BACKGROUND:Although drug-coated balloons (DCBs) demonstrate efficacy in de novo coronary artery disease, patients with non-small vessel lesions (NSVLs, ≥2.75 mm) face elevated risks of rescue stenting due to procedure-related coronary dissection. Radial wall stress maximum (RWSmax), an angiography-derived parameter reflecting plaque vulnerability, may predict dissection severity and optimize patient selection for DCB strategies. OBJECTIVES:This study aimed to evaluate the predictive value of RWSmax for severe coronary dissection following DCB treatment in de novo NSVL. METHODS:This study retrospectively analyzed 194 patients with de novo NSVL who were evaluated for DCB angioplasty. Dissections were classified via National Heart, Lung, and Blood Institute criteria: nonsevere (no dissection or Type A/B) vs severe (Type C-F). RWSmax was quantified using electrocardiography-gated angiographic analysis (AngioPlus Core software). Multivariable regression and receiver operating characteristic analyses identified predictors of severe dissection. RESULTS:Severe dissections occurred in 32.0% (62 of 194), predominantly Type C (83.9%, 52 of 62). RWSmax increased progressively with dissection severity (Jonckheere-Terpstra P < 0.001) and was higher compared with patients with nonsevere dissections (14.70% [12.80-16.65] vs 12.20% [11.00-13.30], P < 0.001). RWSmax independently predicted severe dissection (adjusted OR per 1%: 1.55; 95% CI: 1.31-1.90; P < 0.001), with an optimal cutoff of 13.7% (area under the curve = 0.752 [0.673-0.831], sensitivity = 61.3% [56.5% to 66.1%], specificity = 81.1%[74.4% to 87.8%]). Incorporating RWSmax into clinical prediction models significantly improved discrimination (Δarea under the curve = +0.093 [0.035-0.151]; P = 0.008). Subgroup analyses confirmed consistency across lesion types, calcification severity, and operator experience levels. CONCLUSIONS:RWSmax is a robust, angiography-based predictor of severe coronary dissection after DCB in NSVL. A 13.7% cutoff helps identify high-risk patients, supporting precision selection for DCB strategy.

Although oxidative stress (OS) links to the pathogenesis of coronary artery disease (CAD), its underlying genetic mechanisms remain unclear. Through summary data-based Mendelian randomization (SMR) and colocalization, this research seeks to assess the potential causal links between OS-related genes and CAD. Summary-level data on the methylation, expression, and protein abundance levels of OS-related genes were obtained from the corresponding quantitative trait loci (QTL) studies. We obtained genome-wide association study summary statistics for CAD from a previous study (discovery), the FinnGen and UK Biobank (replication). Two-sample MR analysis was conducted to verify the associations between key genes expressions and meta-analysis cohort of CAD risk. Mediation analysis was conducted to evaluate the mediating role of gene expression variation in the causal pathway linking methylation levels of key loci to the risk or progression of the disease. We identified 35 methylation loci, 7 genes, and 12 proteins in the discovery cohort. By integrating multiomic data, we identified SMARCA4, NAGLU, SREBF1, RPTOR, and HLA-B as potential causal targets associated with CAD. The two-sample MR analysis once again confirmed that the expressions of the SMARCA4, SREBF1, and HLA-B genes in the meta-analysis cohort showed a significant association with the risk of CAD, and this association was consistent with the direction of the SMR. Furthermore, both the expression and methylation of SMARCA4 were positively associated with CAD, and the direct and indirect effects of SMARCA4 methylation were confirmed. In summary, our results identified potential causal associations between SMARCA4, NAGLU, SREBF1, RPTOR, HLA-B, and CAD. The findings highlight the necessity for further exploration into the underlying etiology of CAD.

