Cytomegalovirus (CMV) is associated with congenital infections. We aimed to validate the revised CMV immunoglobulin (Ig) M titer cutoff for IgG avidity measurements as a reflex test in maternal screening to identify women with primary CMV infection and newborn congenital cytomegalovirus (cCMV). We screened maternal CMV antibodies (the Denka assay) in Japan, from 2017 to 2019, using a revised IgM cutoff (≥4.00 index). Participants were tested for IgG and IgM antibodies, and for IgG avidity if IgM levels exceeded the cutoff. We compared these with corresponding results from 2013 to 2017 based on the original cutoff (≥1.21) and recalculated using the revised cutoff. Newborn urine CMV DNA tests were performed for women with low avidity (≤35.0%). Among 12,832 women screened in 2017–2019, 127 (1.0%) had IgM above the revised cutoff. Thirty-five exhibited low avidity, and seven infants developed cCMV. Of 19,435 women screened in 2013–2017, 184 (1.0%) had IgM above the revised cutoff, 67 had low avidity, and 1 had cCMV. The 2017–2019 results were not significantly different from the 2013–2017 results. The revised IgM cutoff improves maternal screening in identifying primary infection and newborn cCMV; however, further study related to other assays than Denka is required.

Human cytomegalovirus (CMV) is the leading cause of neurological sequelae in infants. Understanding the risk factors of primary CMV infection is crucial in establishing preventive strategies. Thus, we conducted a retrospective cohort study to identify risk factors of vertical transmission among pregnant women with immunoglobulin (Ig) M positivity. The study included 456 pregnant women with IgM positivity. Information on age, parity, occupation, clinical signs, IgM levels, and IgG avidity index (AI) was collected. The women were divided into infected and non-infected groups. The two groups showed significant differences in IgM level, IgG AI, number of women with low IgG AI, clinical signs, and number of pregnant women with single parity. In the multiple logistic regression analysis, pregnant women with single parity and low IgG AI were independent predictors. Among 40 women who tested negative for IgG antibody in their previous pregnancy, 20 showed low IgG AI in their current pregnancy. Among the 20 women, 4 had vertical transmission. These results provide better understanding of the risk factors of vertical transmission in pregnant women with IgM positivity.

Objective: To establish a model to predict high cytomegalovirus (CMV) immunoglobulin (Ig)G avidity index (AI) using clinical information, to contribute to the mental health of CMV-IgM positive pregnant women. Methods: We studied 371 women with IgM positivity at <= 14 w of gestation. Information on the age, parity, occupation, clinical signs, IgM and G values, and IgG AI was collected. The IgG AI cut-off value for diagnosing congenital infection was calculated based on a receiver operating characteristic curve analysis. Between-group differences were assessed using the Mann-Whitney U-test or chi(2) analysis. The factors predicting a high IgG AI were determined using multiple logistic regression. Results: The women were divided into high or low IgG AI groups based on an IgG AI cut-off value of 31.75. There were significant differences in the IgG and IgM levels, age, clinical signs, and the number of women with one parity between the two groups. In a multiple logistic regression analysis, IgM and the number of women with one parity were independent predictors. This result helped us establish a mathematical model that correctly classified the IgG AI level for 84.6% of women. Conclusion: We established a highly effective model for predicting a high IgG AI immediately after demonstrating IgM positivity. (C) 2020 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.