Clinical, Biochemical, and Neuroimaging Findings Predict Long-Term Neurodevelopmental Outcome in Symptomatic Congenital Cytomegalovirus Infection

Objective To evaluate clinical, biochemical, and neuroimaging findings as predictors of neurodevelopmental outcome in patients with symptomatic congenital cytomegalovirus (CMV). Study design The study cohort comprised 26 patients with symptomatic congenital CMV born between 1993 and 2009 in a single center. Absolute and weight deficit-adjusted head circumference were considered. Cerebrospinal fluid (CSF) investigations included standard cytochemical analysis, determination of beta(2)-microglobulin (beta(2)-m), neuron-specific enolase, and CMV DNA detection. Neuroimaging was classified according to a validated scoring system comprising calcifications, ventriculomegaly, and atrophy, with findings graded from 0 to 3. Systematic long-term neurodevelopmental assessment included motor function, cognition, behavior, hearing, vision, and epilepsy. Sequelae were graded as mild/absent, moderate, or severe; adverse outcome was defined as death or moderate to severe disability. Results Three children died. The mean age at follow-up of the survivors was 8.7 +/- 5.3 years (range, 19 months to 18.0 years). Neonatal findings showing a significant association with adverse outcome were relative microcephaly, CSF beta(2)-m concentrations, and grade 2-3 neuroimaging abnormalities (P < .05). Receiver operator characteristic curve analysis indicated that the most accurate single factor for predicting unfavorable outcome was CSF beta(2)-m > 7.9 mg/L (area under the curve, 0.84 +/- 0.08; sensitivity, 69%; specificity, 100%). The combination of CSF beta(2)-m > 7.9 mg/L and moderate-severe neuroimaging alterations improved predictive ability (area under the curve, 0.92 +/- 0.06; sensitivity, 87%; specificity, 100%). Conclusion Adjusted head circumference, CSF beta(2)-m level, and neuroimaging studies have prognostic significance for neurodevelopmental outcome in newborns with congenital CMV. A combination of early findings improves the predictive value.