Objectives: Confirming the diagnosis in viral central nervous system (CNS) infections can be difficult with the currently available diagnostic tools. Virus discovery cDNA-amplified fragment length polymorphism next-generation sequencing (VIDISCA-NGS) is a promising viral metagenomic technique that enables the detection of all viruses in a single assay. We performed a retrospective study on the diagnostic accuracy of VIDISCA-NGS in cerebrospinal fluid (CSF) of individuals with suspected CNS infections. Methods: Consecutive adult patients presenting to the Emergency Department or inpatients, who underwent a lumbar puncture for the suspicion of a CNS infection, were included if they were diagnosed with a viral CNS infection, or if a viral CNS infection was initially suspected but eventually a different diagnosis was made. A quantitative PCR panel of the most common causative viruses was performed on CSF of these patients as reference standard and compared with the results of VIDISCA-NGS, the index test. Results: We included 38 individuals with viral CNS infections and 35 presenting with suspected CNS infection for whom an alternative aetiology was finally established. Overall sensitivity and specificity were 52% (95% CI 31%–73%) and 100% (95% CI 91%–100%), respectively. One enterovirus, detected by VIDISCA-NGS, was only identified by quantitative PCR upon retesting. Additional viruses identified by VIDISCA-NGS consisted of GB virus C, human papillomavirus, human mastadenovirus C, Merkel cell polyoma virus and anelloviruses. Conclusion: In patients for whom routine diagnostics do not yield a causative pathogen, VIDISCA-NGS can be of additional value as it can detect a broader range of viruses, but it does not perform well enough to replace quantitativePCR.
Original languageEnglish
Pages (from-to)631.e7-631.e12
JournalClinical microbiology and infection
Issue number4
Early online date2020
Publication statusPublished - Apr 2021


  • Diagnosis
  • Diagnostic accuracy
  • Viral central nervous system infections
  • Viral metagenomics

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