Noninvasive Prediction of Congenital Cytomegalovirus Infection After Maternal Primary Infection

for the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Maternal-Fetal Medicine Units (MFMU) Network

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


OBJECTIVE:To develop and internally validate a noninvasive method for the prediction of congenital cytomegalovirus (CMV) infection after primary maternal CMV infection.METHODS:We conducted a secondary analysis of a multicenter randomized placebo-controlled trial of CMV hyperimmune globulin to prevent congenital infection. Women were eligible if they had primary CMV infection, defined as detectable plasma CMV-specific immunoglobulin (Ig)M and CMV-specific IgG with avidity less than 50% before 24 weeks of gestation or IgG seroconversion before 28 weeks, and were carrying a singleton fetus without ultrasonographic findings suggestive of CMV infection. Antibody assays were performed in a single reference laboratory. Congenital infection was defined as CMV detection in amniotic fluid, neonatal urine or saliva, or postmortem tissue. Using backward elimination, we developed logit models for prediction of congenital infection using factors known at randomization. The performance of the model was assessed using leave-one-out cross-validation (a method of internal validation).RESULTS:Of 399 women enrolled in the trial, 344 (86%) had informative data for this analysis. Congenital infection occurred in 68 pregnancies (20%). The best performing model included government-assisted insurance, IgM index 4.5 or higher, IgG avidity less than 32%, and whether CMV was detectable by polymerase chain reaction in maternal plasma at the time of randomization. Cross-validation showed an average area under the curve of 0.76 (95% CI 0.70-0.82), indicating moderate discriminatory ability. More parsimonious one-, two-, and three-factor models performed significantly less well than the four-factor model. Examples of prediction with the four-factor model: for a woman with government-assisted insurance, avidity less than 32%, IgM index 4.5 or higher, and detectable plasma CMV, probability of congenital infection was 0.69 (95% CI 0.53-0.82); for a woman with private insurance, avidity 32% or greater, IgM index less than 4.5, and undetectable plasma CMV, probability of infection was 0.03 (95% CI 0.02-0.07).CONCLUSION:We developed models to predict congenital CMV infection in the presence of primary maternal CMV infection and absence of ultrasonographic findings suggestive of congenital infection. These models may be useful for patient counseling and decision making.

Original languageEnglish (US)
Pages (from-to)400-406
Number of pages7
JournalObstetrics and gynecology
Issue number3
StatePublished - Mar 1 2022

ASJC Scopus subject areas

  • Obstetrics and Gynecology


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