A first trimester prediction model for large for gestational age infants: a preliminary study

Francesca Monari, Daniela Menichini, Ludovica Spano' Bascio, Giovanni Grandi, Federico Banchelli, Isabella Neri, Roberto D'Amico, Fabio Facchinetti, Francesca Monari, Daniela Menichini, Ludovica Spano' Bascio, Giovanni Grandi, Federico Banchelli, Isabella Neri, Roberto D'Amico, Fabio Facchinetti

Abstract

Background: Large for gestational age infants (LGA) have increased risk of adverse short-term perinatal outcomes. This study aims to develop a multivariable prediction model for the risk of giving birth to a LGA baby, by using biochemical, biophysical, anamnestic, and clinical maternal characteristics available at first trimester.

Methods: Prospective study that included all singleton pregnancies attending the first trimester aneuploidy screening at the Obstetric Unit of the University Hospital of Modena, in Northern Italy, between June 2018 and December 2019.

Results: A total of 503 consecutive women were included in the analysis. The final prediction model for LGA, included multiparity (OR = 2.8, 95% CI: 1.6-4.9, p = 0.001), pre-pregnancy BMI (OR = 1.08, 95% CI: 1.03-1.14, p = 0.002) and PAPP-A MoM (OR = 1.43, 95% CI: 1.08-1.90, p = 0.013). The area under the ROC curve was 70.5%, indicating a satisfactory predictive accuracy. The best predictive cut-off for this score was equal to - 1.378, which corresponds to a 20.1% probability of having a LGA infant. By using such a cut-off, the risk of LGA can be predicted in our sample with sensitivity of 55.2% and specificity of 79.0%.

Conclusion: At first trimester, a model including multiparity, pre-pregnancy BMI and PAPP-A satisfactorily predicted the risk of giving birth to a LGA infant. This promising tool, once applied early in pregnancy, would identify women deserving targeted interventions.

Trial registration: ClinicalTrials.gov NCT04838431 , 09/04/2021.

Keywords: Biochemical markers; Biophysical markers; First trimester; LGA; Prediction model.

Conflict of interest statement

The authors have no competing interests.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
ROC curve and predicted versus observed event probability plot

