Browsing by Subject "Epstein–Barr virus"

In diagnosis of many viral and some other microbial infections, measurement of IgG avidity is a globally emerging approach for identifying primary infections and estimating the time of clinical onset. While many calculation methods have been introduced for conversion of the raw data into a numerical avidity value, little information exists on their comparison and whether the complex and laborious ones show superior performance. We here compare diverse approaches for avidity calculation, and introduce for clinical use a new, highly sensitive and specific one. Enzyme immune assay (EIA) absorbance data from 135 parvovirus B19 IgG-positive sera were analyzed in parallel with the new and two reference methods (Avidity1.2 software representing gold standard methodology; avidity index (AI) widely used due to its simplicity). When sample dilutions were selected on the basis of optimal EIA absorbances, all three approaches performed equally (receiver operating characteristic area-under-curve, AUC, discriminating primary infection from past immunity 0.969-0.971). When the samples were reanalyzed at either lower or higher absorbance levels, avidity status (low, borderline or high) was altered, on the average, in 3.7 % of the samples with the new method, in 5.6 % with Avidity1.2 and in 28 % with AI. The new approach was further validated with extensive serum panels for cytomegalovirus, Toxoplasma gondii, rubella and Epstein–Barr virus (AUC 0.990-1.000). It allows for accurate measurement of antimicrobial IgG avidity even from samples with low IgG level, while the globally popular AI approach provides an alternative for samples with sufficiently high IgG level.