Birth - Macrosomia

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Introduction

Historic model of birth

Macrosomia (large gestational age, LGA) is a term used to describe a newborn with an excessive birth weight due to a range of known and unknown causes. There are many different definitions that have been used for to this term, generally a birth weight of 4000 to 4500 g (8 lb 13 oz to 9 lb 15 oz) or greater than 90% for gestational age after correcting for neonatal sex and ethnicity.


A recent study of USA data[1] suggests adverse perinatal outcomes of birthweight exceeded the 97th percentile. Their definition was a "birthweight greater than 4500 g in Whites, or 4300 g in Blacks and Hispanics regardless of gestational age is the optimal threshold to define macrosomia. A birthweight greater than the 97th percentile for a given gestational age, irrespective of race is also reasonable to define macrosomia."

  1. Duration of gestation - growth past the due date.
  2. Maternal diabetes - presence of gestational diabetes; and class A, B, and C diabetes mellitus.
  3. Genetic Syndromes and Tumours - a range of overgrowth syndromes associated with developmental delay, tumors, and other anomalies with genetic causes and syndromes (Pallister-Killian, Beckwith-Wiedemann, Sotos, Perlman, and Simpson-Golabi-Behmel) rarely diagnosed prenatally.


Currently there is clinical research looking into the best mathematical formula, based upon ultrasound measurements, to estimate the possibility of macrosomia occurring.


Birth Links: Introduction | Lecture - Birth | Caesarean | Preterm | Birth Weight | Birth Statistics | Australian Birth Data | Developmental Origins of Health and Disease | Macrosomia | Neonatal Diagnosis | Apgar test | Guthrie test | Neonatal Development | Stillbirth and Perinatal Death | ICD-10 Perinatal Period | Category:Birth | Maternal Diabetes

Some Recent Findings

  • Searching for the Definition of Macrosomia through an Outcome-Based Approach[1] "Macrosomia has been defined in various ways by obstetricians and researchers. The purpose of the present study was to search for a definition of macrosomia through an outcome-based approach. In a study of 30,831,694 singleton term live births and 38,053 stillbirths in the U.S. Linked Birth-Infant Death Cohort datasets (1995-2004), we compared the occurrence of stillbirth, neonatal death, and 5-min Apgar score less than four in subgroups of birthweight (4000-4099 g, 4100-4199 g, 4200-4299 g, 4300-4399 g, 4400-4499 g, 4500-4999 g vs. reference group 3500-4000 g) and birthweight percentile for gestational age (90th-94th percentile, 95th-96th, and ≥97th percentile, vs. reference group 75th-90th percentile). There was no significant increase in adverse perinatal outcomes until birthweight exceeded the 97th percentile. A birthweight greater than 4500 g in Whites, or 4300 g in Blacks and Hispanics regardless of gestational age is the optimal threshold to define macrosomia. A birthweight greater than the 97th percentile for a given gestational age, irrespective of race is also reasonable to define macrosomia. The former may be more clinically useful and simpler to apply."
  • Maternal serum adiponectin at 11 to 13 weeks of gestation in the prediction of macrosomia[2] "Maternal serum adiponectin concentration was measured in a case-control study of singleton pregnancies at 11 to 13 weeks' gestation, which included 50 cases that subsequently delivered macrosomic neonates with birth weight above the 95th percentile for gestation at delivery and 300 controls who delivered appropriate for gestational age neonates. In the macrosomic group the median serum adiponectin [0.82, interquartile range (IQR): 0.56-1.02 MoM] was significantly lower than in the non-macrosomic controls (1.02, IQR: 0.70-1.29 MoM; p = 0.001). The estimated detection rate of macrosomia, at fixed false positive rate of 10%, from maternal characteristics and obstetric history was 34.6% and this increased to 38.2% with the addition of serum adiponectin. Maternal serum adiponectin at 11 to 13 weeks is a useful biomarker for early prediction of macrosomia."
  • Birth-weight prediction by two- and three-dimensional ultrasound imaging[3] "To compare the accuracies of birth-weight predicting models derived from two-dimensional (2D) ultrasound parameters and from total fetal thigh volumes measured by three-dimensional (3D) ultrasound imaging; and to compare the performances of these formulae with those of previously published equations. ...We believe that the greatest sources of discrepancy in estimation of birth weight are the phenotypic differences among patients used to create each of the formulae mentioned in this study. Our data reinforce the need for customized birth-weight prediction formulae, regardless of whether 2D or 3D measurements are employed."
  • Genetic considerations in the prenatal diagnosis of overgrowth syndromes[4] "Large (>90%) for gestational age (LGA) fetuses are usually identified incidentally. Detection of the LGA fetus should first prompt the provider to rule out incorrect dates and maternal diabetes. Once this is done, consideration should be given to certain overgrowth syndromes, especially if anomalies are present. The overgrowth syndromes have significant clinical and molecular overlap, and are associated with developmental delay, tumors, and other anomalies. Although genetic causes of overgrowth are considered postnatally, they are infrequently diagnosed prenatally. Here, we review prenatal sonographic findings in fetal overgrowth syndromes, including Pallister-Killian, Beckwith-Wiedemann, Sotos, Perlman, and Simpson-Golabi-Behmel. We also discuss prenatal diagnosis options and recurrence risks."
More recent papers  
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Search term: Macrosomia

