A Ego1. 1. Département méthodologie de l'information en santé, CHU de Grenoble, pavillon Taillefer, CS 10217, 38043 Grenoble cedex 9, France; Inserm U953 - « Unité de recherche épidémiologique sur la santé périnatale et la santé des femmes et des enfants », maternité Port-Royal, 53, avenue de l'Observatoire, 75014 Paris, France. Electronic address: aego@chu-grenoble.fr.
Abstract
OBJECTIVES: Screening for intrauterine growth restriction (IUGR) is a major component of antenatal care, but the debate about the choice of birthweight standards is longstanding. The objective of this first chapter is to provide guidelines about optimal definition of IUGR. MATERIALS AND METHODS: Literature review about available birthweight curves to define IUGR, including the analysis of their diagnosis accuracy and their relevance to identify babies at risk of poor perinatal outcomes. RESULTS: Intrauterine growth curves are more suitable for "normal" growth modeling than birth weight curves, and fetal growth is influenced by individual characteristics, fetal gender being the most important among them (EL2). Infants with a low birth weight are either constitutionally small babies or babies with pathological fetal growth failure. Use of "SGA" for all Small for Gestational Age infants is now recommended, "IUGR" being appropriate only for infants with pathological growth restriction (Professional consensus). Depending on reference curves, identified SGA babies and pregnancy outcomes may be different. Customized birth weight standards are based on an intrauterine growth modeling adjusted for fetal gender, maternal height, weight and parity, and appear to be the most accurate to identify SGA births at risk (EL3). However, their benefit on perinatal morbidity and mortality has not been demonstrated by prospective studies. CONCLUSION: Benefits and drawbacks of customized birth weight curves seem in favor of their use. Their application in ante and postnatal investigations is a real opportunity to standardize clinical practice and make information provided to parents more consistent.
OBJECTIVES: Screening for intrauterine growth restriction (IUGR) is a major component of antenatal care, but the debate about the choice of birthweight standards is longstanding. The objective of this first chapter is to provide guidelines about optimal definition of IUGR. MATERIALS AND METHODS: Literature review about available birthweight curves to define IUGR, including the analysis of their diagnosis accuracy and their relevance to identify babies at risk of poor perinatal outcomes. RESULTS:Intrauterine growth curves are more suitable for "normal" growth modeling than birth weight curves, and fetal growth is influenced by individual characteristics, fetal gender being the most important among them (EL2). Infants with a low birth weight are either constitutionally small babies or babies with pathological fetal growth failure. Use of "SGA" for all Small for Gestational Age infants is now recommended, "IUGR" being appropriate only for infants with pathological growth restriction (Professional consensus). Depending on reference curves, identified SGA babies and pregnancy outcomes may be different. Customized birth weight standards are based on an intrauterine growth modeling adjusted for fetal gender, maternal height, weight and parity, and appear to be the most accurate to identify SGA births at risk (EL3). However, their benefit on perinatal morbidity and mortality has not been demonstrated by prospective studies. CONCLUSION: Benefits and drawbacks of customized birth weight curves seem in favor of their use. Their application in ante and postnatal investigations is a real opportunity to standardize clinical practice and make information provided to parents more consistent.
Keywords:
Birthweight standards; Courbes de poids; Dépistage; Intra-uterine growth restriction; Mortalité périnatale; Perinatal mortality; Petit poids pour l’âge gestationnel; Retard de croissance intra-utérin; Screening; Small for gestational age
Authors: Sarah Vanlieferinghen; Olivia Anselem; Camille Le Ray; Yao Shen; Louis Marcellin; François Goffinet Journal: PLoS One Date: 2015-04-13 Impact factor: 3.240
Authors: Ali Ghanchi; Neil Derridj; Damien Bonnet; Nathalie Bertille; Laurent J Salomon; Babak Khoshnood Journal: Int J Environ Res Public Health Date: 2020-04-28 Impact factor: 3.390