Fetal weight extrapolation following a third-trimester ultrasound examination using the gestation-adjusted projection method: a systematic review and meta-analysis.

Objective Using systematic review and meta-analysis methodology, we sought to evaluate the accuracy of the gestation-adjusted projection (GAP) method of fetal weight extrapolation in the prediction of actual birth weight. Study Design A systematic literature search was performed using MEDLINE/PubMed, Embase, Scopus, and Web of Science for studies published from database inception to June 2023. Studies were compiled that assessed accuracy of the GAP method in pregnant women at term (≥37 weeks' gestation) with an ultrasound performed at 34 to 36 weeks' gestation. Quality was assessed using the Newcastle-Ottawa Scale, and risk of bias was assessed using the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) tool. Meta-analysis was performed to evaluate the agreement between the GAP method and the actual birth weight using the mean percent error, mean absolute error, and mean absolute percent error. Means and 95% confidence intervals (95% CI) were calculated. Heterogeneity between studies was assessed using I² and tau² statistics. Results The search identified 949 records. After full text review, a total of eight studies with 5306 subjects were included. Studies were retrospective and prospective cohort studies. All studies were deemed high quality and determined to have a low risk of bias. Five studies were performed in the United States, one in Italy, one in Spain, and one in the United Kingdom. Four studies included patients with pregestational or gestational diabetes and obesity. Due to substantial heterogeneity, the random-effects model was used to estimate the effects of studies. The mean percent error was 3.1% (95% CI: 1.1-5.2%), the mean absolute error was 240 g (95% CI: 205-275 g), and the mean absolute percent error was 8.0% (95% CI: 6.9-9.1%). Conclusion The GAP method of fetal weight extrapolation is an accurate approach to birth weight prediction and is suitable for use in a diverse population.