Pediatric meningoencephalitis in the molecular diagnostic era: epidemiological insights from 1198 suspected cases in Germany between 2016 and 2024
摘要
The epidemiology of suspected pediatric meningoencephalitis has changed in the era of conjugate vaccines and multiplex PCR. Updated epidemiologic data are needed to adapt diagnostic and therapeutic algorithms to current practice.
MethodsThis retrospective single-center study included children < 18 years who underwent lumbar puncture with cerebrospinal fluid multiplex PCR for suspected central nervous system infection at a tertiary pediatric hospital in Germany between 2016 and 2024. Clinical, laboratory, and outcome data were extracted from electronic medical records. Cerebrospinal fluid was analyzed using the BioFire® FilmArray® Meningitis/Encephalitis Panel. Statistical analyses included descriptive statistics, nonparametric comparisons, and receiver operating characteristic analyses.
ResultsAmong 1,198 children, definite bacterial meningitis was diagnosed in 13 (1.1%), definite viral meningitis in 80 (6.7%), aseptic meningitis of unknown etiology in 131 (11.0%), confirmed/probable encephalitis in 53 (4.4%), and possible encephalitis in 34 (2.8%). Bacterial meningitis represented 5.8% of meningitis cases. A causative pathogen was identified in all bacterial cases, most commonly Streptococcus pneumoniae (n = 7). Enterovirus (n = 52) and parechovirus (n = 9) predominated in viral meningitis, while an infectious etiology was identified in only 13/53 confirmed/probable encephalitis cases. The Bacterial Meningitis Score showed 80.0% sensitivity and 57.6% specificity. The recently published UK-ChiMES pre- and post-lumbar puncture scores demonstrated sensitivities of 84.6% and 76.9% and specificities of 86.3% and 92.7%, respectively.
ConclusionBacterial meningitis was rare, whereas viral and etiologically unresolved infections predominated despite routine multiplex PCR. Clinical prediction scores supported risk stratification, with the UK-ChiMES pre–lumbar puncture score showing the most favorable sensitivity–specificity balance.