Validation of a Diagnosis Model for Differentiating Bacterial from Viral Meningitis in Infants and Children under 3.5 Years of Age

Abstract

The aim of this study was to validate, in a population of infants and children under 3.5 years of age, a diagnosis model that provides a figure for the probability of bacterial meningitis (pABM), based on four parameters collected at the time of the first lumbar tap: the cerebrospinal fluid (CSF) protein level, CSF polymorphonuclear cell count, blood glucose level, and leucocyte count. The best cut-off value for distinguishing between bacterial and viral meningitis was previously found to be 0.1, since 99% of meningitides associated with pABM<0.1 were viral. The charts of 103 consecutive children 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 aetiology: bacterial (positive CSF culture, n=48); viral (negative CSF culture 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 confirmed that the best cut-off pABM value was 0.1, for which the positive and negative predictive values in this model were 96% and 97%, respectively. Only one case of bacterial meningitis (lumbar tap performed early in an infant with meningococcal purpura fulminans with negative CSF culture) was associated with a pABM value of <0.1. This model is quite reliable for differentiating between bacterial and viral meningitis in children under 3.5 years of age, and it may enable physicians to withhold antibiotics in cases of meningitis of uncertain aetiology.

Clinical decision rules to distinguish between bacterial and aseptic meningitis

“…Mandatory 100% sensitivity was not reached with the rule developed by Jaeger et al (94% sensitivity), 19 because it failed to identify one of the 17 patients with bacterial meningitis that could be tested: a 3 year old boy with pneumococcal meningitis whose risk of having bacterial meningitis was 5% (below the pABM threshold of 10%), based on his blood WBC count (20 500/ mm 3 ), serum glucose concentration (3.5 mmol/l), CSF protein concentration (0.39 g/l), and CSF neutrophil count (225/mm 3 ). The rule developed by Oostenbrink et al achieved only 83% sensitivity because two of the 12 patients with bacterial meningitis that could be tested were not identified: both children had a clinical-biological score ,8.5 (no vomiting and no meningeal irritation at admission).…”

“…1 Some of our patients could not be used for the analysis of the rules developed by Jaeger et al 19 and Oostenbrink et al 14 (n = 53 and n = 47, including 3 and 8 bacterial meningitis, respectively), because a considerable amount of data is required to apply these rules, and some of the items (e.g. serum glucose at the time of the lumbar puncture) are not systematically recorded in our emergency room, as in other centres.…”

“…Both rules recommended treatment for patients with a pABM >10%. Jaeger and coworkers 19 Oostenbrink et al 14 combined two scores: a clinicalbiological score including the duration of the main complaint (1 point/day for a maximum of 10 points), vomiting (2 points), meningeal irritation (7.5 points), cyanosis (6.5 points), petechiae (4 points), altered consciousness (8 points), C reactive protein (CRP) value (0.5 points per 50 mg/l for a maximum of 2 points if CRP >200 mg/l), and a CSF score based on the CSF neutrophil count (1 point/ 10 log cells (ml)) and CSF/serum glucose ratio (20.5 point/10% for a minimum of 25 points). Antibiotics were recommended according to a grid of values for each partial score.…”

Epidemiology, Diagnosis, and Antimicrobial Treatment of Acute Bacterial Meningitis

“…Although these data are suggestive that this score is an accurate decision support tool, practice guidelines from the Infectious Diseases Society of America recommend that these prediction rules should not be used for clinical decisions for individual patients (311). One additional aspect of particular importance to physicians working in emergency medicine and other urgent outpatient settings is that all of the studies were performed with hospitalized patients (38,39,149,161,188). Therefore, in all of the studies evaluating the potential to differentiate bacterial from viral meningitis, every patient was admitted to the hospital for observation regardless of whether or not they received antibiotics (106).…”

How to differentiate bacterial from viral meningitis

“…Since no single CSF or blood parameter has been able to discriminate between bacterial and viral meningitis, a model for the differential diagnosis has been introduced by Spanos et al [7] and validated in more recent series [12, 13,14]. Four independent variables are used here to calculate the probability of bacterial (pABM, i.e., odds of bacterial relative to viral meningitis) vs. viral meningitis, namely CSF protein level, total CSF polymorphonuclear count, blood glucose level, and leukocyte count.…”