Timing of NIPT and Fetal Abnormality Determination

Abstract

Non-invasive prenatal testing (NIPT) screens for chromosomal abnormalities by analyzing fetal cell-free DNA (cfDNA) in maternal blood, with its accuracy highly dependent on fetal DNA concentration. This study systematically analyzed the quantitative relationship between fetal Y chromosome concentration and gestational age/BMI in high-BMI pregnant women. We established an individualized optimal NIPT timing strategy based on BMI grouping and developed a high-precision machine learning model to enhance the detection efficacy of female fetal chromosomal abnormalities. Results indicate that Y chromosome concentration increases logarithmically with gestational age but decreases significantly with rising BMI, exhibiting a negative interaction effect. For male fetuses, controlling the testing window between 11 and 19 weeks based on BMI grouping ensures over 90% of pregnant women meet the threshold during the low-risk mid-pregnancy period, with Monte Carlo simulations showing a false negative rate below 2%. For female fetuses, a multi-feature Stacking ensemble model achieved an AUC of 0.94 on the test set, significantly outperforming the traditional Z-score method. This study provides a scientific, robust, and scalable personalized decision-making framework for NIPT screening in high-BMI pregnant women, effectively reducing clinical risks associated with delayed testing.