Evidence map›Paper›PMID 40167633›Full record

ArticleActa diabetologica2025

Early prediction of gestational diabetes mellitus: the role of the pregnancy-specific triglycerides-glucose index and other fasting parameters in combination with dynamic testing.

Christian S Göbl, Tina Linder, Daniel Eppel, Grammata Kotzaeridi, Laura Weidinger, Sophie Zarotti, Thorsten Fischer, Monya Todesco Bernasconi, Mirjam Kunze, Nicole Ochsenbein-Koelble and 4 more

Abstract read
PubMed Publisher
In one paragraph

Article in Acta diabetologica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Christian S GöblDivision of Obstetrics and Feto-Maternal Medicine, Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria. christian.goebl@meduniwien.ac.at.
Tina LinderDivision of Obstetrics and Feto-Maternal Medicine, Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria.
Daniel EppelDivision of Obstetrics and Feto-Maternal Medicine, Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria.
Grammata KotzaeridiDivision of Obstetrics and Feto-Maternal Medicine, Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria.
Laura WeidingerDivision of Obstetrics and Feto-Maternal Medicine, Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria.
Sophie ZarottiDivision of Obstetrics and Feto-Maternal Medicine, Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria.
Thorsten FischerDepartment of Obstetrics and Gynaecology, Paracelsus Medical University, Salzburger Landeskrankenhaus, Salzburg, Austria.
Monya Todesco BernasconiDepartment of Obstetrics and Gynaecology, Cantonal Hospital Aarau, Aarau, Switzerland.
Mirjam KunzeDepartment of Obstetrics and Gynaecology, University Hospital Freiburg, Freiburg im Breisgau, Germany.
Nicole Ochsenbein-KoelbleDepartment of Obstetrics and Gynaecology, University Hospital Zurich, Zurich, Switzerland.
Bettina WinzelerDepartment of Endocrinology and Diabetology, University Hospital Basel, Basel, Switzerland.
Irene HoesliDepartment of Obstetrics and Gynaecology, University and University Hospital Basel, Basel, Switzerland.
Evelyn A HuhnDepartment of Obstetrics and Gynaecology, University and University Hospital Basel, Basel, Switzerland.
Andrea TuraInstitute of Neuroscience, CNR, Padua, Italy. andrea.tura@cnr.it.ORCID http://orcid.org/0000-0003-3466-5900

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The identification of mothers at risk for gestational diabetes mellitus (GDM) at start of pregnancy may be beneficial to improve perinatal outcomes. This study aims evaluating the predictive performance of fasting and dynamic indices of glucose metabolism at first trimester and their association with later GDM development. A cohort of 198 women received detailed metabolic assessment at median gestational age (13 weeks) including 75-g oral glucose tolerance test (OGTT) with assessment of glucose, insulin and C-peptide, and biochemical markers (including triglycerides) to calculate different indices of insulin sensitivity either at fasting and in the OGTT dynamic conditions. Moreover, parameters of β-cell function were assessed. A second OGTT was performed between 24 and 28 gestational weeks (GW) to identify women with GDM. We found that 28 women developed GDM, and, in univariable analysis, this was fairly predicted by several first trimester indices, both at fasting and in dynamic conditions. However, fasting indices containing maternal triglycerides showed better accuracy as compared to traditional indices (even the dynamic ones). In multivariable analysis, the best predictive model of GDM development included fasting and OGTT glucose values, HbA1c, and an insulin sensitivity marker that includes triglycerides (e.g. the improved triglyceride-glucose index, TyGIS). β-Cell function was not included in such predictive model, but at 24-28 GW it showed remarkable impairment in women with GDM. In conclusion, both fasting and dynamic parameters of glucose homeostasis at early pregnancy showed fair predictive accuracy for later GDM, with TyGIS showing excellent performance. β-Cell dysfunction role needs being further elucidated.

Indexed as

Blood GlucoseDiabetes, GestationalFastingTriglyceridesAdultFemaleGlucose Tolerance TestHumansInsulinInsulin ResistancePregnancyPregnancy Trimester, FirstBlood GlucoseInsulinTriglyceridesGestational diabetes mellitusImproved triglyceride-glucose indexInsulin sensitivityβ-Cell function

Identifiers

PMID40167633

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.