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.