Evidence map›Paper›PMID 39980689›Full record

SynthesisFrontiers in microbiology2025

A scientometric visualization analysis of the gut microbiota and gestational diabetes mellitus.

Zehao Su, Lina Liu, Jian Zhang, Jingjing Guo, Guan Wang, Xiaoxi Zeng

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in microbiology, 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. Review
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

6 authors.

Zehao SuWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Lina LiuCenter for Pathogen Research, West China Hospital, Sichuan University, Chengdu, China.
Jian ZhangWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Jingjing GuoWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Guan WangWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Xiaoxi ZengWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The prevalence of gestational diabetes mellitus (GDM), a condition that is widespread globally, is increasing. The relationship between the gut microbiota and GDM has been a subject of research for nearly two decades, yet there has been no bibliometric analysis of this correlation. This study aimed to use bibliometrics to explore the relationship between the gut microbiota and GDM, highlighting emerging trends and current research hotspots in this field. Results: A total of 394 papers were included in the analysis. China emerged as the preeminent nation in terms of the number of publications on the subject, with 128 papers (32.49%), whereas the United States had the most significant impact, with 4,874 citations. The University of Queensland emerged as the most prolific institution, contributing 18 publications. Marloes Dekker Nitert was the most active author with 16 publications, and Omry Koren garnered the most citations, totaling 154. The journal Conclusion: This study provides a comprehensive knowledge map of the gut microbiota and GDM, highlights key research areas, and outlines potential future directions.

Indexed as

bibliometric analysisco-occurrence analysisgestational diabetes mellitusgut microbiotavisualization

Identifiers

PMID39980689
PMCPMC11841407

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.