Citations

Background In low-gradient severe aortic stenosis (AS), reduced left ventricular ejection fraction (LVEF <50%) is practically used to define low flow and prompt dobutamine stress echocardiography to discern pseudo-severe AS. In patients with preserved LVEF, stroke volume index (SVI) <35 mL/m² is typically used. However, both are volume-based surrogates. Transaortic flow rate (TAFR), calculated as stroke volume divided by left ventricular ejection time, may better reflect true flow. Nonetheless, comparative data between TAFR and established metrics remain limited. We aimed to evaluate the prognostic value of TAFR in symptomatic low-gradient severe AS. Methods We retrospectively identified patients with low-gradient severe AS (AVA ≤1 cm 2 and peak velocity (Vmax) <4 m/s or mean gradient (MG) <40 mm Hg) who underwent transcatheter aortic valve replacement at Mayo Clinic sites (2017–2023). The primary outcome was 1-year all-cause mortality. Survival was assessed using Kaplan-Meier and Cox proportional hazards models. Results Among 475 patients included (mean age 85±8 years; 49% women), 242 (51%) had TAFR <220 mL/s, 165 (35%) had EF <50%, and 221 (47%) had SVI <35 mL/m 2 . Low TAFR was significantly associated with higher 1-year mortality even after stratifying by EF or SVI. In multivariate analysis, TAFR was an independent predictor of mortality (HR 2.38; 95% CI 1.19 to 4.76, p=0.014) after adjusting for reduced LVEF, low SVI, gender, chronic kidney disease and mitral and tricuspid regurgitation. Conclusions In patients with symptomatic low-gradient severe AS, low TAFR, not SVI or LVEF, is independently associated with mortality and may offer more accurate measure of flow state for clinical staging.

aims: We assessed the diagnostic accuracy of the SVEAT score in predicting 30-day major adverse cardiac events (MACE) in comparison with the well-established HEART and TIMI scores. background: Acute chest pain (ACP) is a common symptom in emergency departments. Various risk stratification tools have been developed to assess patients presenting with ACP. The Simple Vascular Event Assessment Tool (SVEAT) is the most recent scoring system introduced, based on five variables: Symptoms of chest pain, history of Vascular disease, ECG, Age, and Troponin-I. objective: We assessed the diagnostic accuracy of the SVEAT score in predicting 30-day major adverse cardiac events (MACE) in comparison with the well-established HEART and TIMI scores. method: Following PRISMA guidelines, a systematic literature search was conducted across five databases until June 22, 2024. Four studies comprising 1,520 patients were included in this meta-analysis. The predictive accuracy of the SVEAT, HEART, and TIMI scores for 30-day MACE was assessed by the area under the receiver operating characteristic curve (AUC). Heterogeneity was evaluated using the I² statistic, with values over 75% indicating significant heterogeneity. Indirect comparisons among the scores were performed using the Z-test. result: Pooled AUC for the SVEAT score was 0.92 (95% CI: 0.86-0.98), indicating superior predictive accuracy compared to the HEART (AUC: 0.86, 95% CI: 0.81-0.92) and TIMI (AUC: 0.82, 95% CI: 0.69-0.96) scores. However, significant heterogeneity (I² = 90.6%) was observed across studies, potentially due to variations in patient demographics, clinical settings, and outcome definitions. Despite the higher AUC, indirect Z-test comparisons revealed no statistically significant differences between the scoring systems. conclusion: SVEAT score demonstrates potential as an accurate tool for predicting 30-day MACE in patients with ACP. other: N/A

