Screening for seemingly healthy newborns with congenital cytomegalovirus infection by quantitative real-time polymerase chain reaction using newborn urine: an observational study

Objective

Approximately 8–10% of newborns with asymptomatic congenital cytomegalovirus (cCMV) infection develop sensorineural hearing loss (SNHL). However, the relationship between CMV load, SNHL and central nervous system (CNS) damage in cCMV infection remains unclear. This study aimed to examine the relationship between urinary CMV load, SNHL and CNS damage in newborns with cCMV infection.

Study design

The study included 23 368 newborns from two maternity hospitals in Saitama Prefecture, Japan. Urine screening for cCMV infection (quantitative real-time PCR) and newborn hearing screening (automated auditory brainstem response (AABR) testing) were conducted within 5 days of birth to examine the incidence of cCMV infection and SNHL, respectively. CNS damage was assessed by MRI of cCMV-infected newborns.

Results

The incidence of cCMV infection was 60/23 368 (0.257%; 95% CI 0.192% to 0.322%). The geometric mean urinary CMV DNA copy number in newborns with cCMV was 1.79x10⁶ copies/mL (95% CI 7.97x10⁵ to 4.02x10⁶). AABR testing revealed abnormalities in 171 of the 22 229 (0.769%) newborns whose parents approved hearing screening. Of these 171 newborns, 22 had SNHL (12.9%), and 5 of these 22 were infected with cCMV (22.7%). Newborns with both cCMV and SNHL had a higher urinary CMV DNA copy number than newborns with cCMV without SNHL (p=0.036). MRI revealed CNS damage, including white matter abnormalities, in 83.0% of newborns with cCMV. Moreover, newborns with CNS damage had a significantly greater urinary CMV load than newborns without CNS damage (p=0.013).

Conclusions

We determined the incidence of cCMV infection and urinary CMV DNA copy number in seemingly healthy newborns from two hospitals in Saitama Prefecture. SNHL and CNS damage were associated with urinary CMV DNA copy number. Quantification of urinary CMV load may effectively predict the incidence of late-onset SNHL and neurodevelopmental disorders.

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