Evidence map›Paper›PMID 39940917›Full record

ArticleInternational journal of molecular sciences2025

Early Prediction of Fetal Macrosomia Through Maternal Lipid Profiles.

Vitaliy Chagovets, Natalia Frankevich, Natalia Starodubtseva, Alisa Tokareva, Elena Derbentseva, Sergey Yuryev, Anastasia Kutzenko, Gennady Sukhikh, Vladimir Frankevich

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Vitaliy ChagovetsNational Medical Research Center for Obstetrics, Gynecology and Perinatology Named After Academician Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia.
Natalia FrankevichNational Medical Research Center for Obstetrics, Gynecology and Perinatology Named After Academician Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia.
Natalia StarodubtsevaNational Medical Research Center for Obstetrics, Gynecology and Perinatology Named After Academician Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia.ORCID 0000-0001-6650-5915
Alisa TokarevaNational Medical Research Center for Obstetrics, Gynecology and Perinatology Named After Academician Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia.
Elena DerbentsevaNational Medical Research Center for Obstetrics, Gynecology and Perinatology Named After Academician Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia.
Sergey YuryevDepartment of Obstetrics and Gynecology, Siberian State Medical University, 634050 Tomsk, Russia.
Anastasia KutzenkoDepartment of Obstetrics and Gynecology, Siberian State Medical University, 634050 Tomsk, Russia.
Gennady SukhikhNational Medical Research Center for Obstetrics, Gynecology and Perinatology Named After Academician Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia.
Vladimir FrankevichNational Medical Research Center for Obstetrics, Gynecology and Perinatology Named After Academician Academician V.I. Kulakov of the Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia.

Funding

Russian Science Foundation 24-64-00006
6 · The paper itself

Abstract

The prevalence of fetal macrosomia is steadily increasing worldwide, reaching up to 20%. Fetal macrosomia complicates pregnancy and delivery. Current prediction strategies are inaccurate, and most patients with fetal macrosomia go into labor with an "unknown status". The aim of this study was to develop a system for predicting fetal macrosomia based on the lipid profiles of pregnant women's blood serum. In total, 110 patients were included in this study: 30 patients had gestational diabetes mellitus (GDM) and 80 did not. During the observation, blood samples were collected at three time points: in the first trimester (11-13 weeks of pregnancy), in the second trimester (24-26 weeks), and in the third trimester (30-32 weeks). Lipids were detected by flow injection analysis with mass spectrometry. Lipid profiles of pregnant women were discriminated by orthogonal projection on latent structure discriminant analysis (OPLS-DA) in all three trimesters. The developed OPLS-DA models allowed for the prediction of the occurrence of fetal macrosomia during pregnancy. Three sets of models were developed: models independent of GDM status with a sensitivity of 0.85 and specificity of 0.91, models for patients with positive GDM status with a sensitivity of 0.91 and specificity of 0.96, and models for patients with negative GDM status with a sensitivity of 0.93 and specificity of 0.92. Phosphatidylcholines and sphingomyelins were the most important discriminative features. These lipid groups probably play an important role in the pathogenesis of fetal macrosomia and may serve as laboratory markers of this pregnancy complication.

Indexed as

Diabetes, GestationalFetal MacrosomiaLipidsAdultBiomarkersFemaleHumansPregnancyBiomarkersLipidsdiagnosticsfetal macrosomialipidomicsmass spectrometryprognosis

Identifiers

PMID39940917
PMCPMC11818448

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.