Analysis of the Optimal Timing for NIPT and the Detection of Fetal Abnormalities Based on Cluster Analysis and Gradient Boosting Techniques - Zhang, Mengtian; Lv, Jingjing; Tian, Xiaodong; Zhang, Yingying (International Journal of Public Health and Medical Research, 2026)
With the continuous growth of the world's population, ensuring the health of the fetus has become a top priority. To optimize the timing selection of Non-Invasive Prenatal Testing (NIPT) and the strategy for determining fetal abnormalities, this paper constructs multiple models based on medical clinical knowledge and solves for the best NIPT under different circumstances. To explore whether the BMI of pregnant women affects the accuracy of NIPT, the correlation between the concentration of fetal Y chromosome, gestational age of pregnant women, and BMI is first analyzed visually through a correlation heatmap. Then, a generalized additive model is constructed, including single models of BMI, gestational age, and Y chromosome concentration, as well as an interaction model of BMI, gestational age, and Y chromosome concentration to obtain the correlation model. The model is solved using algorithms such as PIRLS. Through analysis, it is found that the concentration of Y chromosome is positively correlated with gestational age and weakly negatively correlated with BMI; both gestational age and BMI have statistical significance with Y chromosome concentration. To further focus on the BMI grouping of pregnant women carrying male fetuses and analyze the impact of different BMIs on the time to reach the Y chromosome concentration standard (>4%), avoiding subjective grouping errors and achieving the goal of "minimizing potential risks", the clustering analysis method is used to divide the BMI intervals with significant differences in the time to reach the Y chromosome concentration standard. Through the analysis of the interference of detection errors on the determination of the standard time, the best NIPT time points for each group are matched. The BMI grouping strategy based on clustering analysis and the matched best NIPT time points can significantly improve the detection accuracy, reduce the potential risks of pregnancy, and keep the detection errors controllable, providing reliable support for the precise clinical implementation of NIPT.