Ultrasound estimation of birth weight in twin pregnancy: comparison of biometry algorithms in the STORK multiple pregnancy cohort

Objectives The aims of this study were first, to ascertain the accuracy of formulae for ultrasonographic birth-weight estimation in twin compared with singleton pregnancies and second, to assess the accuracy of sonographic examination in the prediction of birth-weight discordance in twin pregnancies. Methods This was a retrospective cohort study including both singleton and twin pregnancies. Routine biometry was recorded and estimated fetal weight (EFW) calculated using 33 different formulae. Only pregnancies that delivered within 48 h of the ultrasound scan were included (4280 singleton and 586 twin fetuses). Differences between the EFW and actual birth weight (ABW) were assessed by percentage error, accuracy in predictions within +/- 10% and +/- 15% of error and use of the Bland-Altman method. The accuracy of prediction of the different cut-offs of birth-weight discordance in twin pregnancies was also assessed using the area under the receiver-operating characteristics curve (AUC). Results The overall mean absolute percentage error was <= 10% for 25 formulae in singleton pregnancies compared with three formulae in twin pregnancies. The overall predictions within +/- 10% and +/- 15% of the ABW were 62.2% and 81.5% in singleton and 49.7% and 68.5% in twin pregnancies, respectively. When the formulae were categorized according to the biometric parameters included, those based on a combination of head, abdomen and femur measurements showed the lowest mean absolute percentage error, in both singleton and twin pregnancies. The predictive accuracy for 25% birth-weight discordance using the Hadlock 2 formula, as assessed by the AUC, was 0.87. Conclusions Ultrasound estimation of birth weight is less accurate in twin than in singleton pregnancies. Formulae that include a combination of head, abdomen and femur measurements perform best in both singleton and twin pregnancies. Copyright (C) 2013 ISUOG. Published by John Wiley & Sons Ltd.