Background A novel computational angiographic microcirculatory resistance (AMR) derived from a single angiographic view presents a feasible alternative to the pressure wire‐based index of microcirculatory resistance. However, its prognostic significance in patients undergoing percutaneous coronary intervention (PCI) remains insufficiently established. Methods This is a post hoc analysis of 3404 patients undergoing PCI from the FAVOR III China (Comparison of Quantitative Flow Ratio Guided and Angiography Guided Percutaneous Intervention in Patients With Coronary Artery Disease) trial. Pre‐ and post‐PCI AMR were measured in target vessels, with percentage change in AMR before and after PCI calculated as (100×[post‐PCI AMR−pre‐PCI AMR]/pre‐PCI AMR). The primary model used was the log‐rank test, and the proportional hazards model was also used to assess the association between AMR and the 3‐year risk of major adverse cardiac events, defined as a composite of all‐cause death, myocardial infarction, or ischemia‐driven revascularization. Results Patients with percentage change in AMR before and after PCI ≥85 (23.7%) versus <85 (76.3%) had comparable baseline characteristics but received more and longer stents per patient. Overall major adverse cardiac events risk was similar between groups (14.8% versus 12.4%; hazard ratio [HR], 1.18 [0.95–1.45]; log‐rank P=0.064). However, in patients with post‐PCI AMR ≥250, percentage change in AMR before and after PCI ≥85 showed a significant increase in the major adverse cardiac events risk (16.3% versus 10.8%; HR, 1.52 [1.14–2.04]), contrasting with no difference when post‐PCI AMR <250 (12.3% versus 13.4%; HR, 0.89 [0.63–1.25]; Pinteraction=0.019). Conclusions In patients undergoing PCI from the FAVOR III China population, significant AMR elevation (percentage change in AMR before and after PCI ≥85) in target vessels alone did not predict outcomes, but in the subgroup with post‐PCI AMR ≥250 it identified patients at increased 3‐year cardiovascular risk. REGISTRATION https://www.clinicaltrials.gov; Unique identifier: NCT03656848.

PURPOSE:Coronary artery disease (CAD) is a leading cause of cardiovascular morbidity and mortality worldwide. Recent studies suggest disruptions in circadian rhythms may contribute to CAD, but the underlying mechanisms remain unclear. This study employs summary-data-based Mendelian randomization to explore the roles of circadian rhythm genes in CAD and their clinical implications. METHODS:We retrieved circadian rhythm-related genes from the GeneCards database and utilized genome-wide association study summary data for CAD from the IEU database, further validated with FinnGen and UK Biobank datasets. We integrated expression quantitative trait loci (eQTL), methylation quantitative trait loci (mQTL), and protein abundance quantitative trait loci (pQTL) data to assess causal associations with CAD. Colocalization analysis confirmed that the signals originated from the same genetic variants. RESULTS:Our analyses identified 49 mQTLs, 11 eQTLs, and one pQTL causally associated with CAD. Integration of mQTL and eQTL data revealed 13 methylation sites and eight key genes, particularly RASD1 (OR = 0.777, 95% CI: 0.672-0.898) and SREBF1 (OR = 0.893, 95% CI: 0.844-0.946). The DNA methylation level at site cg20122488 was negatively correlated with RASD1 expression, while eQTL data for SREBF1 indicated a regulatory relationship with CAD risk. CONCLUSIONS:This study emphasizes the significant roles of circadian rhythm genes RASD1 and SREBF1 in CAD pathogenesis. Findings suggest therapeutic potential for these genes, warranting further research to validate their functions and inform preventive and treatment strategies. Key messages What is already known Coronary artery disease (CAD) is a leading global cause of cardiovascular mortality, with circadian rhythm disruptions increasingly implicated in its pathogenesis, though causal genetic mechanisms remain unclear. What this study adds This Mendelian randomization study identifies 13 methylation sites and eight key circadian-related genes (e.g. RASD1, SREBF1) with causal links to CAD, revealing specific epigenetic and transcriptional regulatory effects on disease risk. How this study might affect research, practice, or policy The findings highlight circadian rhythm genes as potential therapeutic targets, offering novel insights for CAD prevention strategies and guiding future research into circadian-based interventions.

