The application value and limitations of metagenomic detection technology based on cerebrospinal fluid samples in...

Accurately diagnosing central nervous system (CNS) infections remains challenging. This study aimed to evaluate the effectiveness of metagenomic next-generation sequencing (mNGS) in diagnosing suspected CNS infections and its role in facilitating rapid and accurate pathogen identification.

This retrospective study enrolled cerebrospinal fluid specimens from 246 patients with suspected CNS infections and 20 controls with definitively ruled-out infections. Using clinical diagnoses established by an expert panel based on comprehensive criteria as the reference standard, we evaluated the diagnostic performance of mNGS relative to culture and conventional tests. Additionally, we analyzed the therapeutic guidance value of positive mNGS results and risk factors for false negatives.

mNGS showed 73.2% (180/246) agreement with clinical diagnosis, superior to culture (54.1%, 133/246) and conventional methods (61.4%, 151/246). For general bacteria and fungi, mNGS showed 61.9% (26/42) concordance with culture. False negatives in mNGS predominantly involved viral missed detection. Age, presence of systemic infection, headache, and cerebrospinal fluid glucose levels were likely key determinants of mNGS performance. mNGS detection of Epstein-Barr virus, Streptococcus spp., Mycobacterium tuberculosis complex, herpes simplex virus type 1, and Staphylococcus spp. suggested high pathogenic potential, whereas Torque teno virus detection more likely indicated carriage or experimental contamination.

mNGS holds significant value for the diagnosis, therapeutic management, and prognostic assessment of suspected CNS infections.