| Abstract |
Background: Many complications increase with macrosomia, which is defined as birthweight of ≥4000 g. The ability to estimate when the fetus would exceed 4000 g could help to guide decisions surrounding the optimal timing of delivery. To the best of our knowledge, there is no available tool to perform this estimation independent of the currently available growth charts.
Objective: This study aimed to develop ultrasound- and magnetic resonance imaging-based models to estimate at which gestational age the birthweight would exceed 4000 g, evaluate their predictive performance, and assess the effect of each model in reducing adverse outcomes in a prospectively collected cohort.
Study design: This study was a subgroup analysis of women who were recruited for the estimation of fetal weight by ultrasound and magnetic resonance imaging at 36 0/7 to 36 6/7 weeks of gestation. Primigravid women who were eligible for normal vaginal delivery were selected. Multiparous patients, patients with preeclampsia spectrum, patients with elective cesarean delivery, and patients with contraindications for normal vaginal delivery were excluded. Of note, 2 linear models were built for the magnetic resonance imaging- and ultrasound-based models to predict a birthweight of ≥4000 g. Moreover, 2 formulas were created to predict the gestational age at which birthweight will reach 4000 g (predicted gestational age); one was based on the magnetic resonance imaging model, and the second one was based on the ultrasound model. This study compared the adverse birth outcomes, such as intrapartum cesarean delivery, operative vaginal delivery, anal sphincter injury, postpartum hemorrhage, shoulder dystocia, brachial plexus injury, Apgar score of <7 at 5 minutes of life, neonatal intensive care unit admission, and intracranial hemorrhage in the group of patients who delivered after the predicted gestational age according to the magnetic resonance imaging-based or the ultrasound-based models with those who delivered before the predicted gestational age by each model, respectively.
Results: Of 2378 patients, 732 (30.8%) were eligible for inclusion in the current study. The median gestational age at birth was 39.86 weeks of gestation (interquartile range, 39.00-40.57), the median birthweight was 3340 g (interquartile range, 3080-3650), and 63 patients (8.6%) had a birthweight of ≥4000 g. Prepregnancy body mass index, geographic origin, gestational age at birth, and fetal body volume were retained for the optimal magnetic resonance imaging-based model, whereas maternal age, gestational diabetes mellitus, diabetes mellitus type 1 or 2, geographic origin, fetal gender, gestational age at birth, and estimated fetal weight were retained for the optimal ultrasound-based model. The performance of the first model was significantly better than the second model (area under the curve: 0.98 vs 0.89, respectively; P<.001). The group of patients who delivered after the predicted gestational age by the first model (n=40) had a higher risk of cesarean delivery, postpartum hemorrhage, and shoulder dystocia (adjusted odds ratio: 3.15, 4.50, and 9.67, respectively) than the group who delivered before this limit. Similarly, the group who delivered after the predicted gestational age by the second model (n=25) had a higher risk of cesarean delivery and postpartum hemorrhage (adjusted odds ratio: 5.27 and 6.74, respectively) than the group who delivered before this limit.
Conclusion: The clinical use of magnetic resonance imaging- and ultrasound-based models, which predict a gestational age at which birthweight will exceed 4000 g, may reduce macrosomia-related adverse outcomes in a primigravid population. The magnetic resonance imaging-based model is better for the identification of the highest-risk patients.
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