Differential Diagnosis of Bacterial and Viral Meningitis Using Dominance-Based Rough Set Approach

Abstract

Differential diagnosis of bacterial and viral meningitis remains an important clinical problem, particularly in the initial hours of hospitalization, before obtaining results of lumbar punction. We conducted a retrospective analysis of the medical records of 193 children hospitalized in St. Joseph Children’s Hospital in Poznan. In this study, we applied the original methodology of dominance-based rough set approach (DRSA) to induce diagnostic patterns from meningitis data and to represent them by decision rules useful in discriminating between bacterial and viral meningitis. The rule induction algorithm applied to this end is VC-DomLEM from jRS library. In the studied group of 193 patients, there were 124 boys and 69 girls, and the mean age was 94 months. The patients were characterized by 10 attributes, of which only 5 were used in 5 rules able to discriminate between bacterial and viral meningitis with an average precision of 98%, where C-reactive protein attribute (CRP) appeared to be the most valuable. Factors associated with bacterial meningitis were: CRP level ≥ 85 mg/l, or age < 2 months. Factors associated with viral meningitis were CRP level ≤ 60 mg/l and procalcytonin level < 0.5 ng/ml, or CRP level ≤ 84 mg/l and the presence of vomiting. We established a minimum set of attributes significant for classification of patients with bacterial or viral meningitis. These attributes are analyzed in just 5 rules able to distinguish almost perfectly between bacterial and viral meningitis without the need of lumbar punction.