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Can We Improve The Birth Weight Prediction? The Effect of Normal BMI Using A Multivariate Model

Vila-Candel R, Martin-Moreno JM, Alamar S, Soriano-Vidal FJ and Naranjo de la Puerta FG

Objective: The construction of a predictive model that improves the estimation of the fetal weight (EFW). Study Design: A comparative, descriptive study. One hundred forty pregnant women were recruited at two-stage sample in health department in Spain. They were classified in four groups depending on the pre-gestational BMI. Fetal weight was estimated by ultrasound at 35-40 weeks (EFW40w) by one gynecologist. A regression model was created with the variables that reacted to the newborn´s weight, symphysis-fundal height (SFH), EFW40w, gestational age (GA), ferritin level and cigarettes smoked. Results: A multivariate model was created for the NW group to estimate the fetal weight (EFWme), resulting in R2=0.727 (p<0.001). The differences of the averages obtained between EFW40w and EFWme, with the newborn´s weight were significant (p<0.001). EFWme underestimates birth weight by 0.07 g (mean error 0.53%), and EFW40w overestimates it by 300.89 g (mean error 10.12%). In order to evaluate the predictive model and verify the predictions we used the Bland-Altman analysis. The average error in estimating the birth weight with EFWme was 1.94% underestimating the result, whereas the ultrasound error overestimated the result 10.93%. Conclusion: The multivariate model created for the NW group improves the accuracy of the ultrasound.