Paediatric meningitis in the conjugate vaccine era and a novel clinical decision model to predict bacterial aetiology.
Martin NG., Defres S., Willis L., Beckley R., Hardwick H., Coxon A., Kadambari S., Yu L-M., Liu X., Galal U., Conlin K., Griffiths MJ., Kneen R., Nadel S., Heath PT., Kelly DE., Solomon T., Sadarangani M., Pollard AJ., UK-ChiMES and ENCEPH-UK study groups None.
OBJECTIVES: The aims of this study were to assess aetiology and clinical characteristics in childhood meningitis, and develop clinical decision rules to distinguish bacterial meningitis from other similar clinical syndromes. METHODS: Children aged <16 years hospitalised with suspected meningitis/encephalitis were included, and prospectively recruited at 31 UK hospitals. Meningitis was defined as identification of bacteria/viruses from cerebrospinal fluid (CSF) and/or a raised CSF white blood cell count. New clinical decision rules were developed to distinguish bacterial from viral meningitis and those of alternative aetiology. RESULTS: The cohort included 3002 children (median age 2·4 months); 1101/3002 (36·7%) had meningitis, including 180 bacterial, 423 viral and 280 with no pathogen identified. Enterovirus was the most common pathogen in those aged <6 months and 10-16 years, with Neisseria meningitidis and/or Streptococcus pneumoniae commonest at age 6 months to 9 years. The Bacterial Meningitis Score had a negative predictive value of 95·3%. We developed two clinical decision rules, that could be used either before (sensitivity 82%, specificity 71%) or after lumbar puncture (sensitivity 84%, specificity 93%), to determine risk of bacterial meningitis. CONCLUSIONS: Bacterial meningitis comprised 6% of children with suspected meningitis/encephalitis. Our clinical decision rules provide potential novel approaches to assist with identifying children with bacterial meningitis. FUNDING: This study was funded by the Meningitis Research Foundation, Pfizer and the NIHR Programme Grants for Applied Research.