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ISSN: 2376-127X

Journal of Pregnancy and Child Health
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Research Article

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

Vila-Candel R1*, Martin-Moreno JM2, Alamar S3, Soriano-Vidal FJ4 and Naranjo de la Puerta FG1
1Department of Obstetrics and Gynaecology, Hospital Universitario de la Ribera, Spain
2Department of Preventive Medicine and Public Health, Universitat de Valencia, Spain
3Department of Nursing, Universidad Católica de Valencia, Spain
4Department of Obstetrics and Gynaecology, Hospital LLuis Alcanyis, Spain
Corresponding Author : Vila-Candel R
Department of Obstetrics and Gynaecology
Hospital Universitario de la Ribera, Spain
Tel: 34962001010
E-mail: [email protected]
Received: December 04, 2014; Accepted: April 19, 2015; Published: April 22, 2015
Citation: Vila-Candel R, Martin-Moreno JM, Alamar S, Soriano-Vidal FJ, Naranjo de la Puerta FG (2015) Can We Improve The Birth Weight Prediction? The Effect of Normal BMI Using A Multivariate Model. J Preg Child Health 2:154. doi: 10.4172/2376-127X.1000154
Copyright: © 2015 Vila-Candel R, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

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.

Keywords

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