Back

Association of maternal hepatitis B virus infection with adverse pregnancy outcomes and prenatal screening result of second-trimester: a retrospective cohort study

He, Q.; Zhou, Y.; Wu, X.; Xue, Y.; Zhang, C.; Lu, L.; Liu, H.; Zhang, J.-G.; Dang, X.; Wang, T.; Li, H.

2020-04-24 obstetrics and gynecology
10.1101/2020.04.20.20068874 medRxiv
Show abstract

ObjectiveThe association between maternal HBV infection and adverse pregnancy outcomes remains controversial and the prenatal screening features was not investigated though they strongly indicate adverse pregnancy outcomes. We conducted a retrospective cohort study to determine the association between maternal HBV infection and adverse pregnancy outcomes and the result of prenatal screening. DesignThe information from 65,257 pregnant women who performed non-invasive prenatal screening (NIPS) in second-trimester from July 2015 to Nov 2019 in Suzhou, China were collected. The participants were divided into the group of "control" (n = 63,591) and "exposure" (n = 1,666). Meanwhile, eight types of adverse pregnancy outcomes in history and twelve prenatal screening results in the second-trimester of current pregnancy were investigated by estimating and adjusting their risk ratios (aRR) for women between HBV infected and uninfected using multivariate logic regression. ResultOur results suggested that women infected with HBV have higher risks on the biochemical pregnancy, extrauterine pregnancy and three kinds of screen result for fetal Downs syndrome (DS) than women with HBV un-infected. Meanwhile, the diagnostic result for the positive result of fetal Down syndrome in NIPS suggested the 98% additional risk in women with HBV infected than uninfected and supported by all adjusted models. ConclusionTaken together, maternal HBV infection is an independent risk factor of biochemical pregnancy, extrauterine pregnancy, and fetal Downs syndrome. It also indicates the influence of maternal HBV infection way across all gestation.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.