BACKGROUND:Long-term mortality remains unsatisfactorily high after transcatheter aortic valve replacement (TAVR). Conventional risk models are limited in capturing subclinical electrophysiological alterations associated with poor prognosis, which can be identified on routine preoperative electrocardiograms. OBJECTIVES:The authors aim to develop and validate an artificial intelligence-enhanced electrocardiogram (AI-ECG) model for predicting long-term mortality in post-TAVR patients. METHODS:A total of 711 patients with severe aortic stenosis undergoing TAVR were enrolled from 2 centers. Patients from one center were divided into training and internal validation sets (7:3), and participants from another center served as the external validation cohort. Preoperative electrocardiogram images were analyzed using a Residual Network-18 model to generate mortality risk stratification. The primary endpoint was 3-year all-cause death. RESULTS:The AI-ECG model demonstrated comparable discrimination between the internal and external patient cohorts, with areas under the receiver operating characteristics curve of 0.767 (95% CI: 0.657-0.877) vs 0.712 (95% CI: 0.627-0.795) (P for DeLong test = 0.428). High-risk patients (15.5% [39 of 251]) exhibited a 61.5% (24 of 39, 95% CI: 42.8%-74.1%) 3-year mortality rate vs 16.5% (35 of 212, 95% CI: 11.4%-21.4%) in low-risk patients (84.5% [212 of 251]) (log-rank P < 0.001). Adjusted for comorbidities, high-risk classification independently predicted mortality (adjusted HR: 3.49; 95% CI: 1.96-6.22). Subgroup analysis did not reveal significant interaction effects of the AI-ECG model across different patient populations. Decision curve analysis confirmed clinical net benefit across threshold probabilities (0.05-0.60). CONCLUSIONS:The AI-ECG model provides noninvasive and accurate long-term risk stratification for TAVR patients, with promising clinical application value for individualized follow-up management.

BACKGROUND:Atherosclerosis (AS) is a leading cause of cardiovascular diseases, with lipid metabolism disorders playing a key role in its development. This study used Mendelian randomization (MR) analysis to examine the causal links between four lipid traits [high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG), and total cholesterol (TC)] and AS risk, and also investigated the polygenic risk score (PRS) and potential molecular mechanisms. METHODS:Genome-Wide Association Study GWAS summary data for lipid traits from the Integrative Epidemiology Unit IEU and Finngen databases were used for MR analysis to assess the causal link between lipid traits and AS risk. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) data were used to evaluate the PRS of AS. Drug enrichment analysis and molecular docking were performed to identify potential drug targets. RESULTS:Higher HDL levels were associated with a decreased risk of AS (OR = 0.8038, P = 0.000014), while higher LDL, TC, and TG levels were linked to increased AS risk (OR = 1.0147, P = 9.95 × 10 -13 ; OR = 1.0163, P = 8.98 × 10 -16 ; OR = 1.0087, P = 4.32 × 10 -4 ). Drug enrichment analysis highlighted potential drug targets, including HMGCR binding with STIGMASTEROL and Benzofurans. PRS analysis revealed that multiple lipid metabolism-related genes influence AS susceptibility. CONCLUSION:The study demonstrated a clear causal relationship between lipid traits and AS risk. Higher HDL levels were associated with a reduced risk, while higher LDL, TC, and TG levels increase AS risk. The role of lipid metabolism genes in AS pathogenesis was underscored by PRS analysis.

BACKGROUND:Lipoprotein(a) (Lp[a]) has been identified as a significant risk factor for aortic stenosis (AS). However, its impact on outcomes post-transcatheter aortic valve replacement (TAVR) remains unknown. OBJECTIVE:To investigate the association between Lp(a) levels and long-term outcomes as well as its impact on the bioprosthetic valve degeneration in patients post-TAVR. METHODS:Patients with severe AS who underwent TAVR were consecutively recruited. Lp(a) was measured before TAVR procedure. The subjects were divided according to levels of Lp(a). The outcomes were all-cause mortality and possible structural valve degeneration (SVD) measured by Doppler echocardiography. Cox regression models and competing risk models were used to explore the association between Lp(a) levels and outcomes. RESULTS:Of the 601 included patients (mean age: 75.5 ± 7.2, male: 58.7%), 137 patients (22.7%) experienced mortality after a median follow-up of 3.9 years. After multivariable adjustment, elevated Lp(a) (defined as ≥30 mg/dL) was identified as an independent predictor of all-cause mortality (hazard ratio [HR]: 1.81, 95% CI: 1.27-2.57, P = .001) and cardiovascular mortality (HR: 2.02, 95% CI: 1.12-3.66, P = .020). Elevated Lp(a) was also associated with increased risk of possible SVD (subdistribution HR: 3.40, 95% CI: 1.32-8.79, P = .012). Using a threshold value of 50 mg/dL for elevated Lp(a) still supported the main findings. CONCLUSION:Elevated baseline Lp(a) levels are associated with poor clinical outcomes and possible SVD in patients with severe AS undergoing TAVR. Further research is warranted to confirm these findings.

Background The optimal timing of transcatheter aortic valve replacement (TAVR) for asymptomatic or minimally symptomatic patients with severe aortic stenosis (AS) remains controversial. Microvascular dysfunction and increased microcirculatory resistance have been linked to adverse outcomes in AS, suggesting that resting angiographic microvascular resistance (AMRr) may aid in identifying higher-risk patients. Method We conducted a retrospective study of 180 severe AS patients who underwent TAVR at Fuwai Hospital between 2012 and 2021. Patients were grouped based on an AMRr cutoff value of 490, identified through receiver operating characteristic (ROC) analysis. The primary endpoint was the incidence of major adverse cardiovascular events (MACE), including all-cause mortality, heart failure, and myocardial infarction. Kaplan-Meier and Cox regression analyses were used to compare outcomes between groups. Results A total of 180 asymptomatic or minimally symptomatic AS patients undergoing TAVR were enrolled. After a 40-month follow-up, the AMRr >490 group had a higher MACE risk, mainly driven by readmission for heart failure. Additionally, continuous analysis indicated that every 100-unit increase in AMRr was associated with an 18 %, 17 %, and 1.58-fold increased risk of MACE, all-cause mortality, and NOAF, respectively. Moreover, the addition of AMRr to a clinical model significantly improved the prediction of MACE (AUC 0.678 vs. 0.582, p = 0.023). Conclusion Asymptomatic or minimally symptomatic AS patients with AMRr >490 had a significantly higher incidence of MACE and heart failure rehospitalization than those with AMRr ≤490 after TAVR. The inclusion of AMRr in a predictive model improved the accuracy for long-term MACE, demonstrating an incremental prognostic value.

Purpose: The impact of periprocedural myocardial injury (PPMI) according to VARC-3 criteria in patients undergoing transcatheter aortic valve replacement (TAVR) remains unclear. This study aimed to investigate the incidence, risk factors, and prognosis of PPMI in patients with severe aortic who underwent TAVR in China. Materials and Methods: Between September 2012 and November 2021, 516 patients with severe aortic stenosis who underwent TAVR at the Fuwai Hospital were consecutively enrolled. PPMI was defined according to the VARC-3 criteria as a 70-fold increase of upper reference limit in cardiac troponin I (cTnI) levels. We compared the baseline characteristics, perioperative conditions, and inhospital and long-term endpoints between the PPMI and non-PPMI groups. Logistic regression analysis was used to determine the predictors of PPMI. Survival probabilities for outcomes between the PPMI and non-PPMI groups were estimated using the Kaplan Results: Of the enrolled patients (mean age: 75.5 +/- 7.2 years, 57.5% male), the incidence of PPMI was 20.5%. The median cTnI was 24.9 (interquartile range: 11.4-60.2) times the upper reference limit. After multivariable adjustment, female sex (odds ratio [OR]: 3.01, 95% confidence interval [CI]: 1.88-4.82, P < 0.001), anticoagulant use (OR: 0.27, 95% CI: 0.08-0.96, P = 0.043), balloon-expandable valve (OR: 0.27, 95% CI: 0.09-0.79, P = 0.017), and secondary valve implantation (OR: 2.66, 95% CI: 1.40-5.03, P = 0.003) were significantly associated with PPMI. Patients with PPMI had short- and long-term outcomes similar to those without PPMI. Conclusion: Female sex and secondary valve implantation are predictors of an increased risk of PPMI, whereas baseline anticoagulant use and the use of balloon-expandable valves are protective factors. The presence of PPMI does not seem to indicate poor short- or long-term prognosis in patients undergoing TAVR.

Transcatheter aortic valve replacement (TAVR) is a well-established technique for the treatment of aortic stenosis (AS). However, due to the complex anatomical features of the aortic root, the risk of vascular injury caused by operation under the condition of anatomical variations of the aortic root is high, and there is a lack of studies on the anatomical features of the aortic root on CT before TAVR. Therefore, this study will preliminarily summarize anatomical features of aortic root in patients with aortic stenosis treated by TAVR. A retrospective study was conducted at a single center, involving 60 patients with symptomatic severe AS treated TAVR between September 2022 and December 2022. Baseline patient information, CT measurements of aortic root anatomical characteristics, and associated risks were analyzed. The mean age of the 60 patients was 77.72 ± 4.33 years, with 39 males (65.00

BACKGROUND:The rapid increase in the number of transcatheter aortic valve replacement (TAVR) procedures in China and worldwide has led to growing attention to hypoattenuating leaflet thickening (HALT) detected during follow-up by 4D-CT. It's reported that HALT may impact the durability of prosthetic valve. Early identification of these patients and timely deployment of anticoagulant therapy are therefore particularly important. METHODS:We retrospectively recruited 234 consecutive patients who underwent TAVR procedure in Fuwai Hospital. We collected clinical information and extracted morphological characteristics parameters of the transcatheter heart valve (THV) post TAVR procedure from 4D-CT. LASSO analysis was conducted to select important features. Three models were constructed, encapsulating clinical factors (Model 1), morphological characteristics parameters (Model 2), and all together (Model 3), to identify patients with HALT. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were plotted to evaluate the discriminatory ability of models. A nomogram for HALT was developed and verified by bootstrap resampling. RESULTS:In our study patients, Model 3 (AUC = 0.738) showed higher recognition effectiveness compared to Model 1 (AUC = 0.674, p = 0.032) and Model 2 (AUC = 0.675, p = 0.021). Internal bootstrap validation also showed that Model 3 had a statistical power similar to that of the initial stepwise model (AUC = 0.723 95%CI: 0.661-0.786). Overall, Model 3 was rated best for the identification of HALT in TAVR patients. CONCLUSION:A comprehensive predictive model combining patient clinical factors with CT-based morphology parameters has superior efficacy in predicting the occurrence of HALT in TAVR patients.

Background Stress hyperglycemia ratio (SHR) has recently been recognized as a novel biomarker that accurately reflects acute hyperglycemia status and is associated with poor prognosis of heart failure. We evaluated the relationship between SHR and clinical outcomes in patients with severe aortic stenosis receiving transcatheter aortic valve replacement (TAVR). Methods There were 582 patients with severe native aortic stenosis who underwent TAVR consecutively enrolled in the study. The formula used to determine SHR was as follows: admission blood glucose (mmol/L)/(1.59×HbA 1c [%]–2.59). The primary endpoint was defined as all-cause mortality, while secondary endpoints included a composite of cardiovascular mortality or readmission for heart failure, and major adverse cardiovascular events (MACE) including cardiovascular mortality, non-fatal myocardial infarction, and non-fatal stroke. Multivariable Cox regression and restricted cubic spline analysis were employed to assess the relationship between SHR and endpoints, with hazard ratios (HRs) and 95% confidence intervals (CIs). Results During a median follow-up of 3.9 years, a total of 130 cases (22.3%) of all-cause mortality were recorded. Results from the restricted cubic spline analysis indicated a linear association between SHR and all endpoints (p for non-linearity > 0.05), even after adjustment for other confounding factors. Per 0.1 unit increase in SHR was associated with a 12% (adjusted HR: 1.12, 95% CI: 1.04–1.21) higher incidence of the primary endpoint, a 12% (adjusted HR: 1.12, 95% CI: 1.02–1.22) higher incidence of cardiovascular mortality or readmission for heart failure, and a 12% (adjusted HR: 1.12, 95% CI: 1.01–1.23) higher incidence of MACE. Subgroup analysis revealed that SHR had a significant interaction with diabetes mellitus with regard to the risk of all-cause mortality (p for interaction: 0.042). Kaplan-Meier survival analysis showed that there were significant differences in the incidence of all endpoints between the two groups with 0.944 as the optimal binary cutoff point of SHR (all log-rank test: p < 0.05). Conclusions Our study indicates linear relationships of SHR with the risk of all-cause mortality, cardiovascular mortality or readmission for heart failure, and MACE in patients with severe aortic stenosis receiving TAVR after a median follow-up of 3.9 years. Patients with an SHR exceeding 0.944 had a poorer prognosis compared to those with lower SHR values.