Validation of a diagnosis model for differentiating bacterial from viral meningitis in infants and children under 3.5 years of age

The aim of this study was to validate, in a population of infants and child ren under 3.5 years of age, a diagnosis model that provides a figure for th e probability of bacterial meningitis (pABM), based on four parameters coll ected at the time of the first lumbar tap: the cerebrospinal fluid (CSF) pr otein level, CSF polymorphonuclear cell count, blood glucose level, and leu cocyte count. The best cut-off value for distinguishing between bacterial a nd viral meningitis was previously found to be 0.1, since 99% of meningitid es associated with pABM<0.1 were viral. The charts of 103 consecutive child ren aged 0.1-3.5 years who had been hospitalised for acute meningitis were reviewed. Each case was sorted into the following three categories for aeti ology: bacterial (positive CSF culture, n = 48); viral (negative CSF cultur e and no other aetiology, and no antibiotic treatment after diagnosis, n = 36); and undetermined (fitting neither of the first two definitions, n = 19 ). After computation of pABM values in each case, the predictive values of the model were calculated for different pABM cut-off values. The results co nfirmed that the best cut-off pABM value was 0.1, for which the positive an d negative predictive values in this model were 96% and 97%, respectively. Only one case of bacterial meningitis (lumbar tap performed early in an inf ant with meningococcal purpura fulminans with negative CSF culture) was ass ociated with a pABM value of <0.1. This model is quite reliable for differe ntiating between bacterial and viral meningitis in children under 3.5 years of age, and it may enable physicians to withhold antibiotics in cases of m eningitis of uncertain aetiology.