Ritsuko Kawaharada, Haruna Masuda, Zhenyi Chen, Eric Blough, Tomoko Kohama, Akio Nakamura Intrauterine hyperglycemia-induced inflammatory signalling via the receptor for advanced glycation end products in the cardiac muscle of the infants of diabetic mother rats. Eur J Nutr: 2017; PubMed 28942514

Cornelia J J M Caron, Britt I Pluijmers, Eppo B Wolvius, Caspar W N Looman, Neil Bulstrode, Robert D Evans, Peter Ayliffe, John B Mulliken, David Dunaway, Bonnie Padwa, Maarten J Koudstaal Erratum to "Craniofacial and extracraniofacial anomalies in craniofacial macrosomia: A multicenter study of 755 patients" [J Craniomaxillofac Surg vol. 45(8) (August 2017), 1302-1310]. J Craniomaxillofac Surg: 2017; PubMed 28935485

Hui-Ling Liang, Shu-Juan Ma, Yan-Ni Xiao, Hong-Zhuan Tan Comparative efficacy and safety of oral antidiabetic drugs and insulin in treating gestational diabetes mellitus: An updated PRISMA-compliant network meta-analysis. Medicine (Baltimore): 2017, 96(38);e7939 PubMed 28930827

Fatima Vally, Jeffrey Presneill, Thomas Cade Macrosomia Rates in Women with Diet-Controlled Gestational Diabetes: A Retrospective Study. J Pregnancy: 2017, 2017;4935397 PubMed 28928985

Aditi Shruti, George S Wu Case 246: MR Imaging of a Complex Cystic Mass in a Newborn Girl. Radiology: 2017, 285(1);324-328 PubMed 28926319

Birth Weight Classification

Human Birth Weight Classifications
no colour
Birth weight (grams) less 500 500 – 999 1,000 – 1,499 1,500 – 1,999 2,000 – 2,499 2,500 – 2,999 3,000 – 3,499 3,500 – 3,999 4,000 – 4,499 4,500 – 4,999 5,000 or more
Classification
Extremely Low Birth Weight
Very Low Birth Weight
Low Birth Weight
Normal Birth Weight
High Birth Weight


Korea

Birth statistics of high birth weight infants (macrosomia) in Korea.[5]

We used 2 data sources, namely, the hospital units (1960's to 1990's) and Statistics Korea (1993 to 2010). The analyses include the incidence of high birth weight infants (HBWIs), birth weight distribution, sex ratio, and the relationship of HBWI to maternal age. The incidence of HBWIs for the past 50 years has been dropping in Korea. The older the mother, the higher was the risk of a HBWI and LBWI. We hope that these findings would be utilized as basic data that will aid those managing HBWIs.

References

  1. 1.0 1.1 Jiangfeng Ye, Lin Zhang, Yan Chen, Fang Fang, ZhongCheng Luo, Jun Zhang Searching for the definition of macrosomia through an outcome-based approach. PLoS ONE: 2014, 9(6);e100192 PubMed 24941024 | PLoS One.
  2. Surabhi Nanda, Ranjit Akolekar, Rita Sarquis, Ana Paula Mosconi, Kypros H Nicolaides Maternal serum adiponectin at 11 to 13 weeks of gestation in the prediction of macrosomia. Prenat. Diagn.: 2011, 31(5);479-83 PubMed 21394735
  3. J R Bennini, E F Marussi, R Barini, C Faro, C F A Peralta Birth-weight prediction by two- and three-dimensional ultrasound imaging. Ultrasound Obstet Gynecol: 2010, 35(4);426-33 PubMed 20069666
  4. Neeta Vora, Diana W Bianchi Genetic considerations in the prenatal diagnosis of overgrowth syndromes. Prenat. Diagn.: 2009, 29(10);923-9 PubMed 19609940
  5. Byung-Ho Kang, Joo-Young Moon, Sung-Hoon Chung, Yong-Sung Choi, Kyung-Suk Lee, Ji-Young Chang, Chong-Woo Bae Birth statistics of high birth weight infants (macrosomia) in Korea. Korean J Pediatr: 2012, 55(8);280-5 PubMed 22977440

Reviews

Jennifer M Walsh, Fionnuala M McAuliffe Prediction and prevention of the macrosomic fetus. Eur. J. Obstet. Gynecol. Reprod. Biol.: 2012, 162(2);125-30 PubMed 22459652


Articles

Paul A O M De Reu, L J M Smits, H P Oosterbaan, J G Nijhuis Value of a single early third trimester fetal biometry for the prediction of birth weight deviations in a low risk population. J Perinat Med: 2008, 36(4);324-9 PubMed 18598122


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Cite this page: Hill, M.A. 2017 Embryology Birth - Macrosomia. Retrieved September 25, 2017, from https://embryology.med.unsw.edu.au/embryology/index.php/Birth_-_Macrosomia

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