Clinical risk factors for fetal macrosomia

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription or Fee Access

Abstract

Relevance: The prevalence of fetal macrosomia is steadily increasing worldwide and reaches up to 20%. Fetal macrosomia complicates the course of pregnancy and birth, leading to the increase in the number of emergency caesarean sections and perinatal losses by 1.5–3 times. Current prediction strategies are inaccurate, and most patients with fetal macrosomia are sent to labor with the “unknown status”. Current prognostic strategies are inaccurate, and the majority of patients with fetal macrosomia go into labor with the "unknown status".

Objective: To assess the clinical and laboratory risk factors for fetal macrosomia with subsequent development of prognostic mathematical models.

Materials and methods: The case-control study included 110 female patients. Group I (the main group) consisted of 30 patients with gestational diabetes mellitus (GDM). Group II (the control group) consisted of 80 women without GDM. The patients were stratified into four subgroups: Ia and 1b, IIa and IIb) depending on the presence of absence of fetal macrosomia and GDM. The clinical and laboratory risk factors were determined using univariate and multivariate logistic regression.

Results: Risk factors for the development of macrosomia included parity, body mass index before and during pregnancy, macrosomia in history, body weight of the pregnant woman and her partner (baby’s father) at birth, triglyceride and glucose levels at 24–28 weeks of pregnancy, estimated fetal weight during the 3rd ultrasound screening, and baby’s gender. Based on the obtained clinical and laboratory data, mathematical prediction models of macrosomia were constructed. The sensitivity was 100–78%, and specificity was 85–50%, the AUC was 0.76–0.77.

Conclusion: The developed mathematical models can be used to predict the development of fetal macrosomia at or after 24 weeks of pregnancy, both independently of the presence of GDM (also in the group with unknown GDM status) and can be used separately in the group of women with carbohydrate metabolism disorders.

Full Text

Restricted Access

About the authors

Natalia A. Frankevich

Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia

Author for correspondence.
Email: natasha-lomova@yandex.ru
ORCID iD: 0000-0002-6090-586X

Dr. Med. Sci., Senior Researcher at the Department of Obstetrics

Russian Federation, 117997, Moscow, Ac. Oparina str., 4

Alisa O. Tokareva

Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia

Email: alisa.tokareva@phystech.edu
ORCID iD: 0000-0001-5918-9045

PhD (in Physics and Mathematics), specialist at the Laboratory of Clinical Proteomics

Russian Federation, 117997, Moscow, Ac. Oparina str., 4

Tamara E. Karapetyan

Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia

Email: tomamed02@mail.ru
ORCID iD: 0000-0003-0025-3182

Dr. Med. Sci., Senior Researcher at the Department of Obstetrics

Russian Federation, 117997, Moscow, Ac. Oparina str., 4

Anastasia A. Kutsenko

Siberian State Medical University, Ministry of Health of Russia

Email: maori.nastya@yandex.ru
ORCID iD: 0009-0007-6146-561X

PhD student, Department of Obstetrics and Gynecology

Russian Federation, 634050, Tomsk, Moskovsky tract, 2

Angela G. Vasilyeva

Siberian State Medical University, Ministry of Health of Russia

Email: angela.grigorjevna@yandex.ru
ORCID iD: 0009-0006-7975-1115

applicant at the Department of Obstetrics and Gynecology

Russian Federation, 634050, Tomsk, Moskovsky tract, 2

Vitaly V. Chagovets

Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia

Email: v_chagovets@oparina4.ru
ORCID iD: 0000-0002-5120-376X

PhD (in Physics and Mathematics), Head of the Laboratory of Metabolomics and Bioinformatics

Russian Federation, 117997, Moscow, Ac. Oparina str., 4

Vladimir E. Frankevich

Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia; Siberian State Medical University, Ministry of Health of Russia

Email: v_frankevich@oparina4.ru
ORCID iD: 0000-0002-9780-4579

Dr. Sci. (in Physics and Mathematics), Director for Science – Head of the Department of Systems Biology in Reproduction, Institute of Translational Medicine

Russian Federation, 117997, Moscow, Ac. Oparina str., 4; 634050, Tomsk, Moskovsky tract, 2

