ArticleFrontiers in microbiology2022
Gut-microbiome-based predictive model for ST-elevation myocardial infarction in young male patients.
Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 14 citations in OpenAlex.
- Myocardial Infarction in the Young: Aetiology, Emerging Risk Factors, and the Role of Novel Biomarkers.Journal of cardiovascular development and disease · 2025Review
- Metagenomic Sequencing Combined with Metabolomics to Explore Gut Microbiota and Metabolic Changes in Mice with Acute Myocardial Infarction and the Potential Mechanism of Allicin.Drug design, development and therapy · 2025Article
- Human Gut Microbiota in Heart Failure: Trying to Unmask an Emerging Organ.Biomedicines · 2023Review
- Article
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Authors and funding
15 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: ST-segment elevation myocardial infarction (STEMI) in young male patients accounts for a significant proportion of total heart attack events. Therefore, clinical awareness and screening for acute myocardial infarction (AMI) in asymptomatic patients at a young age is required. The gut microbiome is potentially involved in the pathogenesis of STEMI. The aim of the current study is to develop an early risk prediction model based on the gut microbiome and clinical parameters for this population. Methods: A total of 81 young males (age < 44 years) were enrolled in this study. Forty-one young males with STEMI were included in the case group, and the control group included 40 young non-coronary artery disease (CAD) males. To identify the differences in gut microbiome markers between these two groups, 16S rRNA-based gut microbiome sequencing was performed using the Illumina MiSeq platform. Further, a nomogram and corresponding web page were constructed. The diagnostic efficacy and practicability of the model were analyzed using K-fold cross-validation, calibration curves, and decision curve analysis (DCA). Results: Compared to the control group, a significant decrease in tendency regarding α and β diversity was observed in patients in the case group and identified as a significantly altered gut microbiome represented by Conclusion: In this study, we combined the gut microbiome and common clinical parameters to construct a prediction model. Our analysis shows that the constructed model is a non-invasive tool with potential clinical application in predicting STEMI in the young males.
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