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Stillbirth or neonatal death before 45 post-menstrual weeks in relation to gestational duration in pregnancies at 39 weeks of gestation or beyond: the impact of parity and body mass index. A national cohort study.

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Related Experiment Video

Updated: May 13, 2026

Modeling Ascending Vaginal Infection, Preterm Birth, and Neonatal Morbidity in Mice
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.

G Lindell1, K Maršál, K Källén

  • 1Department of Obstetrics and Gynecology, Clinical Sciences Lund, Lund, Sweden. gun.lindell@med.lu.se

Ultrasound in Obstetrics & Gynecology : the Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology
|March 19, 2013
PubMed
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.

Related Experiment Videos

Last Updated: May 13, 2026

Modeling Ascending Vaginal Infection, Preterm Birth, and Neonatal Morbidity in Mice
04:18

Modeling Ascending Vaginal Infection, Preterm Birth, and Neonatal Morbidity in Mice

Published on: October 10, 2025

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.