Prediction of the Timing Selection of NIPT and Abnormality Determination of Fetus Based on Logistic Regression and Comprehensive Loss Function
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Keywords

Logistic regression
Comprehensive loss function
Optimal detection time point
Robustness analysis

DOI

10.26689/jera.v10i2.14382

Submitted : 2026-03-04
Accepted : 2026-03-19
Published : 2026-04-03

Abstract

Chromosomal abnormalities are categorized into chromosomal-level (ROH, polyploidy, aneuploidy), local copy number, and gene-level (insertion/deletion) types. Unlike invasive prenatal diagnostics with miscarriage risks, NIPT is non-invasive, reducing medical risks and maternal anxiety. This study addresses clinical NIPT bottlenecks (inaccurate timing, inconsistent abnormality determination) using high BMI pregnant women’s data via three core approaches: Spearman correlation and mixed-effects models confirm gestational age’s weak positive (rs = 0.084, p < 0.01) and BMI’s weak negative (rs = -0.155, p < 0.001) correlation with fetal Y chromosome concentration; BMI grouping + Logistic regression + comprehensive loss function identifies robust optimal detection timing for each group; K-means clustering (4 groups) + three-layer weighted risk model (accuracy 0.4, timeliness 0.4, stability 0.2) optimizes multi-factor timing. Rational timing and multivariate models improve detection accuracy, supporting early clinical decisions.

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