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Updated: May 13, 2026
04:18
Modeling Ascending Vaginal Infection, Preterm Birth, and Neonatal Morbidity in Mice
Published on: October 10, 2025
Predicting risk for large-for-gestational age neonates at term: a population-based Bayesian theorem study
Summary
Routine third-trimester ultrasound effectively predicts large-for-gestational age (LGA) neonates. Adding maternal characteristics to fetal weight estimations further improves LGA prediction accuracy.
Area of Science:
- Perinatal medicine
- Maternal-fetal medicine
- Diagnostic imaging
Background:
- Large-for-gestational age (LGA) neonates are associated with increased perinatal risks.
- Accurate prediction of LGA is crucial for optimizing perinatal care and outcomes.
Purpose of the Study:
- To assess the predictive capability of routine third-trimester ultrasound for LGA neonates.
- To determine if incorporating maternal characteristics enhances LGA prediction.
Main Methods:
- Retrieved data from 56,792 singleton term pregnancies with third-trimester ultrasounds.
- Utilized receiver-operating characteristics (ROC) curves to evaluate prediction accuracy.
- Employed logistic regression and Bayesian theorem to integrate fetal weight Z-scores and maternal data.
Main Results:
- Fetal weight Z-scores alone demonstrated high predictive ability for LGA (AUC 0.89).
- A combined model of fetal weight Z-scores and maternal characteristics significantly improved LGA prediction (AUC 0.91).
- Maternal characteristics alone had a lower predictive value (AUC 0.74).
Conclusions:
- Routine third-trimester ultrasound for fetal weight estimation is effective in predicting LGA neonates.
- Integrating maternal characteristics into predictive models offers a significant improvement in LGA prediction accuracy.
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