摘要:The elevation of neopterin in cerebrospinal fluid (CSF) has been reported in several neuroinflammatory disorders. However, it is not expected that neopterin alone can discriminate among different neuroinflammatory etiologies. We conducted an observational retrospective and case–control study to analyze the CSF biomarkers neopterin, total proteins, and leukocytes in a large cohort of pediatric patients with neuroinflammatory disorders. CSF samples from 277 subjects were included and classified into four groups: Viral meningoencephalitis, bacterial meningitis, acquired immune-mediated disorders, and patients with no-immune diseases (control group). CSF neopterin was analyzed with high-performance liquid chromatography. Microbiological diagnosis included bacterial CSF cultures and several specific real-time polymerase chain reactions. Molecular testing for multiple respiratory pathogens was also included. Antibodies against neuronal and glial proteins were tested. Canonical discriminant analysis of the three biomarkers was conducted to establish the best discriminant functions for the classification of the different clinical groups. Model validation was done by biomarker analyses in a new cohort of 95 pediatric patients. CSF neopterin displayed the highest values in the viral and bacterial infection groups. By applying canonical discriminant analysis, it was possible to classify the patients into the different groups. Validation analyses displayed good results for neuropediatric patients with no-immune diseases and for viral meningitis patients, followed by the other groups. This study provides initial evidence of a more efficient approach to promote the timely classification of patients with viral and bacterial infections and acquired autoimmune disorders. Through canonical equations, we have validated a new tool that aids in the early and differential diagnosis of these neuroinflammatory conditions.
其他摘要:Abstract The elevation of neopterin in cerebrospinal fluid (CSF) has been reported in several neuroinflammatory disorders. However, it is not expected that neopterin alone can discriminate among different neuroinflammatory etiologies. We conducted an observational retrospective and case–control study to analyze the CSF biomarkers neopterin, total proteins, and leukocytes in a large cohort of pediatric patients with neuroinflammatory disorders. CSF samples from 277 subjects were included and classified into four groups: Viral meningoencephalitis, bacterial meningitis, acquired immune-mediated disorders, and patients with no-immune diseases (control group). CSF neopterin was analyzed with high-performance liquid chromatography. Microbiological diagnosis included bacterial CSF cultures and several specific real-time polymerase chain reactions. Molecular testing for multiple respiratory pathogens was also included. Antibodies against neuronal and glial proteins were tested. Canonical discriminant analysis of the three biomarkers was conducted to establish the best discriminant functions for the classification of the different clinical groups. Model validation was done by biomarker analyses in a new cohort of 95 pediatric patients. CSF neopterin displayed the highest values in the viral and bacterial infection groups. By applying canonical discriminant analysis, it was possible to classify the patients into the different groups. Validation analyses displayed good results for neuropediatric patients with no-immune diseases and for viral meningitis patients, followed by the other groups. This study provides initial evidence of a more efficient approach to promote the timely classification of patients with viral and bacterial infections and acquired autoimmune disorders. Through canonical equations, we have validated a new tool that aids in the early and differential diagnosis of these neuroinflammatory conditions.