1. Introduction
In recent years, the rate of twin pregnancies has continued to rise due
to the growing utilization of
assisted
reproductive technology (ART) and late childbirth 1,
2. Available data suggest that ART accounts for a third of twin
pregnancies 3, 4. It has been well documented that
fetal growth of twin fetuses is slower than that of singletons, usually
starting from 28 to 32 week of gestation5-8,owing to
the limited uterine space9.
Up to date the clinical examination for the intrauterine growth of twins
still largely relies on the growth standards of singletons, and it has
been an increasing focus to develop twin-specific biometry chart to
monitor fetal growth trajectory for twin pregnancy 10.
In recent years, several ultrasonographic reference charts of twins have
been established 5-8, 11-16, however, they were
derived from small
populations5, 11, 15 or did not rule out high risk
pregnancies5, 12, 16. In addition, evidence suggested
that, compared with dichorionic diamniotic (DCDA) twins,
monochorionic diamniotic (MCDA)
twins showed a slower growth rate6, 11,
16, and ART may affect the
perinatal outcome of twin pregnancies17-20. Therefore,
both chorionicity and conception mode should be taken into consideration
when developing fetal biometric reference for twins. A newly published
study from Italy established the first longitudinal growth charts for
fetal ultrasound biometry customized for chorionicity, however, the data
didn’t show statistical difference of fetal growth over gestation age
between DCDA and MCDA twins6.
To date, no study explored the
differences of fetal intrauterine growth between ART and spontaneously
conceived (SC) twin pregnancies. To fill the knowledge gap, our study
would examine the growth difference of twins with varied chorionicity
and conception mode, aiming to establish chorionicity- and conception
mode-specific fetal biometric parameters reference.
Existing studies modeled the growth curve adopting linear mixed
model5-7, 12, 13, multilevel linear
models14, 15 or hierarchical Bayesian
models8, in all of which the fitting precision and
accuracy were somewhat weakened by the data’s deviation in skewness and
kurtosis coefficient. Compared to linear model, the generalized additive
model for location, scale and shape (GAMLSS) extends to model all the
fourth-order variations, including median, standard deviation, skewness,
and kurtosis, demonstrating a strong strength in improving the accuracy
of fitting smoothed percentile curves21. Since 2006,
WHO performed GAMLSS to establish child growth
standards10.
The fetal growth can be differed by race or
ethnicity22, 23. In 2015, a Chinese study initially
established a standard for twin fetal weight growth24.
However, the study was based on birth weight data but not
ultrasonographic biometric parameters, while the birth weight data can
be biased by preterm delivery since preterm delivery is usually
associated with pregnancy complications and fetal growth abnormalities.
Therefore, the standard established in this study somewhat sacrificed
the sensitivity to identify the early onset of growth restriction and
cannot convey the longitudinal pattern of fetal growth from early
pregnancy 24.
The present study would step forward to fit GAMLSS model based
longitudinal growth trajectories among Chinese pregnant women by using
ultrasonographic biometry data. We are the first to develop fetal growth
reference for Chinese twin pregnancies stratified by both chorionicity
and mode of conception, and the reference would be tested through the
comparison with data from singletons.