References

    1. Weissmann-Brenner A, Simchen MJ, Zilberberg E, et al. Maternal and neonatal outcomes of large for gestational age pregnancies. Acta Obstet Gynecol Scand. 2012;91(7):844–849. doi: 10.1111/j.1600-0412.2012.01412.x.
    1. Mendez-Figueroa H, Truong V, Pedroza C, Chauhan S. Large for gestational age infants and adverse outcomes among uncomplicated pregnancies at term. Am J Perinatol. 2016;34(07):655–662. doi: 10.1055/s-0036-1597325.
    1. Jolly MC, Sebire NJ, Harris JP, Regan L, Robinson S. Risk factors for macrosomia and its clinical consequences: a study of 350,311 pregnancies. Eur J Obstet Gynecol Reprod Biol 2003;111(1):9–14. 10.1016/S0301-2115(03)00154-4.
    1. Chavkin U, Wainstock T, Sheiner E, Sergienko R, Walfisch A. Perinatal outcome of pregnancies complicated with extreme birth weights at term. J Matern Neonatal Med. 2019;32(2):198–202. doi: 10.1080/14767058.2017.1376048.
    1. Johnsson IW, Haglund B, Ahlsson F, Gustafsson J. A high birth weight is associated with increased risk of type 2 diabetes and obesity. Pediatr Obes. 2015;10(2):77–83. doi: 10.1111/ijpo.230.
    1. Kuciene R, Dulskiene V, Medzioniene J. Associations between high birth weight, being large for gestational age, and high blood pressure among adolescents: a cross-sectional study. Eur J Nutr. 2018;57(1):373–381. doi: 10.1007/s00394-016-1372-0.
    1. Boldt HB, Conover CA. Pregnancy-associated plasma protein-a (PAPP-A): a local regulator of IGF bioavailability through cleavage of IGFBPs. Growth Hormon IGF Res. 2007;17(1):10–18. doi: 10.1016/j.ghir.2006.11.003.
    1. Agrogiannis G, Sifakis S, Patsouris E, Konstantinidou O. Insulin-like growth factors in embryonic and fetal growth and skeletal development (review) Mol Med Rep. 2014;10(2):579–584. doi: 10.3892/mmr.2014.2258.
    1. Baer RJ, Lyell DJ, Norton ME, Currier RJ, Jelliffe-Pawlowski LL. First trimester pregnancy-associated plasma protein-a and birth weight. Eur J Obstet Gynecol Reprod Biol. 2016;198:1–6. doi: 10.1016/j.ejogrb.2015.12.019.
    1. Heidegger H, Jeschke U. Human chorionic gonadotropin (hCG)—an endocrine, regulator of gestation and Cancer. Int J Mol Sci. 2018;19(5):1502. doi: 10.3390/ijms19051502.
    1. Metzenbauer M, Hafner E, Hoefinger D, et al. Three-dimensional ultrasound measurement of the placental volume in early pregnancy: method and correlation with biochemical placenta parameters. Placenta. 2001;22(6):602–605. doi: 10.1053/plac.2001.0684.
    1. Frick AP, Syngelaki A, Zheng M, Poon LC, Nicolaides KH. Prediction of large-for-gestational-age neonates: screening by maternal factors and biomarkers in the three trimesters of pregnancy. Ultrasound Obstet Gynecol. 2016;47(3):332–339. doi: 10.1002/uog.15780.
    1. Maynard SE, Min JY, Merchan J, et al. Excess placental soluble fms-like tyrosine kinase 1 (sFlt1) may contribute to endothelial dysfunction hypertension, and proteinuria in preeclampsia. J Clin Invest. 2003;111(5):649–658. doi: 10.1172/JCI17189.
    1. Kuc S, Wortelboer EJ, Koster MPH, De Valk HW, Schielen PCJI, Visser GHA. Prediction of macrosomia at birth in type-1 and 2 diabetic pregnancies with biomarkers of early placentation. BJOG An Int J Obstet Gynaecol. 2011;118(6):748–754. doi: 10.1111/j.1471-0528.2011.02904.x.
    1. Singnoi W, Wanapirak C, Sekararithi R, Tongsong T. A cohort study of the association between maternal serum Inhibin-a and adverse pregnancy outcomes: a population-based study. BMC Pregnancy Childbirth. 2019;19(1):124. doi: 10.1186/s12884-019-2266-y.
    1. Åmark H, Westgren M, Persson M. Prediction of large-for-gestational-age infants in pregnancies complicated by obesity: a population-based cohort study. Acta Obstet Gynecol Scand. 2019;98(6):769–776. doi: 10.1111/aogs.13546.
    1. Nelson L, Wharton B, Grobman WA. Prediction of large for gestational age birth weights in diabetic mothers based on early third-trimester Sonography. J Ultrasound Med. 2011;30(12):1625–1628. doi: 10.7863/jum.2011.30.12.1625.
    1. Boriboonhirunsarn D, Kasempipatchai V. Incidence of large for gestational age infants when gestational diabetes mellitus is diagnosed early and late in pregnancy. J Obstet Gynaecol Res. 2016;42(3):273–278. doi: 10.1111/jog.12914.
    1. Sweeting AN, Wong J, Appelblom H, et al. A novel early pregnancy risk prediction model for gestational diabetes mellitus. Fetal Diagn Ther. 2019;45(2):76–84. doi: 10.1159/000486853.
