Clinical risk factors for fetal macrosomia

DOI

https://dx.doi.org/10.18565/aig.2025.150

Frankevich N.A., Tokareva A.O., Karapetyan T.E., Kutsenko A.A., Vasilyeva A.G., Chagovets V.V., Frankevich V.E.
1) Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia, Moscow, Russia; 2) Siberian State Medical University, Ministry of Health of Russia, Tomsk, Russia

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.

Authors' contributions: Frankevich N.A – the concept and design of the study, clinical data analysis, systematic analysis, manuscript writing; Tokareva A.O. – statistical analysis of the obtained data, manuscript editing; Karapetyan T.E. – clinical data analysis, clinical data management in clinical data analysis, clinical and laboratory data collection and processing; Kutsenko A.A. – clinical and laboratory data collection and processing for subsequent information analysis; Vasilyeva A.G. – clinical and laboratory data collection and processing for subsequent information analysis; Chagovets V.V. – analysis of the obtained data, manuscript editing; Frankevich V.E. – systematic analysis, manuscript editing.
Conflicts of interest: The authors confirm that they have no conflicts of interest to declare.
Funding: The study was funded by research funding grant No. 24-64-00006 of the Russian Science Foundation,
https://rscf.ru/project/24-64-00006/
Ethical Approval: The study was approved by the local Ethics Committee of the Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia (Protocol No. 4 of April 18, 2024).
Patient Consent for Publication: The patients have signed informed consent for publication of their data.
Authors' Data Sharing Statement: The data supporting the findings of this study are available on request from the corresponding author after approval from the principal investigator.
For citation: Frankevich N.A., Tokareva A.O., Karapetyan T.E., Kutsenko A.A., Vasilyeva A.G.,
Chagovets V.V., Frankevich V.E. Clinical risk factors for fetal macrosomia.
Akusherstvo i Gynecologia/Obstetrics and Gynecology. 2025; 9: 70-81 (in Russian)
https://dx.doi.org/10.18565/aig.2025.150

fetal macrosomia

risk factors

prognostic models

gestational diabetes mellitus

obesity

multivariate logistic regression

Full text (in Russian)

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Received 11.06.2025

Accepted 15.08.2025

Natalia A. Frankevich, Dr. Med. Sci., Senior Researcher at the Department of Obstetrics, Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia, 117997, Moscow, Russia, Ac. Oparina str., 4, natasha-lomova@yandex.ru, https://orcid.org/0000-0002-6090-586X
Alisa O. Tokareva, PhD (in Physics and Mathematics), specialist at the Laboratory of Clinical Proteomics, Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia, 117997, Russia, Moscow, Ac. Oparina str., 4, alisa.tokareva@phystech.edu,
https://orcid.org/0000-0001-5918-9045
Tamara E. Karapetyan, Dr. Med. Sci., Senior Researcher at the Department of Obstetrics, Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia, 117997, Moscow, Russia, Ac. Oparina str., 4, tomamed02@mail.ru, https://orcid.org/0000-0003-0025-3182
Anastasia A. Kutsenko, PhD student, Department of Obstetrics and Gynecology, Siberian State Medical University, Ministry of Health of Russia, 634050, Russia, Tomsk, Moskovsky tract, 2, maori.nastya@yandex.ru, https://orcid.org/0009-0007-6146-561X
Angela G. Vasilyeva, applicant at the Department of Obstetrics and Gynecology, Siberian State Medical University, Ministry of Health of Russia, 634050, Russia, Tomsk, Moskovsky tract, 2, angela.grigorjevna@yandex.ru, https://orcid.org/0009-0006-7975-1115
Vitaly V. Chagovets, PhD (in Physics and Mathematics), Head of the Laboratory of Metabolomics and Bioinformatics, Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia, 117997, Russia, Moscow, Ac. Oparina str., 4, v_chagovets@oparina4.ru,
https://orcid.org/0000-0002-5120-376X
Vladimir E. Frankevich, Dr. Sci. (in Physics and Mathematics), Director for Science – Head of the Department of Systems Biology in Reproduction, Institute of Translational Medicine, Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia,
117997, Russia, Moscow, Ac. Oparina str., 4, v_frankevich@oparina4.ru, https://orcid.org/0000-0002-9780-4579
Corresponding author: Natalia A. Frankevich, natasha-lomova@yandex.ru

Clinical risk factors for fetal macrosomia

Frankevich N.A., Tokareva A.O., Karapetyan T.E., Kutsenko A.A., Vasilyeva A.G., Chagovets V.V., Frankevich V.E.

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