Background: Accurate estimation of fetal birth weight is critical in determining the delivery route and management of the neonate. Purpose of Study: The purpose is to determine the accuracy of Hadlock IV, Campbell, and Shepard's algorithm as predictors of birth weight in a cohort of fetuses of Yoruba descent. Materials and Methods: Fetal weight (FW) was estimated in a sample of 384 fetuses using Hadlock IV, Campbell, and Shepard's algorithm while actual birth weight (ABW) was measured. Receiver operating characteristic curves were plotted and used to determine the accuracy and sensitivity of each algorithm. Results: Most babies (84.6%) had normal estimated fetal weight (EFW) and ABW; mean FW = 3.2 ± 0.5 kg); 10% had low weight while 5.5% were macrosomic. While EFW correlated positively and strongly with ABW, the Hadlock IV algorithm had the strongest correlation (r = 0.978). The Hadlock IV, Campbell, and Shepard's algorithms had 92%, 72%, and 56% accuracy within the tenth centile, respectively. At 95% confidence interval, Hadlock IV was the most accurate predictor of normal birth and low birth weight (area under the curve [AUC] =0.91 and 0.94, respectively). Campbell was the most accurate predictor of macrosomia (AUC = 0.89). Conclusion: While Hadlock IV and Campbell algorithm are valid predictors, the Shepard model is a doubtful birth weight predictor among fetuses of Yoruba origin. When there is a need for absolute birth weight values, the Hadlock IV algorithm is preferred for suspected normal and low-weight babies while the Campbell model is preferred for fetuses weighing >4 kg among Yoruba fetuses.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.