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

This study was aimed to evaluate the accuracy of the gestation-adjusted projection (GAP) forward projection model among neonates classified as small (SGA), appropriate (AGA), or large for gestational age (LGA), and to assess the impact of elevated maternal body mass index (BMI) on prediction accuracy. The GAP model uses percentile-based extrapolation to predict birth weight from remote ultrasounds, maintaining fetal weight percentile from scan to delivery, unlike traditional methods relying on static weight estimates near delivery.We conducted a retrospective review (2016-2023) of singleton, liveborn, nonanomalous pregnancies delivered after 28 weeks. Exclusions included multiples, major anomalies, stillbirth, and missing third-trimester growth ultrasounds or mid-gestational anatomical surveys. Among 1,559 records reviewed, 554 (35.5%) met inclusion criteria, with exclusions primarily due to missing third-trimester growth ultrasounds and mid-gestational anatomical surveys. This represents approximately 5.6% of total deliveries during the study period, reflecting our specific inclusion requirement for third-trimester growth assessments beyond routine prenatal care. GAP prediction accuracy was defined as birth weight prediction within 10% of actual, consistent with prior literature. Percent error and absolute percent error were also evaluated.Median absolute percent error for the cohort was 8.56% (interquartile range: 3.9, 15.2). Accuracy within 10% of actual birth weight was achieved in 51.4% of normal weight, 64.1% of overweight, and 58.0% of obese patients (p = 0.031). SGA infants were more often underestimated (median error: -15.79%) than AGA (-5.05%) or LGA (1.18%) infants (p < 0.001). Accuracy within 10% was achieved in 64.8% of AGA, 29.9% of SGA, and 66.9% of LGA infants (p < 0.001).The GAP model demonstrates better accuracy in pregnancies with elevated maternal BMI and similar accuracy for LGA and AGA infants. Findings support its potential value in high-risk groups, such as those with obesity or suspected LGA. · GAP model shows 8.6% median error in weight estimate.. · SGA often underestimated; LGA more accurate.. · GAP performs well in overweight and obese patients..