This study aimed to examine whether the addition of fetal growth velocities, based on serial scans, compared with estimated fetal weight (EFW) alone, improves the prediction accuracy of birth weight (BW).
Study DesignFrom the prospective National Institute for Child Health and Human Development Fetal Growth Studies, Singletons (2009–2013) that recruited women at low-risk for aberrant fetal growth, we included 2,397 participants with two to five ultrasounds between 15 and 41 weeks. Fetal growth velocity (V) was calculated between successive visits. Linear regression estimated the relationship between EFW and BW: non-V model, absent all growth velocities, included EFW at visit 5, interval from visit 5 to delivery, their cubic polynomials, and delivery gestational age; all-V model added all available velocities between research visits (i.e., V2 + V3 + V4 + V5) to the non-V model; single-V model added only the velocity between visits 4 and 5.
ResultsNon-V performed the worst, with the highest mean absolute error of 197 g and the lowest R 2, 0.63. The two best performing models were all-V and single-V, with the lowest mean absolute error (192 g for both), the highest R 2 of 0.65 (for both), and the greatest proportion of predicted BWs within 10% of actual BW (84.7% for both).
ConclusionIntegrating fetal growth velocities into BW estimating formulas improved BW prediction accuracy, which has the potential to guide clinical intervention decisions that rely on EFW.
Key PointsDecreasing the BW prediction error is essential.
Single EFW assessment to predict BW is standard.
Adding third-trimester growth velocity improved accuracy.
Growth velocities also improved small- and large-for-gestational age predictions.
These improvements reach a population level.
Keywords birth weight - estimated fetal weight - fetal growth velocity - large for gestational age - small for gestational age NoteThe study was registered at ClinicalTrials.gov (identifiers: NCT00912132 and NCT03266198).
K.L.G.: Conceptualization, data curation, investigation, project administration, resources, and writing—original draft preparation. M.S.V.: Writing—review and editing. J.G.: Data curation and writing—review and editing. D.H.: Data curation, formal analysis, methodology, and writing—review and editing. W.A.G., D.S., R.B.N., J.O., E.K.C., and A.C.R.: Funding acquisition, investigation, and writing—review and editing. S.K. and P.S.A.: Investigation, resources, and writing—review and editing. J.G.: Funding acquisition, investigation, project administration, resources, and writing—review and editing. Z.C.: Conceptualization, formal analysis, methodology, and writing—review and editing.
Received: 22 May 2025
Accepted: 05 August 2025
Accepted Manuscript online:
07 August 2025
Article published online:
21 August 2025
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