Ability of Procalcitonin and C-Reactive Protein for Discriminating between Bacterial and Enteroviral Meningitis in Children Using Decision Tree.

Bacterial meningitis (BM) is a public health burden in developing countries, including Central Asia. This disease is characterized by a high mortality rate and serious neurological complications. Delay with the start of adequate therapy is associated with an increase in mortality for patients with acute bacterial meningitis. Cerebrospinal fluid culture, as a gold standard in bacterial meningitis diagnosis, is time-consuming with modest sensitivity, and this is unsuitable for timely decision-making. It has been shown that bacterial meningitis differentiation from viral meningitis could be done through different parameters such as clinical signs and symptoms, laboratory values, such as PCR, including blood and cerebrospinal fluid (CSF) analysis. In this study, we proposed the method for distinguishing the bacterial form of meningitis from enteroviral one. The method is based on the machine learning process deriving making decision rules. The proposed fast-and-frugal trees (FFTree) decision tree approach showed an ability to determine procalcitonin and C-reactive protein (CRP) with cut-off values for distinguishing between bacterial and enteroviral meningitis (EVM) in children. Such a method demonstrated 100% sensitivity, 96% specificity, and 98% accuracy in the differentiation of all cases of bacterial meningitis in this study. These findings and proposed method may be useful for clinicians to facilitate the decision-making process and optimize the diagnostics of meningitis.

COVID-19 in the paediatric population of Kazakhstan.

Background: To date, there have been no studies of COVID-19 infection in children in Central Asia, particularly the Republic of Kazakhstan. This report analyses the epidemiological data on COVID-19 infection in children in Kazakhstan.Methods: The study included 650 paediatric patients diagnosed with COVID-19. Demographic and epidemiological data and the symptoms and radiological evidence of complications were collected and analysed. Children were sub-divided into four groups: neonates/infants, young children, older children and adolescents.Results: All of the 650 children were under 19 years of age, 56.3% of whom were male, and 122 (18.8%) were newborns and infants. The majority of cases (n = 558, 85.8%) were asymptomatic and only four cases were severe (0.6%). The symptoms were as follows in descending order: cough (14.8%), sore throat (12.8%), fever (9.1%) and rhinorrhoea (5.5%). Diarrhoea (2%), dyspnoea (1.8%) and muscle pain were rare (1.1%). Only three children required intensive care, including invasive ventilation. One patient had acute respiratory distress syndrome. There were no deaths.Conclusion: Most cases of COVID-19 infection in children in Kazakhstan were asymptomatic or the symptoms were mild. Only three patients required intensive care.