ArticleFrontiers in immunology2023
Risk prediction model construction for post myocardial infarction heart failure by blood immune B cells.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- Development and validation of a multimodal machine learning prediction model for heart failure after acute myocardial infarction.Clinical and experimental medicine · 2026Article
- Epicardial Adipose Tissue and Heterogeneity Parameters Combined with Inflammatory Cells to Predict the Value of Heart Failure with Preserved Ejection Fraction Patients Post Myocardial Infarction.Cardiovascular diabetology · 2025Article
- Causal relationship between immune cells and risk of heart failure: evidence from a Mendelian randomization study.Frontiers in cardiovascular medicine · 2024Article
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Myocardial infarction (MI) is a common cardiac condition with a high incidence of morbidity and mortality. Despite extensive medical treatment for MI, the development and outcomes of post-MI heart failure (HF) continue to be major factors contributing to poor post-MI prognosis. Currently, there are few predictors of post-MI heart failure. Methods: In this study, we re-examined single-cell RNA sequencing and bulk RNA sequencing datasets derived from the peripheral blood samples of patients with myocardial infarction, including patients who developed heart failure and those who did not develop heart failure after myocardial infarction. Using marker genes of the relevant cell subtypes, a signature was generated and validated using relevant bulk datasets and human blood samples. Results: We identified a subtype of immune-activated B cells that distinguished post-MI HF patients from non-HF patients. Polymerase chain reaction was used to confirm these findings in independent cohorts. By combining the specific marker genes of B cell subtypes, we developed a prediction model of 13 markers that can predict the risk of HF in patients after myocardial infarction, providing new ideas and tools for clinical diagnosis and treatment. Conclusion: Sub-cluster B cells may play a significant role in post-MI HF. We found that the
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