References

  1. Langley-Evans S.C., Pearce J., Ellis S. Overweight, obesity and excessive weight gain in pregnancy as risk factors for adverse pregnancy outcomes: a narrative review. J. Hum. Nutr. Diet. 2022; 35(2): 250-64. https://dx.doi.org/10.1111/jhn.12999
  2. Wang H., Li N., Chivese T., Werfalli M., Sun H., Yuen L. et al. IDF diabetes atlas: estimation of global and regional gestational diabetes mellitus prevalence for 2021 by International association of diabetes in pregnancy study group’s criteria. Diabetes Res. Clin. Pract. 2022; 183: 109050. https://dx.doi.org/10.1016/j.diabres.2021.109050
  3. Российская ассоциация эндокринологов. Российское общество акушеров-гинекологов. Клинические рекомендации. Гестационный сахарный диабет. Диагностика, лечение, акушерская тактика, послеродовое наблюдение. 2020. [Russian Association of Endocrinologists. Russian Society of obstetricians and gynecologists. Clinical Guidelines. Gestational diabetes mellitus. Diagnosis, treatment, obstetric tactics, postpartum monitoring. 2020 (in Russian)]. https://opc33.ru/wp-content/uploads/2021/07/kr_gsd_2020.pdf
  4. Beta J., Khan N., Khalil A., Fiolna M., Ramadan G., Akolekar R. Maternal and neonatal complications of fetal macrosomia: systematic review and meta-analysis. Ultrasound Obstet. Gynecol. 2019; 54(3): 319-25. https://dx.doi.org/10.1002/uog.20278.
  5. Frick A.P., Syngelaki A., Zheng M., Poon L.C., Nicolaides K.H. 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): 332-9. https://dx.doi.org/10.1002/uog.15780
  6. Goldstein R.F., Abell S.K., Ranasinha S., Misso M., Boyle J.A., Black M.H. et al. Association of gestational weight gain with maternal and infant outcomes: a systematic review and meta-analysis. JAMA. 2017; 317(21): 2207-25. https://dx.doi.org/10.1001/jama.2017.3635
  7. Isaku M., Vrapi E., Bimbashi T., Cala I., Perdja K., Hoxhallari R. et al. Perinatal outcomes among cases of predicted and unpredicted macrosomia. Gynecol. Obstet. Reprod. Med. 2023; 29(2): 93-8. https://dx.doi.org/10.21613/gorm.2022.1379
  8. Boulvain M., Thornton J.G. Induction of labour at or near term for suspected fetal macrosomia. Cochrane Database Syst. Rev. 2023; 3. https://dx.doi.org/10.1002/14651858.CD000938.pub3
  9. Mehlman C.T. Neonatal brachial plexus palsy. The Pediatric Upper Extremity. 2015; 123(4): 589-605. https://dx.doi.org/10.1007/978-1-4614-8515-5_27
  10. Кравченко Е.Н., Серов В.Н., Баев О.Р. Факторы риска родовой травмы. Акушерство и гинекология. 2022; 9: 5-10. [Kravchenko E.N., Serov V.N., Baev O.R. Risk factors for birth injury. Obstetrics and Gynecology. 2022; (9): 5-10 (in Russian)]. https://dx.doi.org/10.18565/aig.2022.9.5-10
  11. Kamana K., Sumisti S., Zhang H. Gestational diabetes mellitus and macrosomia: a literature review. Ann. Nutr. Metab. 2015; 66: 14-20. https://dx.doi.org/10.1159/000371628
  12. Whincup P.H., Kaye S.J., Owen C.G., Huxley R., Cook D.G., Anazawa S. et al. Birth weight and risk of type 2 diabetes a systematic review. JAMA. 2008; 300(24): 2886-97. https://dx.doi.org/10.1001/jama.2008.886
  13. Szabo A.J. Transferred maternal fatty acids stimulate fetal adipogenesis and lead to neonatal and adult obesity. Med. Hypotheses. 2019; 122: 82-8. https://dx.doi.org/10.1016/j.mehy.2018.10.022
  14. Liu C.H., Yang S.T., Wang P.H. Maternal factors associated with fetal macrosomia. Journal of the Chinese Medical Association. 2023; 86(5): 455-6. https://dx.doi.org/10.1097/JCMA.0000000000000894
  15. Moodley T., Moodley J. A retrospective identification of risk factors associated with fetal macrosomia. Afr. J. Reprod. Health. 2022; 26(7): 127-34. https://dx.doi.org/10.29063/ajrh2022/v26i7.13
  16. Romero R., Kingdom J., Deter R., Lee W., Vintzileos A. Fetal growth: evaluation and management. Am. J. Obstet. Gynecol. 2018; 218(2S): S608. https://dx.doi.org/10.1016/j.ajog.2018.01.010
  17. Rizzo G., Patrizi L., Mappa I. Can we improve the diagnosis of fetal macrosomia? J. Clin. Ultrasound. 2022; 50(7): 974-5. https://dx.doi.org/10.1002/jcu.23238
