Evidence map›Paper›PMID 35211112›Full record

SynthesisFrontiers in immunology2022

Chemokines in Gestational Diabetes Mellitus.

Hongying Liu, Aizhong Liu, Atipatsa C Kaminga, Judy McDonald, Shi Wu Wen, Xiongfeng Pan

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
4.1field-weighted citation impact, top 6% of its field
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

18 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Hyperglycemia enhances group BFrontiers in immunology · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Chemokine CX3CL1 (Fractalkine) Signaling and Diabetic Encephalopathy.International journal of molecular sciences · 2024
    Review
  14. Beta-cell compensation and gestational diabetes.The Journal of biological chemistry · 2023
    Review
  15. Article
  16. Observational
  17. Review
  18. 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 at 3 institutions in 3 countries.

Hongying LiuDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Aizhong LiuDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Atipatsa C KamingaDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Judy McDonaldMcLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
Shi Wu WenOMNI Research Group, Ottawa Hospital Research Institute, Ottawa, ON, Canada.
Xiongfeng PanDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
Central South University · CNUniversity of Ottawa · CAMzuzu University · MW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Studies investigating chemokines in gestational diabetes mellitus (GDM) have yielded mixed results. The purpose of this meta-analysis was to explore whether concentrations of chemokines in patients with GDM differed from that of the controls. Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched Web of Science, Embase, Cochrane Library, and PubMed databases for articles, published in any language, on chemokines and GDM through August 1st, 2021. The difference in concentrations of chemokines between patients with GDM and controls was determined by a standardized mean difference (SMD) with a 95% confidence interval (CI), calculated in the meta-analysis of the eligible studies using a random-effects model with restricted maximum-likelihood estimator. Results: Seventeen studies met the inclusion criteria for the meta-analysis. Altogether, they included nine different chemokines comparisons involving 5,158 participants (1,934 GDM patients and 3,224 controls). Results showed a significant increase of these chemokines (CCL2, CXCL1, CXCL8, CXCL9, and CXCL12) in the GDM patients compared with the controls. However, there was a significant decrease of the chemokines, CCL4, CCL11 and CXCL10, in the GDM patients compared with the controls. Moreover, subgroup analysis revealed a potential role of chemokines as biomarkers in relation to laboratory detection (different sample type and assay methods) and clinical characteristics of GDM patients (ethnicity and body mass index). Conclusion: GDM is associated with several chemokines (CCL2, CCL4, CCL11, CXCL1, CXCL8, CXCL9, CXCL10 and CXCL12). Therefore, consideration of these chemokines as potential targets or biomarkers in the pathophysiology of GDM development is necessary. Notably, the information of subgroup analysis underscores the importance of exploring putative mechanisms underlying this association, in order to develop new individualized clinical and therapeutic strategies.

Indexed as

BiomarkersChemokinesDiabetes, GestationalFemaleHumansPregnancyBiomarkersChemokineschemokinesgestational diabetes mellitusimmune microenvironmentinflammatorymeta-analysis

Identifiers

PMID35211112
PMCPMC8860907
OpenAlexW4210828719

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.