Background ST-elevated myocardial infarction (STEMI) is the leading cause of mortality worldwide. The mortality rate of heart attacks has decreased due to various preventive factors and the development of early diagnostic resuscitation measures, but the long-term prognosis remains poor. The present study aimed to identify novel serum biomarkers in STEMI patients and explored a possible new mechanism of STEMI from an immune molecular angle with bioinformatics analysis. Methods Gene expression profiles were obtained from Gene Expression Omnibus (GEO) database. Differential gene analysis, machine learning algorithms, gene set enrichment analysis, and immune cell infiltration analysis were conducted using R software. Results We identified 146 DEGs (differentially expressed genes) in the integrated dataset between the STEMI and CAD (coronary artery disease) groups. Immune infiltration analysis indicated that eleven cell types were differentially infiltrated. Through correlation analysis, we further screened 25 DEGs that showed a high correlation with monocytes and neutrophils. Afterwards, five genes consistently selected by all three machine learning algorithms were considered candidate genes. Finally, we identified a hub gene (ADM) as a biomarker of STEMI. AUC curves showed that ADM had more than 80% high accuracy in all datasets. Conclusions In this study, we explored a potentially new mechanism of STEMI from an immune molecular perspective, which might provide insights into the pathogenesis of STEMI. ADM positively correlated with monocytes and neutrophils, suggesting its potential role in the immune response during STEMI. Additionally, we validated the diagnostic performance of ADM in two external datasets, which could help to develop new diagnostic tools or therapeutic strategies.

Atrial fibrillation (AF) is the most common arrhythmia. It is associated with increased stroke risks, thromboembolism, and other complications, which are great life and economic burdens for patients. In recent years, with the maturity of percutaneous catheter radiofrequency ablation (RFA) technology, it has become a first-line therapy for AF. However, some patients still experience AF recurrence (AFR) after RFA, which can cause serious consequences. Therefore, it is crucial to identify appropriate parameters that can predict the prognosis. Here, we reviewed possible predicting indicators for AFR, focusing on all the electrocardiogram indicators, such as P wave duration, PR interval and so on. It may provide valuable information for guiding clinical works.

Atrial fibrillation (AF) is a common complication of coronary revascularization. Currently, the mechanisms of postoperative AF are unclear. This study was aimed at investigating the risk factors for new-onset AF (NOAF) after coronary revascularization and exploring the early warning effects of clinical inflammatory markers. A retrospective analysis was conducted on 293 patients with unstable angina pectoris who underwent coronary artery revascularization in Beijing Chao-Yang Hospital, Capital Medical University, between April 2018 and June 2021, including 224 patients who underwent coronary artery bypass grafting and 69 patients who underwent one-step hybrid coronary revascularization. Baseline data, clinical data, blood indicators and AF episodes within 7 days after the surgery were collected. Participants were divided into two groups according to whether AF occurred, and the data were analyzed between groups. In addition, multivariate logistic regression was used to explore the independent risk factors for developing AF post coronary revascularization. Aging, a larger left atrial inferior-superior diameter, use of an intra-aortic balloon pump, a greater blood volume transfused during perioperative period and a higher monocyte to high-density lipoprotein ratios on postoperative day 1 were independent risk factors for NOAF after coronary artery surgery.

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