61%). Conclusions mNGS can identify a wide range of pathogens in LRTIs, with improved sensitivity and being more superior at diagnosing LRTIs etiologically. mNGS has the potential to enhance clinical outcomes by optimizing the treatment regimens.