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Accès ouvert déclaré 2024 article

Paediatric meningitis in the conjugate vaccine era and a novel clinical decision model to predict bacterial aetiology

13Citations signalées — pas une note de qualité
14Institutions déclarées
3Pays d’affiliation déclarés

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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.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Paediatric meningitis in the conjugate vaccine era and a novel clinical decision model to predict bacterial aetiology
Date Crossref
01/05/2024
Éditeur
Elsevier BV
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

Institutions déclarées

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Sujets associés

Bacterial Infections and VaccinesPneumonia and Respiratory InfectionsHerpesvirus Infections and Treatments

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