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Diagnostic Clinical and Laboratory Findings in Response to Predetermining Bacterial Pathogen: Data from the Meningitis Registry

BACKGROUND: Childhood Meningitis continues to be an important cause of mortality in many countries. The search for rapid diagnosis of acute bacterial meningitis has lead to the further exploration of prognostic factors. This study was scheduled in an attempt to analyze various clinical symptoms as w...

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Detalles Bibliográficos
Autores principales: Karanika, Maria, Vasilopoulou, Vasiliki A., Katsioulis, Antonios T., Papastergiou, Panagiotis, Theodoridou, Maria N., Hadjichristodoulou, Christos S.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2714179/
https://www.ncbi.nlm.nih.gov/pubmed/19641629
http://dx.doi.org/10.1371/journal.pone.0006426
Descripción
Sumario:BACKGROUND: Childhood Meningitis continues to be an important cause of mortality in many countries. The search for rapid diagnosis of acute bacterial meningitis has lead to the further exploration of prognostic factors. This study was scheduled in an attempt to analyze various clinical symptoms as well as rapid laboratory results and provide an algorithm for the prediction of specific bacterial aetiology of childhood bacterial meningitis. METHODOLOGY AND PRINCIPAL FINDINGS: During the 32 year period, 2477 cases of probable bacterial meningitis (BM) were collected from the Meningitis Registry (MR). Analysis was performed on a total of 1331 confirmed bacterial meningitis cases of patients aged 1 month to 14 years. Data was analysed using EPI INFO (version 3.4.3-CDC-Atlanta) and SPSS (version 15.0 - Chicago) software. Statistically significant (p<0.05) variables were included in a conditional backward logistic regression model. A total of 838 (63.0%) attributed to Neisseria meningitidis, 252 (18.9%) to Haemophilus influenzae, 186 (14.0%) to Streptococcus pneumoniae and 55 (4.1%) due to other bacteria. For the diagnosis of Meningococcal Meningitis, the most significant group of diagnostic criteria identified included haemorrhagic rash (OR 22.36), absence of seizures (OR 2.51), headache (OR 1.83) and negative gram stain result (OR 1.55) with a Positive Predictive Value (PPV) of 96.4% (95%CI 87.7–99.6). For the diagnosis of Streptococcus pneumoniae, the most significant group of diagnostic criteria identified included absence of haemorrhagic rash (OR 13.62), positive gram stain (OR 2.10), coma (OR 3.11), seizures (OR 3.81) and peripheral WBC≥15000/µL (OR 2.19) with a PPV of 77.8% (95%CI 40.0–97.2). For the diagnosis of Haemophilus influenzae, the most significant group of diagnostic criteria included, absence of haemorrhagic rash (OR 13.61), age≥1year (OR 2.04), absence of headache (OR 3.01), CSF Glu<40 mg/dL (OR 3.62) and peripheral WBC<15000/µL (OR 1.74) with a PPV of 58.5% (95%CI 42.1–73.7). CONCLUSIONS: The use of clinical and laboratory predictors for the assessment of the causative bacterial pathogen rather than just for predicting outcome of mortality seems to be a useful tool in the clinical management and specific treatment of BM. These findings should be further explored and studied.