    1. Hassiakos D, Eleftheriades M, Papastefanou I, et al. Increased maternal serum Interleukin-6 concentrations at 11 to 14 weeks of gestation in low risk pregnancies complicated with gestational diabetes mellitus: development of a prediction model. Horm Metab Res. 2015;48(1):35–41. doi: 10.1055/s-0034-1395659.
    1. Poon L, Nicolaides K. First-trimester screening for preeclampsia. Prenat Diagn. 2014;34:618–627. doi: 10.1002/pd.4397.
    1. DeMers D, Wachs D. Physiology, Mean Arterial Pressure.; 2019.
    1. Lai J, Poon LCY, Bakalis S, Chiriac R, Nicolaides KH. Systolic, diastolic and mean arterial pressure at 30-33 weeks in the prediction of preeclampsia. Fetal Diagn Ther. 2013;33(3):173–181. doi: 10.1159/000345950.
    1. Bertino E, Spada E, Occhi L, et al. Neonatal anthropometric charts: the Italian neonatal study compared with other European studies. J Pediatr Gastroenterol Nutr. 2010;51(3):353–361. doi: 10.1097/MPG.0b013e3181da213e.
    1. Bloomgarden ZT. American Association of Clinical Endocrinologists (AACE) consensus conference on the insulin resistance syndrome: 25-26 august 2002, Washington, DC. Diabetes Care. 2003;26(3):933–939. doi: 10.2337/diacare.26.3.933.
    1. Boisvert MR, Koski KG, Burns DH, Skinner CD. Early prediction of macrosomia based on an analysis of second trimester amniotic fluid by capillary electrophoresis. Biomark Med. 2012;6(5):655–662. doi: 10.2217/bmm.12.54.
    1. Coomarasamy A, Connock M, Thornton J, Khan KS. Accuracy of ultrasound biometry in the prediction of macrosomia: a systematic quantitative review. BJOG An Int J Obstet Gynaecol. 2005;112(11):1461–1466. doi: 10.1111/j.1471-0528.2005.00702.x.
    1. Poon LCY, Karagiannis G, Stratieva V, Syngelaki A, Nicolaides KH. First-trimester prediction of Macrosomia. Fetal Diagn Ther. 2011;29(2):139–147. doi: 10.1159/000318565.
    1. Wells G, Bleicher K, Han X, et al. Maternal diabetes, large-for-gestational-age births, and first trimester pregnancy–associated plasma protein-a. J Clin Endocrinol Metab. 2015;100(6):2372–2379. doi: 10.1210/jc.2014-4103.
    1. Jensen DM, Korsholm L, Ovesen P, et al. Peri-Conceptional A1C and risk of serious adverse pregnancy outcome in 933 women with type 1 diabetes. Diabetes Care. 2009;32(6):1046–1048. doi: 10.2337/dc08-2061.
    1. Patil M, Panchanadikar TM, Wagh G. Variation of Papp-a level in the first trimester of pregnancy and its clinical outcome. J Obstet Gynecol India. 2014;64(2):116–119. doi: 10.1007/s13224-013-0481-4.
    1. McDonnold M, Mele L, Myatt L, et al. Waist-to-hip ratio versus body mass index as predictor of obesity-related pregnancy outcomes. Am J Perinatol. 2016;33(06):618–624. doi: 10.1055/s-0035-1569986.
    1. Stogianni A, Lendahls L, Landin-Olsson M, Thunander M. Obstetric and perinatal outcomes in pregnancies complicated by diabetes, and control pregnancies, in Kronoberg, Sweden. BMC Pregnancy Childbirth. 2019;19(1):159. doi: 10.1186/s12884-019-2269-8.
    1. Boubred F, Pauly V, Romain F, Fond G, Boyer L. The role of neighbourhood socioeconomic status in large for gestational age. Farrar D, ed. PLoS One. 2020;15(6):e0233416. 10.1371/journal.pone.0233416
    1. Scott A, Moar V, Ounsted M. The relative contribution of different maternal factors in large-for-gestational-age pregnancies. Eur J Obstet Gynecol Reprod Biol. 1982;13(5):269–277. doi: 10.1016/0028-2243(82)90049-1.
    1. Sonek JD, Kagan KO, Nicolaides KH. Inverted pyramid of care. Clin Lab Med. 2016;36(2):305–317. doi: 10.1016/j.cll.2016.01.009.
    1. Institute of Medicine (US) and National Research Council (US) Committee to Reexamine IOM Pregnancy Weight Guidelines. Weight Gain During Pregnancy. (Rasmussen K, Yaktine A, eds.). National Academies Press; 2009. 10.17226/12584
    1. Teulings NEWD, Masconi KL, Ozanne SE, Aiken CE, Wood AM. Effect of interpregnancy weight change on perinatal outcomes: systematic review and meta-analysis. BMC Pregnancy Childbirth. 2019;19(1):386. doi: 10.1186/s12884-019-2566-2.
    1. Menichini D, Petrella E, Dipace V, Di Monte A, Neri I, Facchinetti F. The impact of an early lifestyle intervention on pregnancy outcomes in a cohort of insulin-resistant overweight and obese women. Nutrients. 2020;12(5). 10.3390/nu12051496
    1. Englund-Ögge L, Brantsæter AL, Juodakis J, et al. Associations between maternal dietary patterns and infant birth weight, small and large for gestational age in the Norwegian mother and child cohort study. Eur J Clin Nutr. 2019;73(9):1270–1282. doi: 10.1038/s41430-018-0356-y.
    1. Barker D. Maternal nutrition, fetal nutrition, and disease in later life. Nutrition. 1997;13:807–813. doi: 10.1016/S0899-9007(97)00193-7.

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe