Acute aortic dissection (AAD) is a life-threatening emergency without established effective monitoring biomarkers. This study aimed to explore biomarkers to optimize the diagnosis of AAD. AAD related genes were screened by spatial transcriptomics experiments, and their encoded proteins were validated in aortic tissues. We measured plasma levels of candidate proteins in 302 participants (173 AAD cases, 129 controls), finding higher PTMA, ADAMTS8, and CD36 in AAD. Case-control analysis revealed that elevated levels of those proteins along with D-dimer, increased systolic blood pressure (SBP), height and smoking history were risk factors for AAD. A multi-marker score comprising D-dimer, ADAMTS8, height, SBP, and age was developed for AAD diagnosis, achieving an AUC of 0.921 (95%CI 0.889-0.952), with 77.5% sensitivity and 96.5% specificity. We further validated the diagnostic performance of the multi-marker score in an independent validation set including healthy controls and patients with chest pain. Our findings indicate that PTMA, ADAMTS8, and CD36 are potential biomarkers associated with AAD. The multi-marker score effectively discriminates AAD from both healthy controls and non-AAD acute chest pain conditions, and may serve as a rapid, cost-effective auxiliary diagnostic tool.

Stanford type A aortic dissection (AAD) is a life-threatening cardiovascular disease characterized by tearing in the aortic wall. Using spatial transcriptomics and multiplex immunofluorescence, we comprehensively analyzed ascending aortas from eight AAD patients across different severities and segments. We demonstrate that SPP1-driven inflammatory signaling intensifies with AAD severity, identifying a nine-gene, layer-anchored severity scale: MYL6/CALD1/MYH9 (mild); CCL2/CP/COL4A1 (moderate); and TMSB4X/ATP5F1E/PKM (severe). Importantly, the collagen-remodeling triad COL1A1/COL3A1/MMP2 is concurrently up-regulated in the brachiocephalic, left subclavian, and left common carotid arteries, often before the ascending aorta meets surgical diameter thresholds. These molecular signatures provide a critical foundation for non-invasive biomarker discovery, risk stratification, and precision pharmacotherapy targeting the SPP1-inflammatory axis, ultimately offering new insights into AAD mechanisms and therapeutic targets.

Background Diabetes mellitus (DM) and coronary artery disease (CAD) are closely interrelated clinical conditions. However, the combination analysis based on DM related CAD diagnostic model remains a gap. The primary objective of this study was to identify diagnostic models and diagnostic markers for CAD based on the association of diabetic phenotypes and attempt to explore them further in a mouse model. Methods We used data integration as well as multiple datasets for both coronary artery disease and diabetes to exclude bias as well as to improve reliability. We employed the least absolute shrinkage and selection operator (LASSO) regression algorithms to construct the CAD diagnostic model. Furthermore, we established mouse CAD model (low-density lipoprotein receptor deficient mice with high fat diet) to explore the crosstalk between the screened biomarkers and severe CAD progress. Results The intersecting genes from differential analysis and weighted correlation network analysis (WGCNA) results yielded 32 diabetes-related biomarkers. We then identified two diabetes-related phenotypes through the consensus clustering in CAD patients. Microenvironmental analysis revealed that phenotype 1 exhibited higher expression of most cytokines, inflammatory factors, interleukins, and related receptors. Immune cell composition in phenotype 1 showed increased infiltration compared to phenotype 2. The LASSO regression identified 16 diabetes-related genes and we further constructed a diagnostic model based on these genes, which the area under the curve (AUC) reached 0.8. Additionally, single cell immune analysis exhibited the location of these genes. KCNQ1, ATP6V1B1, MTDH, and ITPK1 were predominantly located in macrophages, indicating their potential in regulating macrophage during myocardial injury. Furthermore, We elucidated that KCNQ1 and ITPK1 exhibited high expression level in mouse CAD model in tissue level. exhibited similar expression trends with macrophage biomarkers (CD31 and CD68). The result of qPCR also indicated the elevated level of KCNQ1 and ITPK1, which exhibited crosstalk with CD31 and CD68 in mouse CAD model. Conclusion This study delves into the microenvironmental characteristics of diabetes-related phenotypes in CAD, constructing an optimal diagnostic model and validated the significance of diagnostic markers in mouse CAD model, which may offer insights that could be beneficial for clinical management in the near future.

Purpose:Data on the effect of GLP-1RA treatment on the long-term prognosis of patients with diabetes after percutaneous coronary intervention (PCI) are scant. The purpose of this study was to evaluate the effect of GLP-1RA treatment on the long-term prognosis in T2DM patients after PCI. Patients and Methods:Data on T2DM patients who underwent PCI from January 2019 to December 2020 were retrospectively analyzed. Clinical data and the use of hypoglycaemic drugs were collected. Patients were divided into 2 groups based on whether they were treated with GLP-1RAs: the control group and the GLP-1RA group. PSM was used to match the control group at a 1:1 ratio. Survival curve and univariate and multivariate Cox regression analyses were used to compare the effects of GLP-1RA treatment on prognosis. Results:A total of 981 patients were enrolled, and 277 pairs (554 patients) were matched with propensity scores. The balance between two groups improved after PSM (P>0.05). Compared with the control group, patients in the GLP-1RA group had lower TC, LDL-C, and HbA1c levels (P<0.05). After 24 months of follow-up, a total of 93 patients experienced adverse cardiovascular events. The survival curve revealed that the event-free survival rate in the GLP-1RA group was greater than that in the control group (log rank P=0.012). Univariate and multivariate Cox regression analyses revealed that BMI (HR: 1.055, 95% CI=1.007-1.105), HDL-C levels (HR: 0.236, 95% CI=0.095-0.583) and GLP-1RA use (HR: 0.617, 95% CI=0.403-0.943) were independent influencing factors of post-PCI major adverse cardiovascular event (MACE) risk in T2DM patients (P<0.05). Conclusion:GLP-1RA treatment demonstrates cardiovascular benefits in T2DM patients following PCI, effectively reducing the risk of MACE, and enhancing long-term prognosis.

Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for improved diagnosis and treatment. This study combines proteomics, transcriptomics and machine learning (ML) to identify key proteins and pathways associated with AMI. Plasma samples from 48 AMI patients and 50 healthy controls (HC) were used for proteomic sequencing. Differentially expressed proteins (DEPs) were identified and analyzed for pathway enrichment. Protein-protein interaction (PPI) networks were constructed, and we conducted a meta-analysis (GSE60993, GSE61144, GSE48060) using an inverse variance model to combine differentially expressed genes (DEGs) identified via LIMMA and FDR adjustment across three studies. Clustering and co-expression analysis were performed using K-Medoids and weighted gene co-expression network analysis (WGCNA). ML feature selection identified hub proteins, which were validated across bulk, single-cell, and spatial datasets for atherosclerosis (ATH) and MI. In this study, we identified 437 DEPs with 291 up-regulated and 146 down-regulated proteins. Functional enrichment analysis revealed key pathways involved in inflammation, immunity, metabolism, and cellular stress responses, among others. Using non-negative matrix factorization (NNMF) and K-Medoids clustering, AMI patients were divided into two clusters (C1 and C2), with distinct protein expression patterns and inflammatory responses. Differential analysis between clusters revealed 200 cluster-specific DEPs, with C1 associated with angiogenesis and vascular remodeling, and C2 linked to cellular stress and apoptosis. A meta-analysis identified 1383 DEGs, and their intersection with DEPs yielded 63 proteins, which were subsequently refined by logistic regression to 36 AMI-associated proteins. Furthermore, a protein co-expression network analysis identified 49 modules, with the turquoise module being strongly associated with AMI highlighting pathways in lipid metabolism, immune response, and tissue repair. From this module, 17 key proteins were selected, and ML further distilled these to nine core features (CAMP, CLTC, CTNNB1, FUBP3, IQGAP1, MANBA, ORM1, PSME1, and SPP1) that are closely linked to immune regulation, apoptosis, and metabolism. These proteins were validated across multiple datasets. Single-cell analysis revealed distinct expression patterns of these proteins across cell types and spatial regions in ATH and MI, emphasizing their roles in inflammation, vascular remodeling, and plaque instability. This study identifies critical proteins and pathways in AMI, offering potential biomarkers and therapeutic targets. The use of ML provides a robust framework for identifying AMI's key molecular.

Aim The present study was conducted to measure the expression of early growth response factor 3 (Egr3), inflammatory cytokines (IL-1β, IL-6), vascular endothelial growth factor (VEGF) and NF-κB in patients with coronary artery disease (CAD) to investigate the relationships of these molecules and Egr3 gene expression. Methods We recruited 132 CAD patients and 63 healthy individuals. The expression levels of Egr3, VEGF, p50 and p65 were measured by reverse transcription quantitative polymerase chain reaction and the levels of Egr3, IL-1β and IL-6 in patients serum and in human coronary artery endothelial cells (HCAECs) were measured by enzyme-linked immunosorbent assay (ELISAs) in CAD patients. HCAECs were treated with ox-LDL to establish an in vitro atherosclerosis model. An oil red O staining assay was used to assess the lipid droplet formation. A colloidal external lumen formed by Matrigel was used to test the migration of HCAECs. The expression of Egr3, VEGF and NF-κB was determined by Western blotting. Results The levels of serum Egr3 and IL-6 in the severe stenosis group were greater than those in the mild stenosis group and controls (p < 0.05). The level of serum IL-1β in the severe stenosis group was greater than that in the control group (p < 0.05). Moreover, Egr3 expression was positively associated with IL-6 levels (r= 0.55, p < 0.001), IL-1β levels (r=0.21, p=0.004) and the Gensini score (r=0.20, p=0.02). We also found that Egr3 expression was significantly greater in CAD patients than that in controls. And its expression was highest in the mild patients. The expression of VEGF, P50 and P65 was also greater in CAD patients. In the in vitro experiment, we found that the inhibition of Egr3 expression significantly reduced the expression levels of p50, p65, IL-6 and CRP. Moreover, the inhibition of Egr3 expression significantly reduced the lipid droplet formation and decreased capability of lumen formation. Conclusions In the pathogenesis of atherosclerosis, Egr3 gene expression may induce the expression of inflammatory factors and lipid droplet formation and lumen formation, which could promote the atherosclerosis development.

Metabolic syndrome (MetS) is a collection of metabolic abnormalities including insulin resistance, atherogenic dyslipidemia, central obesity, and hypertension. Recently, long noncoding RNAs (lncRNAs) have emerged as pivotal regulators of metabolic balance, influencing the genes associated with MetS. Although the prevalence of insulin resistance is rising, leading to an increased risk of type 2 diabetes mellitus (T2DM) and its vascular complications, there is still a notable gap in understanding the role of lncRNAs in the context of clinical diabetes. Among lncRNAs, lung adenocarcinoma metastasis-associated transcript 1 (MALAT1) has been identified as a significant regulator of metabolism-related disorders, including T2DM and cardiovascular disease (CVD). This review explores the mechanism of lncRNA MALAT1 and suggests that targeting it could offer a promising strategy to combat MetS, thereby enhancing the prognosis of MetS.

Background Atherosclerosis and metabolic syndrome are the main causes of cardiovascular events, but their underlying mechanisms are not clear. In this study, we focused on identifying genes associated with diagnostic biomarkers and effective therapeutic targets associated with these two diseases. Methods Transcriptional data sets of atherosclerosis and metabolic syndrome were obtained from GEO database. The differentially expressed genes were analyzed by RStudio software, and the function-rich and protein-protein interactions of the common differentially expressed genes were analyzed.Furthermore, the hub gene was screened by Cytoscape software, and the immune infiltration of hub gens was analyzed. Finally, relevant clinical blood samples were collected for qRT-PCR verification of the three most important hub genes. Results A total of 1242 differential genes (778 up-regulated genes and 464 down-regulated genes) were screened from GSE28829 data set. A total of 1021 differential genes (492 up-regulated genes and 529 down-regulated genes) were screened from the data set GSE98895. Then 23 up-regulated genes and 11 down-regulated genes were screened by venn diagram. Functional enrichment analysis showed that cytokines and immune activation were involved in the occurrence and development of these two diseases. Through the construction of the Protein-Protein Interaction(PPI) network and Cytoscape software analysis, we finally screened 10 hub genes. The immune infiltration analysis was further improved. The results showed that the infiltration scores of 7 kinds of immune cells in GSE28829 were significantly different among groups (Wilcoxon Test < 0.05), while in GSE98895, the infiltration scores of 4 kinds of immune cells were significantly different between groups (Wilcoxon Test < 0.05). Spearman method was used to analyze the correlation between the expression of 10 key genes and 22 kinds of immune cell infiltration scores in two data sets. The results showed that there were 42 pairs of significant correlations between 10 genes and 22 kinds of immune cells in GSE28829 (|Cor| > 0.3 & P < 0.05). There were 41 pairs of significant correlations between 10 genes and 22 kinds of immune cells in GSE98895 (|Cor| > 0.3 & P < 0.05). Finally, our results identified 10 small molecules with the highest absolute enrichment value, and the three most significant key genes (CX3CR1, TLR5, IL32) were further verified in the data expression matrix and clinical blood samples. Conclusion We have established a co-expression network between atherosclerotic progression and metabolic syndrome, and identified key genes between the two diseases. Through the method of bioinformatics, we finally obtained 10 hub genes in As and MS, and selected 3 of the most significant genes (CX3CR1, IL32, TLR5) for blood PCR verification. This may be helpful to provide new research ideas for the diagnosis and treatment of AS complicated with MS.

目的 探究冠状动脉CTA(CCTA)对非梗阻性冠状动脉疾病(CAD)患者主要不良心脑血管事件(MACCE)和全因死亡的预测价值.方法 纳入2014年1月至2019年12月于新疆医科大学第一附属医院行CCTA检查诊断为非梗阻性CAD患者.回顾性收集患者临床资料、CCTA资料,并通过电话访谈、医院就诊记录查询等多种途径对患者进行随访,中位随访时间为3.7(2.1,5.6)年.最终纳入患者3828例(失访131例).CCTA参数包括冠状动脉钙化(CAC)评分、斑块类型以及冠状动脉轻度狭窄累及冠状动脉节段数.根据Agatston评分方法测得CAC评分并将患者分为<100(2614例)、100-399(946例)、≥400组(268例);根据CCTA测得冠状动脉斑块类型将患者分为钙化斑块(459例)、混合斑块(2981例)、非钙化斑块组(352例);根据美国心脏协会冠状动脉分段标准计算患者的狭窄节段数,并将患者分为0个(516例)、1～3个(2673例)、4～6个(590例)、≥7个狭窄节段组(49例).分析不同CCTA参数与MACCE和全因死亡的相关性以及CCTA各参数联合对MACCE和全因死亡的预测价值.结果 与非MACCE组相比,MACCE组患者CAC评分更高(109.8比42.2),狭窄节段数更多(3个比2个),非钙化斑块占比更高(33.1％比8.6％).与非死亡组相比,死亡组患者CAC评分更高(123.3比42.7),狭窄节段数更多(3比2),非钙化斑块占比更高(41.8％比8.6％).多因素Cox回归分析显示,CAC评分≥400(MACCE HR=2.641;死亡HR=3.062)、狭窄节段数≥7个(MACCE HR=8.509;死亡HR=4.005)和非钙化斑块存在(MACCE HR=4.981;死亡HR=7.079)是MACCE和死亡的独立危险因素(P均<0.05).ROC曲线提示,CCTA各参数联合对MACCE和死亡的预测价值最高,ROC曲线下面积(AUC)分别为0.740和0.775.在此基础上增加年龄,模型预测能力进一步提升,AUC分别达到0.771和0.847.结论 CCTA各参数联合应用对非梗阻性CAD患者MACCE和全因死亡有良好的预测能力,增加年龄指标后模型预测能力进一步提升,为筛选高危人群进行个体化管理提供依据.

Abstract Objective The aim of this work was to evaluate the predictive value of FAR combined with CACS for MACCEs. Background The fibrinogen-albumin-ratio (FAR), a novel biomarker of inflammation, is associated with the severity of coronary artery disease (CAD). Coronary calcification score (CACS) is associated with the severity of coronary stenosis and is closely related to the prognosis of CAD patients. What is the prognostic value of FAR in patients with chest pain, which has not been reported. This study aims to evaluate the relationship between CACS and FAR and their impact on prognosis in patients with suspected CAD. Methods We used information from 12,904 individuals who had coronary computed tomography angiography (CTA) for chest pain and tracked down any significant adverse cardiac and cerebrovascular events (MACCEs). The following formula was used to calculate FAR: fibrinogen (g/L)/albumin (g/L). Patients were separated into groups with greater levels of FAR (FAR-H) and lower levels of FAR (FAR-L) in accordance with the ideal cut-off value of FAR for MACCEs prediction. In addition, patients were divided into three groups based on their CACS scores (CACS ≤ 100, 100 < CACS ≤ 400, and CACS > 400). Results 4946 patients [62(55–71) years, 64.4% male] were ultimately enrolled in the present study. During follow-up, a total of 234 cases (4.7%) of MACCEs were documented. Linear regression analysis results showed that CACS (R2 = 0.004, Standard β = 0.066, P < 0.001) was positively associated with FAR in patients with chest pain.Compared to ones with FAR-L, FAR-H had an increased risk for MACCEs (adjusted HR 1.371(1.053–1.786) P = 0.019). Multivariate Cox regression showed that age (adjusted HR 1.015 95% CI 1.001–1.028;p = 0.03), FAR (adjusted HR 1.355 95% CI 1.042–1.763;p = 0.023),FBG (adjusted HR 1.043 95% CI 1.006–1.083;p = 0.024) and CACS (adjusted HR 1.470 95% CI 1.250–1.727;p < 0.001) were the independent risk factors for MACCEs. The FAR and CACS significantly improved MACCEs risk stratification, contributing to substantial net reclassification improvement ( NRI 0.122, 95% CI 0.054–0.198, P < 0.001) and integrated discrimination improvement(IDI 0.011, 95% CI 0.006–0.017, P < 0.001). Conclusion FAR was an independent risk factor for MACCEs. The results showed that CACS was positively associated with FAR in patients with suspected CAD. A higher level of FAR and heavier coronary calcification burden was associated with worse outcomes among patients with suspected CAD. FAR and CACS improved the risk identification of patients with suspected CAD, leading to a significant reclassification of MACCEs.

目的 探讨乌鲁木齐地区人群血尿酸(uric acid,UA)水平与代谢综合征(metabolic syndrome,MS)的关系.方法 纳入2019年9月至2021年12月新疆心脑血管疾病筛查研究队列建设中乌鲁木齐地区人群.根据MS的诊断标准,将纳入人群分为MS组及非MS组,分析两组人群的基本资料及实验室指标,并按血UA水平的四分位数间距进行分组,分析不同血UA组与MS及其相关参数的相关性.结果 纳入MS组1 799例,非MS组1 799例,与非MS组相比,MS组人群血UA水平明显增高,且随着血UA水平的升高,MS总患病率以及高血压、超重和(或)肥胖、血脂紊乱各组分患病率逐渐升高.相关性分析显示,血UA与体重指数、收缩压、舒张压、总胆固醇、甘油三酯、低密度脂蛋白胆固醇呈正相关.校正了年龄、性别、腰围、收缩压、舒张压、血糖、高密度脂蛋白胆固醇、甘油三酯等因素后,多因素Logistic回归分析显示与最低血UA水平四分位组相比,血UA的二、三、四分位组MS发生的OR分别为 1.473,2.345,4.257(95％CI:1.209～1.795;1.916～2.870;3.451～5.252;均 P＜0.001).应用受试者工作特征曲线筛检MS的血UA最佳截断点为371.95 μmol·L-1,灵敏度为56.8％,特异度为62.8％.结论 新疆乌鲁木齐地区人群中MS患病率较高,血UA水平与MS密切相关,是MS的独立危险因素,血UA对MS有一定的筛检价值.

Purpose: This study aimed to evaluate the association between metabolic score for insulin resistance (METS-IR) and adverse cardiovascular events in patients with ischemic cardiomyopathy (ICM) and type 2 diabetes mellitus (T2DM).Methods: METS-IR was calculated using the following formula: ln[(2 x fasting plasma glucose (mg/dL) + fasting triglyceride (mg/ dL)] x body mass index (kg/m2)/(ln[high-density lipoprotein cholesterol (mg/dL)]). Major adverse cardiovascular events (MACEs) were defined as the composite outcome of nonfatal myocardial infarction, cardiac death, and rehospitalization for heart failure. Cox proportional hazards regression analysis was used to evaluate the association between METS-IR and adverse outcomes. The predictive value of METS-IR was evaluated by the area under the curve (AUC), continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI).Results: The incidence of MACEs increased with METS-IR tertiles at a 3-year follow-up. Kaplan-Meier curves showed a significant difference in event-free survival probability between METS-IR tertiles (P<0.05). Multivariate Cox hazard regression analysis adjusting for multiple confounding factors showed that when comparing the highest and lowest METS-IR tertiles, the hazard ratio was 1.886 (95% CI:1.613-2.204; P<0.001). Adding METS-IR to the established risk model had an incremental effect on the predicted value of MACEs (AUC=0.637, 95% CI:0.605-0.670, P<0.001; NRI=0.191, P<0.001; IDI=0.028, P<0.001).Conclusion: METS-IR, a simple score of insulin resistance, predicts the occurrence of MACEs in patients with ICM and T2DM, independent of known cardiovascular risk factors. These results suggest that METS-IR may be a useful marker for risk stratification and prognosis in patients with ICM and T2DM.

Background: The prognostic value of coronary artery calcium (CAC) combined with risk factor burdens in middle-aged and elderly patients with symptoms is unclear. Methods: A cohort study comprising 7432 middle-aged and elderly symptomatic patients (aged above 55 years) was conducted between December 2013 and September 2020. All patients had undergone coronary computed tomography angiography, and the Agatston score were used to measure CAC scores. The primary outcome was major adverse cardiac and cerebrovascular events (MACCE), which was defined as a composite outcome of nonfatal myocardial infarction, revascularization (percutaneous coronary intervention or coronary artery bypass graft), stroke, and cardiovascular death. Congestive heart failure, cardiogenic shock, malignant arrhythmia, and all-cause mortality were defined as the secondary outcomes. Results: There are 970 (13%) patients with CAC 0–10, 2331 (31%) patients with CAC 11–100, and 4131 (56%) patients with CAC ≥101. The proportion of patients aged 55–65 years, 65–75 years and ≥75 years was 40.7%, 38.1% and 21.2%, respectively. The total number of MACCEs over the 3.4 years follow-up period was 478. The percentage of CAC ≥101 was higher among the 75-year-old group than the 55–65-year-old group, increasing from 46.5% to 68.2%. With the increase in the CAC score, the proportion of patients aged ≥75 years increased from 12.9% to 25.8%, compared to those aged 55–65 years. The number of risk factors gradually increased as the CAC scores increased in the symptomatic patients aged over 55 years and the similar tendencies were observed among the different age subgroups. The proportion of non-obstructive coronary artery disease (CAD) was comparable between the three age groups (53.5% vs 51.9% vs 49.1%), but obstruction CAD increased with age. The incidence of MACCE in the group with CAC ≥101 and ≥4 risk factors was 1.71 times higher (95% confidence interval (CI) 1.01–2.92; p = 0.044) than the rate in the group with CAC ≥101 and 1 risk factor. In the CAC 0–10 group, the incidence of MACCE in patients aged ≥75 years was 12.65 times higher (95% CI: 6.74–23.75; p < 0.0001) than that in patients aged 55–65 years. By taking into account the combination of CAC score, age, and risk factor burden, the predictive power of MACCE can be increased (area under the curve (AUC) = 0.614). Conclusions: In symptomatic patients aged 55 or above, a rise in age, CAC scores, and risk factor burden was linked to a considerable risk of future MACCE. In addition, combining CAC scores, age and risk factors can more accurately predict outcomes for middle-aged and elderly patients with symptoms.

OBJECTIVE:To clarify the effects of percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) on the clinical outcomes of patients with coronary heart disease (CHD) complicated with reduced ejection fraction heart failure (HFrEF) through meta-analysis.METHODS:Three major literature databases - PubMed, Web of Science, and Cochrane - were searched by search terms and the literature retrieval time was publications dating from January 2007 to December 2021. To search for observational studies and randomized controlled trials (RCT) comparing the efficacy of PCI and CABG in patients with CHD and HFrEF, the abstract or full text of the literature was read and the final included literature was determined, according to inclusion and exclusion criteria. The quality of the included literature was evaluated using the Ottawa scale and data extraction was further completed. Data analysis was made using RevMan5.4 and R4.1 software; relevant forest plots and funnel plots were made, according to the extracted data. Egger's test was used to evaluate whether the data had publication bias. Outcomes were the major adverse cardiovascular events (MACE).RESULTS:A total of 10 studies were included and 11,032 subjects were included, made up of 5,521 cases of PCI and 5,511 cases of CABG. The results showed no significant difference between the two groups in cardiac mortality (CM) (RR=1.13, 95% CI 0.98-1.30, P = 0.10) and in overall all-cause mortality (ACM) (RR=1.12, 95% CI 0.92-1.37, P = 0.25). In the subgroup analysis of ACM, in the subgroups with left ventricular ejection fraction (LVEF) less than 35% and exceeding 35% and less than 50% (RR=1.12, 95% CI 0.92-1.37, P = 0.25) between the two groups, there was no statistical difference. However, among other MACE, compared with the PCI group, the CABG group had a lower risk of MACE (RR=1.58, 95%CI 1.49-1.70, P < 0.00001), myocardial infarction (MI) (RR=1.99, 95% CI 1.02-3.88, P = 0.04), heart failure (HF) (RR=1.29, 95% CI 1.17-1.43, P < 0.00001) and revascularization (RR=2.74, 95% CI 1.93-3.90, P < 0.00001). Finally in the CABG group, the risk of stroke or transient ischemic attack (TIA) was higher (RR=0.71, 95% CI 0.58-0.86, P = 0.0006) than the PCI group.CONCLUSIONS:The mortality rates of PCI and CABG were similar in patients with CHD complicated with HFrEF. Compared with PCI, CABG had a lower incidence of MACE, MI, HF, and revascularization, and a higher incidence of stroke or TIA.

Diabetic patients are prone to acute myocardial infarction. Although reperfusion therapy can preserve the viability of the myocardium, it also causes fatal ischemia‒reperfusion injury. Diabetes can exacerbate myocardial ischemia‒reperfusion injury, but the mechanism is unclear. We aimed to characterize the effects of liraglutide on the prevention of ischemia‒reperfusion injury and inadequate autophagy. Liraglutide reduced the myocardial infarction area and improved cardiac function in diabetic mice. We further demonstrated that liraglutide mediated these protective effects by activating AMPK/mTOR-mediated autophagy. Liraglutide markedly increased p-AMPK levels and the LC3 II/LC3 I ratio and reduced p-mTOR levels and p62 expression. Pharmacological inhibition of mTOR increased cell viability and autophagy levels in high glucose and H/R-treated H9C2 cells. Overall, our study reveals that liraglutide acts upstream of the AMPK/mTOR pathway to effectively counteract high glucose- and H/R-induced cell dysfunction by activating AMPK/mTOR-dependent autophagy, providing a basis for the clinical prevention and treatment of ischemia‒reperfusion in diabetes.

BackgroundPlatelet-related parameters and HDL-C have been regarded as reliable and alternative markers of coronary heart disease (CHD) and the independent predictors of cardiovascular outcomes. PDW is a simple platelet index, which increases during platelet activation. Whether the PDW/HDL-C ratio predicts major adverse cardiovascular and cerebrovascular events (MACCEs) in patients who complained of chest pain and confirmed coronary artery calcification remains to be investigated. This study aimed to investigate the prognostic value of the PDW/HDL-C ratio in patients with chest pain symptoms and coronary artery calcification.MethodsA total of 5,647 patients with chest pain who underwent coronary computer tomography angiography (CTA) were enrolled in this study. Patients were divided into two groups according to their PDW/HDL-C ratio or whether the MACCE occurs. The primary outcomes were new-onset MACCEs, defined as the composite of all-cause death, non-fatal MI, non-fatal stroke, revascularization, malignant arrhythmia, and severe heart failure.ResultsAll patients had varying degrees of coronary calcification, with a mean CACS of 97.60 (22.60, 942.75), and the level of CACS in the MACCEs group was significantly higher than that in non-MACCE (P<0.001). During the 89-month follow-up, 304 (5.38%) MACCEs were recorded. The incidence of MACCEs was significantly higher in patients with the PDW/HDL-C ratio > 13.33. The K–M survival curves showed that patients in the high PDW/HDL-C ratio group had significantly lower survival rates than patients in the low PDW/HDL-C ratio group (log-rank test: P < 0.001). Multivariate Cox hazard regression analysis reveals that the PDW/HDL ratio was an independent predictor of MACCEs (HR: 1.604, 95% CI: 1.263–2.035; P < 0.001). Cox regression analysis showed that participants with a lower PDW/HDL-C ratio had a higher risk of MACCEs than those in the higher ratio group. The incidence of MACCEs was also more common in the PDW/HDL-C ratio > 13.33 group among different severities of coronary artery calcification. Furthermore, adding the PDW/HDL-C ratio to the traditional prognostic model for MACCEs improved C-statistic (P < 0.001), the NRI value (11.3% improvement, 95% CI: 0.018–0.196, P = 0.01), and the IDI value (0.7% improvement, 95% CI: 0.003–0.010, P < 0.001).ConclusionThe higher PDW/HDL-C ratio was independently associated with the increasing risk of MACCEs in patients with chest pain symptoms and coronary artery calcification. In patients with moderate calcification, mild coronary artery stenosis, and CAD verified by CTA, the incidence of MACCEs increased significantly in the PDW/HDL-C ratio > 13.33 group. Adding the PDW/HDL-C ratio to the traditional model provided had an incremental prognostic value for MACCEs.