Evidence map›Paper›PMID 39319462›Full record

ArticleZhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences2024

[Pathogenesis and potential diagnostic biomarkers of atrial fibrillation in Chinese population: a study based on bioinfor-matics].

Xize Wu, Yue Li, Jiaxiang Pan, Jian Kang, Xue Pan, Chentian Xue, Lihong Gong

Abstract readEnglish Abstract
In one paragraph

Article in Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. [Integrating Bioinformatics and Machine Learning Algorithms to Screen Inflammatory Biomarkers for Atrial Fibrillation and Experimental Validation].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026
    Article
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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

7 authors.

Xize WuGraduate School, Liaoning University of Traditional Chinese Medicine, Shenyang 110847, China. 953935269@qq.com.
Yue LiDepartment of Cardiology, the First Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang 110032, China.
Jiaxiang PanDepartment of Cardiology, the First Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang 110032, China.
Jian KangGraduate School, Liaoning University of Traditional Chinese Medicine, Shenyang 110847, China.
Xue PanGraduate School, Liaoning University of Traditional Chinese Medicine, Shenyang 110847, China.
Chentian XueDepartment of Critical Care Medicine, Nantong Hospital of Traditional Chinese Medicine, Nantong 226000, Jiangsu Province, China.
Lihong GongDepartment of Cardiology, the First Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang 110032, China. linda1795@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo explore the pathogenesis and potential biomarkers of atrial fibrillation based on bioinformatics.

methodsDifferentially expressed genes and module genes related to atrial fibrillation were obtained from GSE41177 and GSE79768 datasets (Chinese-origin tissue samples) through differential expression analysis and weighted gene co-expression network analysis. Candidate hub genes were obtained by taking intersections, and hub genes were obtained after gender stratification. Subsequently, functional enrichment analysis and immune infiltration analysis were performed. Four machine learning models were constructed based on the hub genes, and the optimal model was selected to construct a prediction nomogram. The prediction ability of the nomogram was verified using calibration curves and decision curves. Finally, potential therapeutic drugs for atrial fibrillation were screened from the DGIdb database.

resultsA total of 67 differentially expressed genes and 65 module genes related to atrial fibrillation were identified. Functional enrichment analysis indicated that the pathogenesis of atrial fibrillation was closely related to inflammatory response, immune response, and immune and infectious diseases. Four common hub genes (

conclusionsThe pathogenesis of atrial fibrillation is closely related to inflammation and immune response, and the microenvironment of immune cell infiltration of cardiomyocytes in the atrial tissue of patients with atrial fibrillation is disordered.

Indexed as

Atrial FibrillationBiomarkersComputational BiologyEast Asian PeopleFemaleGene Expression ProfilingGene Regulatory NetworksHumansMachine LearningMaleSuperoxide DismutaseSuperoxide Dismutase 2BiomarkersSuperoxide DismutaseSuperoxide Dismutase 2Atrial fibrillationBioinformaticsBiomarkersImmune responseInflammatory responseMachine learning models

Identifiers

PMID39319462
PMCPMC11528137

What OpenQuestion 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 OpenQuestion graph.