Utilizing metagenomic next-generation sequencing to diagnose central nervous system infections after craniotomy
DOI:
https://doi.org/10.3855/jidc.21771Keywords:
mNGS, CNS, postoperative, infection, meningitisAbstract
Introduction: Postoperative central nervous system (CNS) infections in craniotomy patients diagnosed through clinical signs and cerebrospinal fluid (CSF) bacterial culture, pose a challenge due to the morbidity and mortality of bacterial meningitis. The objective of this study was to evaluate the clinical value of metagenomic next-generation sequencing (mNGS) in diagnosing CNS infections post craniotomy.
Methodology: A prospective study compared mNGS with traditional diagnostics from January 2021 to October 2023. Patients with suspected post-craniotomy intracranial infections were enrolled, following guidelines and regulations.
Results: mNGS and traditional culture diagnosed 111 patients with suspected intracranial infections. mNGS showed higher sensitivity (62.5% vs. 25%). Traditional culture excelled in specificity and positive predictive value. Of the 18 mNGS-positive samples, 12 were culture-negative. mNGS detected pathogens such as Candida albicans (2 cases), Enterobacter cloacae (1 case), Enterococcus faecalis (1 case), Klebsiella pneumoniae (2 cases), Pseudomonas aeruginosa (1 case), Staphylococcus aureus (2 cases), Staphylococcus epidermidis (2 cases), and Streptococcus haemolyticus (1 case). Some pathogens were likely missed due to prior antibiotic use and fastidious growth requirements. Physicians adjusted treatments based on mNGS pathogen detection for culture-negative patients. Empirical therapy continued for patients with negative results until more diagnostic information was available.
Conclusions: mNGS detects post-neurosurgery CNS infections, especially hard-to-cultivate microorganisms. While mNGS has advantages, traditional culture's higher positive predictive value confirms infections and remains indispensable. Combining mNGS with traditional methods provides a comprehensive diagnostic strategy, aiding physicians in accurately identifying infections, reducing misdiagnosis, and offering personalized treatment plans to improve outcomes and quality of life.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Jin Wang, Bingjie Jiang

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Funding data
-
Quzhou Municipal Science and Technology Bureau
Grant numbers 2021022

