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Background: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China., Methods: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences., Results: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses., Conclusion: This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance., (Copyright © 2024 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license.)

Introduction: The objective of this research was to explore the possible link between markers of liver fibrosis and survival rates in a group of adults who have been diagnosed with both chronic kidney disease (CKD) and coronary artery disease (CAD)., Methods: The National Health and Nutrition Examination Survey (NHANES) data (1999-2018) for participants with both CAD and CKD were analyzed. The fibrosis-4 index (FIB-4), Nonalcoholic Fatty Liver Score (NFS), Forns index, and aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio were identified as crucial biomarkers. All-cause and cardiovascular disease (CVD) mortality were primary outcomes, assessed using Cox models, Kaplan-Meier curves, and receiver operating characteristic (ROC) analysis., Results: A total of 1,192 CKD and CAD patients were included. The Cox regression analysis revealed substantial correlations between elevated FIB-4, NFS, Forns index, and AST/ALT levels and a heightened risk of all-cause (hazard ratio [HR]: 1.188, 95% confidence interval [CI]: 1.108-1.274; HR: 1.145, 95% CI: 1.069-1.227; HR: 1.142, 95% CI: 1.081-1.201; HR: 1.316, 95% CI: 1.056-1.639, respectively) and CVD mortality (HR: 1.133, 95% CI: 1.007-1.275; HR: 1.155, 95% CI: 1.024-1.303; HR: 1.208, 95% CI: 1.109-1.316 and HR: 1.636, 95% CI: 1.203-2.224, respectively). The ROC analysis indicated comparable predictive accuracy for all three biomarkers, with AST/ALT showing slightly superior performance., Conclusion: Liver fibrosis markers, including AST/ALT, NFS, Forns index and FIB-4, are significant mortality predictors in CAD-CKD patients. The AST/ALT ratio, being easily measurable, may serve as an effective predictive tool for risk stratification in this population., (© 2025 The Author(s). Published by S. Karger AG, Basel.)

Background: While the survival benefits of angiotensin-converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) are firmly established in the general population, their efficacy within patient undergoing dialysis with coronary artery disease (CAD) remains controversial., Methods: Between January 2015 and June 2021, 1168 patients undergoing dialysis with CAD were assessed from 30 tertiary medical centers. The primary outcome was all-cause death, and the secondary outcome was cardiovascular death. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for between-group differences., Results: Overall, ACEI or ARB were prescribed to 518 patients (44.3%) upon discharge. After a median follow-up of 22.2 months, 361 (30.9%) patients died, including 243 cardiovascular deaths. The use of ACEI or ARB was associated with a significantly lower risk of all-cause (25.3% vs 35.4%, hazard ratio [HR] 0.65, 95% confidence interval [CI] 0.52-0.82, p  < 0.001) and cardiovascular death (17.0% vs 23.8%; HR 0.64, 95% CI 0.48-0.83, p  = 0.001). These findings remained consistent across IPTW and PSM analyses. Sensitivity analyses for ACEI and ARB use separately yielded similar results., Conclusions: Our findings suggested that among patients undergoing dialysis with CAD, ACEI or ARB use was associated with a lower risk of all-cause and cardiovascular death.

Aims: Variability of metabolic parameters, such as glycemic variability (GV) and systolic blood pressure variability (SBPV), are associated with adverse cardiovascular outcomes. However, whether these parameters have additive effects on mortality in patients with coronary artery disease (CAD) hospitalized in the intensive care unit (ICU) remains unclear., Methods: We retrospectively enrolled patients with CAD from the Medical Information Mart for Intensive Care-IV database. The highest tertile of variability was defined as high variability. A variability scoring system was established, which assigned 0 points to tertile 1, 1 point to tertile 2, and 2 points to tertile 3 for GV and SBPV., Results: Among 4237 patients with CAD, 400 patients died in hospital, and 967 patients died during 1-year follow-up. High GV and high SBPV were associated with an increased risk of mortality. The effects of GV and SBPV on in-hospital mortality were partially mediated by ventricular arrhythmias (18.0 % and 6.6 %, respectively). The risk of mortality gradually increased with the number of high-variability parameters and increasing variability scores., Conclusions: GV and SBPV have additive effects on the risk of mortality in patients with CAD hospitalized in the ICU. Ventricular arrhythmias partially mediate the effects of GV and SBPV on in-hospital mortality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Stress hyperglycemia and glycemic variability (GV) can reflect dramatic increases and acute fluctuations in blood glucose, which are associated with adverse cardiovascular events. This study aimed to explore whether the combined assessment of the stress hyperglycemia ratio (SHR) and GV provides additional information for prognostic prediction in patients with coronary artery disease (CAD) hospitalized in the intensive care unit (ICU)., Methods: Patients diagnosed with CAD from the Medical Information Mart for Intensive Care-IV database (version 2.2) between 2008 and 2019 were retrospectively included in the analysis. The primary endpoint was 1-year mortality, and the secondary endpoint was in-hospital mortality. Levels of SHR and GV were stratified into tertiles, with the highest tertile classified as high and the lower two tertiles classified as low. The associations of SHR, GV, and their combination with mortality were determined by logistic and Cox regression analyses., Results: A total of 2789 patients were included, with a mean age of 69.6 years, and 30.1% were female. Overall, 138 (4.9%) patients died in the hospital, and 404 (14.5%) patients died at 1 year. The combination of SHR and GV was superior to SHR (in-hospital mortality: 0.710 vs. 0.689, p = 0.012; 1-year mortality: 0.644 vs. 0.615, p = 0.007) and GV (in-hospital mortality: 0.710 vs. 0.632, p = 0.004; 1-year mortality: 0.644 vs. 0.603, p < 0.001) alone for predicting mortality in the receiver operating characteristic analysis. In addition, nondiabetic patients with high SHR levels and high GV were associated with the greatest risk of both in-hospital mortality (odds ratio [OR] = 10.831, 95% confidence interval [CI] 4.494-26.105) and 1-year mortality (hazard ratio [HR] = 5.830, 95% CI 3.175-10.702). However, in the diabetic population, the highest risk of in-hospital mortality (OR = 4.221, 95% CI 1.542-11.558) and 1-year mortality (HR = 2.013, 95% CI 1.224-3.311) was observed in patients with high SHR levels but low GV., Conclusions: The simultaneous evaluation of SHR and GV provides more information for risk stratification and prognostic prediction than SHR and GV alone, contributing to developing individualized strategies for glucose management in patients with CAD admitted to the ICU., (© 2024. The Author(s).)

Background: The triglyceride-glucose (TyG) index has been suggested as a dependable indicator for predicting major adverse cardiovascular events (MACE) in individuals with cardiovascular conditions. Nevertheless, there is insufficient data on the predictive significance of the TyG index in end-stage renal disease (ESRD) patients with coronary artery disease (CAD)., Methods: This study, conducted at multiple centers in China, included 959 patients diagnosed with dialysis and CAD from January 2015 to June 2021. Based on the TyG index, the participants were categorized into three distinct groups. The study's primary endpoint was the combination of MACE occurring within one year of follow-up, including death from any cause, non-fatal myocardial infarction, and non-fatal stroke. We assessed the association between the TyG index and MACE using Cox proportional hazard models and restricted cubic spline analysis. The TyG index value was evaluated for prediction incrementally using C-statistics, continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI)., Results: The three groups showed notable variations in the risk of MACE (16.3% in tertile 1, 23.5% in tertile 2, and 27.2% in tertile 3; log-rank P = 0.003). Following complete adjustment, patients with the highest TyG index exhibited a notably elevated risk of MACE in comparison to those in the lowest tertile (hazard ratio [HR] 1.63, 95% confidence interval [CI] 1.14-2.35, P = 0.007). Likewise, each unit increase in the TyG index correlated with a 1.37-fold higher risk of MACE (HR 1.37, 95% CI 1.13-1.66, P = 0.001). Restricted cubic spline analysis revealed a connection between the TyG index and MACE (P for nonlinearity > 0.05). Furthermore, incorporating the TyG index to the Global Registry of Acute Coronary Events risk score or baseline risk model with fully adjusted factors considerably enhanced the forecast of MACE, as demonstrated by the C-statistic, continuous NRI, and IDI., Conclusions: The TyG index might serve as a valuable and dependable indicator of MACE risk in individuals with dialysis and CAD, indicating its potential significance in enhancing risk categorization in clinical settings., (© 2023. The Author(s).)

Background: The triglyceride-glucose (TyG) index is validated as a reliable biomarker of insulin resistance and an independent predictor of cardiovascular prognosis. However, the prognostic value of the TyG index in patients on dialysis with coronary artery disease (CAD) remained unexplored. This study aimed to determine the association between the TyG index and CAD severity and mortality in these patients., Methods: A total of 1061 dialysis patients with CAD were enrolled in this multi-center cohort study from January 2015 to June 2021. The extent and severity of CAD were evaluated using the multivessel disease and Gensini score (GS). Patients were followed up for all-cause death and cardiovascular death., Results: The multivariable logistic regression model indicated that the TyG index was significantly associated with multivessel disease (odds ratio [OR] 1.51, 95% confidence interval [CI] 1.18-1.94, P = 0.001), and high GS (OR 1.33, 95% CI 1.10-1.61, P = 0.003). After adjusting for baseline risk factors, the hazards of all-cause death and cardiovascular death were 1.23 (95% CI 1.06-1.43, P = 0.007), and 1.33 (95% CI 1.11-1.59, P = 0.002), independent of CAD severity. Restricted cubic spline analysis identified a dose-response association between the TyG index and both CAD severity and mortality (all P for nonlinearity > 0.05). When modeling the TyG index as a categorical variable, these independent associations remained. Subgroup analyses did not substantially modify the results. Furthermore, incorporating the TyG index into the existing risk prediction model improved the predictive accuracy for all-cause death and cardiovascular death, as evaluated by C-statistic, continuous net reclassification improvement, and integrated discrimination improvement., Conclusions: In patients on dialysis with CAD, the TyG index was significantly associated with more severe CAD as well as mortality. These results highlight the clinical importance of the TyG index for assessing CAD severity and risk stratification in patients on dialysis with CAD., (© 2023. BioMed Central Ltd., part of Springer Nature.)

After cardiac ischemia, there is often insufficient myocardial perfusion, even if flow has been successfully and completely restored in an upstream artery. This phenomenon, known as the "no-reflow phenomenon," is attributed to coronary microvascular dysfunction and has been associated with poor clinical outcomes. In clinical practice, a reduction in coronary flow reserve (CFR) is frequently used as an indicator of coronary artery disease. CFR is defined as the ratio of the peak flow velocity induced by pharmacologic or metabolic factors to the resting flow velocity. This protocol focused on assessing the dynamic changes in CFR before and after ischemia-reperfusion (IR) using pulse wave Doppler measurements. In this study, normal mice exhibited the ability to increase the peak velocity of coronary blood flow up to two times higher than the resting values under isoflurane stimulation. However, after ischemia-reperfusion, the CFR at 1 h significantly decreased compared to the pre-operation baseline. Over time, the CFR showed gradual recovery, but it remained below the normal level. Despite the preservation of systolic function, early detection of microvascular dysfunction is crucial, and establishing a practical guide could aid doctors in this task, while also facilitating the study of cardiovascular disease progression over time.

Objective: This study aimed to explore the association between the triglyceride glucose index (TyG) and the risk of in-hospital and one-year mortality in patients with chronic kidney disease (CKD) and cardiovascular disease (CAD) admitted to the intensive care unit (ICU)., Methods: The data for the study were taken from the Medical Information Mart for Intensive Care-IV database which contained over 50,000 ICU admissions from 2008 to 2019. The Boruta algorithm was used for feature selection. The study used univariable and multivariable logistic regression analysis, Cox regression analysis, and 3-knotted multivariate restricted cubic spline regression to evaluate the association between the TyG index and mortality risk., Results: After applying inclusion and exclusion criteria, 639 CKD patients with CAD were included in the study with a median TyG index of 9.1 [8.6,9.5]. The TyG index was nonlinearly associated with in-hospital and one-year mortality risk in populations within the specified range., Conclusion: This study shows that TyG is a predictor of one-year mortality and in-hospital mortality in ICU patients with CAD and CKD and inform the development of new interventions to improve outcomes. In the high-risk group, TyG might be a valuable tool for risk categorization and management. Further research is required to confirm these results and identify the mechanisms behind the link between TyG and mortality in CAD and CKD patients., (© 2023. The Author(s).)

Objective: The serum anion gap (AG) has been reported to be an important prognostic indicator for patients in intensive care units. To explore the potential relationship between the serum AG and 30-day mortality in patients who underwent CABG., Patients and Methods: All data were collected from the Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) database. We divided patients into 3 groups according to AG tertiles. The primary outcome of our study was the 30-day mortality of patients who underwent CABG. The relationship between the serum AG and mortality in individuals who underwent CABG was estimated using Cox proportional hazard models. Subgroup analysis for effect modification was conducted with a likelihood ratio test., Results: A total of 5,102 eligible subjects were included in our analysis. After adjusting for confounding factors, every unit increase in the AG was associated with a 22% higher odds of 30-day mortality in patients who underwent CABG [hazard ratio (HR), 95% confidence interval (CI): 1.22, 1.13-1.33] When the AG was converted into a categorical variable, the high AG group had a higher risk of 30-day mortality than the low AG group in the fully adjusted model (HR, 95% CI: 3.99, 1.35-11.76). Tests for trends were statistically significant (p-value < 0.05). Subgroup analysis demonstrated that higher mortality was related to the subgroups of people ≥ 70 years and females., Conclusions: The serum AG was an independent predictor of short-term prognosis in patients who underwent CABG. A high AG was associated with an increased risk of 30-day mortality after CABG.

Objective: Chronic kidney disease (CKD) patients with coronary artery disease (CAD) in the intensive care unit (ICU) have higher in-hospital mortality and poorer prognosis than patients with either single condition. The objective of this study is to develop a novel model that can predict the in-hospital mortality of that kind of patient in the ICU using machine learning methods., Methods: Data of CKD patients with CAD were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Boruta algorithm was conducted for the feature selection process. Eight machine learning algorithms, such as logistic regression (LR), random forest (RF), Decision Tree, K-nearest neighbors (KNN), Gradient Boosting Decision Tree Machine (GBDT), Support Vector Machine (SVM), Neural Network (NN), and Extreme Gradient Boosting (XGBoost), were conducted to construct the predictive model for in-hospital mortality and performance was evaluated by average precision (AP) and area under the receiver operating characteristic curve (AUC). Shapley Additive Explanations (SHAP) algorithm was applied to explain the model visually. Moreover, data from the Telehealth Intensive Care Unit Collaborative Research Database (eICU-CRD) were acquired as an external validation set., Results: 3590 and 1657 CKD patients with CAD were acquired from MIMIC-IV and eICU-CRD databases, respectively. A total of 78 variables were selected for the machine learning model development process. Comparatively, GBDT had the highest predictive performance according to the results of AUC (0.946) and AP (0.778). The SHAP method reveals the top 20 factors based on the importance ranking. In addition, GBDT had good predictive value and a certain degree of clinical value in the external validation according to the AUC (0.865), AP (0.672), decision curve analysis, and calibration curve., Conclusion: Machine learning algorithms, especially GBDT, can be reliable tools for accurately predicting the in-hospital mortality risk for CKD patients with CAD in the ICU. This contributed to providing optimal resource allocation and reducing in-hospital mortality by tailoring precise management and implementation of early interventions., (© 2023. The Author(s).)

Background: The present study is aimed at identifying the differentially expressed genes (DEGs) and relevant biological processes and pathways associated with epicardial adipose tissue (EAT) from patients with coronary artery disease (CAD). We also explored potential biomarkers using two machine-learning algorithms and calculated the immune cell infiltration in EAT., Materials and Methods: Three datasets (GSE120774, GSE64554, and GSE24425) were obtained from the Gene Expression Omnibus (GEO) database. The GSE120774 dataset was used to evaluate DEGs between EAT of CAD patients and the control group. Functional enrichment analyses were conducted to study associated biological functions and mechanisms using the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA). After this, the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) were performed to identify the feature genes related to CAD. The expression level of the feature genes was validated in GSE64554 and GSE24425. Finally, we calculated the immune cell infiltration and evaluated the correlation between the feature genes and immune cells using CIBERSORT., Results: We identified a total of 130 upregulated and 107 downregulated genes in GSE120774. Functional enrichment analysis revealed that DEGs are associated with several pathways, including the calcium signaling pathway, complement and coagulation cascades, ferroptosis, fluid shear stress and atherosclerosis, lipid and atherosclerosis, and regulation of lipolysis in adipocytes. TCF21, CDH19, XG, and NNAT were identified as feature genes and validated in the GSE64554 and GSE24425 datasets. Immune cell infiltration analysis showed plasma cells are significantly more numerous in EAT than in the control group ( p = 0.001), whereas macrophage M0 ( p = 0.024) and resting mast cells ( p = 0.036) were significantly less numerous. TCF21, CDH19, XG, and NNAT were correlated with immune cells, including plasma cells, M0 macrophages, and resting mast cells., Conclusion: TCF21, CDH19, XG, and NNAT might serve as feature genes for CAD, providing new insights for future research on the pathogenesis of cardiovascular diseases., Competing Interests: The authors declare no conflict of interest., (Copyright © 2022 Yisen Deng et al.)

Background: Accumulating evidence has indicated that persistent human cytomegalovirus (HCMV) infection is associated with several cardiovascular diseases including atherosclerosis and coronary artery disease. However, whether there is a causal association between the level of anti-HCMV immune response and the risk of cardiovascular diseases remains unknown., Methods: Single-nucleotide polymorphisms associated with anti-cytomegalovirus immunoglobulin (Ig) G levels were used as instrumental variables to estimate the causal effect of anti-cytomegalovirus IgG levels on 9 cardiovascular diseases (including atrial fibrillation, coronary artery disease, hypertension, heart failure, peripheral artery disease, pulmonary embolism, deep vein thrombosis of the lower extremities, rheumatic valve diseases, and non-rheumatic valve diseases). For each cardiovascular disease, Mendelian randomization (MR) analyses were performed. Inverse variance-weighted meta-analysis (IVW) with a random-effects model was used as a principal analysis. In addition to this, the weighted median approach and MR-Egger method were used for further sensitivity analysis., Results: In the IVW analysis, genetically predicted anti-cytomegalovirus IgG levels were suggestively associated with coronary artery disease with an odds ratio (OR) of 1.076 [95% CI, 1.009-1.147; p = 0.025], peripheral artery disease (OR 1.709; 95% CI, 1.039-2.812; p = 0.035), and deep vein thrombosis (OR 1.002; 95% CI, 1.000-1.004; p = 0.025). In the further analysis, similar causal associations were obtained from weighted median analysis and MR-Egger analysis with lower precision. No notable heterogeneities and horizontal pleiotropies were observed (p > 0.05)., Conclusions/interpretation: Our findings first provide direct evidence that genetic predisposition of anti-cytomegalovirus IgG levels increases the risk of coronary artery disease, peripheral artery disease, and deep vein thrombosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tan, Ren, Fan, Wei, Hu, Zhu, Yang and Cai.)