  18. Jenabi E., Salehi A.M., Farashi S., Salimi Z. The environmental risk factors associated with fetal macrosomia: an umbrella review. Pediatr. Neonatol. 2024; 65(3): 217-21. https://dx.doi.org/10.1016/j.pedneo.2023.09.007
  19. Ewington L., Black N., Leeson C., Al Wattar B.H., Quenby S. Multivariable prediction models for fetal macrosomia and large for gestational age: a systematic review. BJOG. 2024; 131(12): 1591-602. https://dx.doi.org/10.1111/1471-0528.17802
  20. Salmeri N., Li Piani L., Cavoretto P.I., Somigliana E., Viganò P., Candiani M. Endometriosis increases the risk of gestational diabetes: a meta-analysis stratified by mode of conception, disease localization and severity. Sci. Rep. 2023; 13(1): 8099. https://dx.doi.org/10.1038/s41598-023-35236-y
  21. O’Neill K., Alexander J., Azuma R., Xiao R., Snyder N.W., Mesaros C.A. et al. Gestational diabetes alters the metabolomic profile in 2nd trimester amniotic fluid in a sex-specific manner. Int. J. Mol. Sci. 2018; 19(9): 2696. https://dx.doi.org/10.3390/ijms19092696
  22. Ricart W., López J., Mozas J., Pericot A., Sancho M.A., González N. et al. Maternal glucose tolerance status influences the risk of macrosomia in male but not in female fetuses. J. Epidemiol. Community Health. 2009; 63(1): 64-8. https://dx.doi.org/10.1136/jech.2008.074542
  23. Боташева Т.Л., Андреева В.О., Рымашевский А.Н., Тезиков Ю.В., Липатов И.С., Фабрикант А.Д., Лебеденко Е.Ю., Железнякова Е.В. Роль половой принадлежности плода в патогенезе гестационного сахарного диабета и акушерских осложнений. Акушерство и гинекология. 2022; 9: 33-41. [Botasheva T.L., Andreeva V.O., Rymashevskiy A.N., Tezikov Yu.V., Lipatov I.S., Fabrikant A.D., Lebedenko E.Yu., Zheleznyakova E.V. The role of fetal gender in the pathogenesis of gestational diabetes mellitus and obstetric complications. Obstetrics and Gynecology. 2022; (9): 33-41 (in Russian)]. https://dx.doi.org/10.18565/aig.2022.9.33-41
  24. Одинокова В.А., Шмаков Р.Г. Современные аспекты акушерской тактики при фетальной макросомии. Акушерство и гинекология. 2022; 7: 21-7. [Odinokova V.A., Shmakov R.G. Modern aspects of obstetric tactics for fetal macrosomia. Obstetrics and gynecology. 2022; (7): 21-7 (in Russian)]. https://dx.doi.org/10.18565/aig.2022.7.21-27
  25. Vitner D., Bleicher I., Kadour-Peero E., Lipworth H., Sagi S., Gonen R. Does prenatal identification of fetal macrosomia change management and outcome? Arch. Gynecol. Obstet. 2019; 299(3): 635-44. https://dx.doi.org/10.1007/s00404-018-5003-2
  26. Yuan Y., Zhu Q., Yao X., Shi Z., Wen J. Maternal circulating metabolic biomarkers and their prediction performance for gestational diabetes mellitus related macrosomia. BMC Pregnancy and Childbirth. 2023; 23: 113. https://dx.doi.org/10.1186/s12884-023-05440-9
  27. Zhang Y., Zhang H.H., Lu J.H., Zheng S.Y., Long T., Li Y.T. et al. Changes in serum adipocyte fatty acid-binding protein in women with gestational diabetes mellitus and normal pregnant women during mid- and late pregnancy. Journal of Diabetes Investigation. 2016; 7(5): 797-804. https://dx.doi.org/10.1111/jdi.12484
  28. Ning H., Tao H., Weng Z., Zhao X. Plasma fatty acid-binding protein 4 (FABP4) as a novel biomarker to predict gestational diabetes mellitus. Acta Diabetol. 2016; 53(6): 891-8. https://dx.doi.org/10.1007/s00592-016-0867-8
  29. Wang X., Guan Q., Zhao J., Yang F., Yuan Z., Yin Y. et al. Association of maternal serum lipids at late gestation with the risk of neonatal macrosomia in women without diabetes mellitus. Lipids Health Dis. 2018; 17(1): 78. https://dx.doi.org/10.1186/s12944-018-0707-7

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Figure 1. Operating curves of parameters—potential markers of macrosomia

Download (184KB)
Indexing metadata
3. Figure 2. Operating curves of models: a) model using data from and including the third screenings; b) model not using the results of the third screening, constructed during cross-validation (red) and validation on the test cohort (black)

Download (131KB)
Indexing metadata

Copyright (c) 2025 Bionika Media