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Abstrakt
Multiple regression model for predicting high cytomegalovirus immunoglobulin G avidity levels in pregnant women with IgM positivity
Masatoki Kaneko
Objective: We developed a model to predict high cytomegalovirus (CMV) immunoglobulin (Ig) G avidity index (AI) values using clinical information to contribute to the mental health of pregnant women with positive CMV IgM.
Methods: This retrospective cohort study included 371 pregnant women with IgM positivity at 14 weeks of gestation. Information on the women was obtained from medical records. Congenital infection was confirmed by polymerase chain reaction using amniotic fluid or neonatal urine. The IgG AI cutoff value for diagnosing congenital infection was calculated based on ROC curve analysis. Differences between groups were assessed using the Mann-Whitney U test or χ2 analysis. Factors predicting high IgG AI were assessed using multiple logistic regression.