Statistical Analysis
Categorical variables were described by percentage, and continuous
variables were described by mean and standard deviation. The
Kolmogorov-Smirnov test was used to test the normality of the continuous
variables. The group differences were examined using Chi-squared test,
Student t test, or Mann Whitney U test where appropriate.
The linear regression models were used to test the association of fetal
fraction with birthweight difference. Logistic regression was used to
obtain the odds ratio (OR) and 95% confidence interval (CI), and
examine the effects of fetal fraction on birth weight discordance of
20% and 25% and sFGR.
The Optimal Cutpoints package was used to perform a receiver operator
characteristics curve (ROC) analysis for fetal fraction and birth
outcomes that have significance in above regression analysis, and
determine the optimum cut-off points. Then fetal fraction was converted
into according to the optimal cut-off points, and the association of
fetal fraction (categorical variable) on birth outcomes was assessed
using logistic regression.
The multivariate analyzes between fetal fraction and birth outcomes were
carried out on using multiple logistic regression and multiple linear
regression model. Model adjusted for maternal age, weight, primipara,
history of abortion, chorionicity, pregnancy via ART and physical
conditions (gestational hypertension, gestational diabetes).
All analyses were performed with the Statistical Package for the Social
Sciences (version 24; SPSS Inc, Chicago, IL) and the Optimal Cutpoints
and verification packages for R statistical software (version 3.5.1;
http://www.R-project.org). Significance was defined as a 2-tail
probability value of <0.05.