Forward Weight Prediction among Small for Gestational Age, Average for Gestational Age, and Large for Gestational Age

Stephanie Masters1, Nneoma Edokobi1, Chloe Lessard1

  • 1Carilion Clinic, Roanoke, Virginia, United States.

PubMed

Insights

The Gestation-Adjusted Projection (GAP) model accurately predicts birth weight, performing well in pregnancies with elevated maternal BMI and for large for gestational age (LGA) neonates. This forward projection model offers potential value in high-risk pregnancies.

Area of Science:

  • Perinatology
  • Maternal-Fetal Medicine
  • Neonatal Ultrasound

Background:

  • Accurate fetal weight estimation is crucial for managing pregnancies and neonatal outcomes.
  • Traditional methods often rely on static estimates near delivery, which may lack precision.
  • The Gestation-Adjusted Projection (GAP) model offers a novel approach using percentile-based extrapolation for more dynamic prediction.

Purpose of the Study:

  • To evaluate the accuracy of the GAP forward projection model for predicting birth weight in neonates categorized as small (SGA), appropriate (AGA), or large for gestational age (LGA).
  • To assess the impact of elevated maternal Body Mass Index (BMI) on the prediction accuracy of the GAP model.

Main Methods:

  • Retrospective review of singleton, liveborn, nonanomalous pregnancies delivered after 28 weeks between 2016-2023.
  • Inclusion criteria required third-trimester growth ultrasounds and mid-gestational anatomical surveys.
  • GAP prediction accuracy was defined as birth weight prediction within 10% of actual; percent error and absolute percent error were also analyzed.

Main Results:

  • The median absolute percent error for the GAP model was 8.56%.
  • Prediction accuracy within 10% varied by maternal BMI: 51.4% (normal), 64.1% (overweight), and 58.0% (obese) (p=0.031).
  • Accuracy within 10% was achieved in 64.8% of AGA, 29.9% of SGA, and 66.9% of LGA infants (p<0.001), with SGA infants frequently underestimated.

Conclusions:

  • The GAP model demonstrates improved accuracy in pregnancies with elevated maternal BMI.
  • The model shows similar accuracy for LGA and AGA infants but struggles with SGA predictions.
  • Findings suggest the GAP model's utility in high-risk populations, including those with obesity or suspected LGA.

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