Abstract Background Loeys-Dietz Syndrome (LDS) is a connective tissue disorder caused by mutations in the TGFBR1 or TGFBR2 genes, leading to significant cardiovascular complications, particularly aortic aneurysms and dissections. Due to the progressive nature of these issues, patients often require multiple cardiac interventions throughout their lives, although this has not been comprehensively reviewed in the literature. Purpose This study aims to review trends in cardiac interventions in LDS patients to better understand the surgical course these patients go through in their lives. Methods A retrospective analysis was conducted on a cohort of individuals diagnosed with LDS at our institution. Medical records were reviewed for data on demographics and types of interventions (e.g., aortic surgeries, valve procedures) were collected. Descriptive statistics were used to analyze the frequency of interventions with comparisons made between intervention types. Results A total of 94 patients with LDS were included in the study. Among them, 69 patients (73.4%) had an ascending aortic aneurysm, and 13 patients (14%) had a type A aortic dissection. A total of 60 patients underwent aortic root replacement surgery due to aneurysm or dissection, with 10 patients (11%) having the procedure following the occurrence of a dissection. Mitral valve prolapse (MVP) was found in 34 patients (36%). Valvular interventions were performed as follows, with some patients undergoing repairs on multiple valves: 12 patients (13%) had mitral valve repair, 10 patients (11%) had tricuspid valve repair, and the aortic valve was the most intervened upon, with 37 patients (39.5%) undergoing either replacement or repair. In total, 45 patients (48%) underwent at least one valvular intervention. Additionally, 4 patients (4.5%) underwent ventricular septal defect (VSD) closure, 3 (3.5%) underwent atrial septal defect (ASD) closure, and 3 (3.5%) had both defects closed. 29 patients (31%) had a patent foramen ovale, with 17 of these patients (59%) undergoing PFO closure. Finally, 16 patients (17%) underwent coronary artery bypass grafting (CABG). Conclusion Patients with LDS often require multiple surgeries and interventions throughout their lives due to the progressive nature of the disease and its impact on the cardiovascular system. The high incidence of aortic aneurysms, dissections, and valvular abnormalities necessitates frequent surgical management, with many patients undergoing interventions such as aortic root replacement, valve repairs, and septal defect closures. Given the complex and multifaceted cardiovascular involvement in LDS, close monitoring and timely intervention are crucial for optimizing outcomes and improving quality of life for these patients.

Abstract Background Marfan syndrome (MFS) predisposes individuals to aortic dissections. Recent data suggest that atrial fibrillation and atrial flutter (AF/AFL) may increase complications and mortality in MFS patients; however, their independent role in aortic dissection remains unclear. Purpose This study aims to assess the risk of aortic dissection in MFS patients with and without AF/AFL. Methods Using the TriNetX database and ICD-10 codes, 2,447 MFS patients with AF/AFL and 20,520 without were identified. Demographics (age, sex, race, ethnicity) were evaluated, and aortic dissection outcomes were compared using risk ratios and Kaplan-Meier survival analysis. Results Patients in the AF/AFL cohort were older (mean age 60.9 ± 16.7 years vs. 38 ± 16.6 years) and had higher proportions of males (62.51% vs. 56.76%) and white patients (74.67% vs. 66.3%). Aortic dissections occurred in 13.9% of MFS patients with AF/AFL compared to 3.4% of those without, resulting in a risk difference of 10.5% (95% CI: 9.0%–11.9%) and a risk ratio of 4.04 (95% CI: 3.547–4.603). Kaplan-Meier analysis revealed significantly lower survival rates in the AF/AFL cohort (74.07% vs. 90.63%; log-rank test, p &lt; 0.0001), with a hazard ratio of 4.232 (95% CI: 3.686–4.858). Conclusion In MFS patients, those with AF/AFL were over four times more likely to experience aortic dissection and had over four times the hazard of mortality. Screening and managing AF/AFL may be essential to preventing aortic dissections and improving outcomes in this population.Figure 1

Key Points Atrial fibrillation after kidney transplantation is common and is associated with poor prognosis. Artificial intelligence applied to 12-lead electrocardiograms pretransplant accurately predicts the risk of new-onset atrial fibrillation in our cohort. High-risk artificial intelligence electrocardiography score was independently associated with increased risk of mortality and allograft failure. Background Incident atrial fibrillation (AF) is common after kidney transplantation (KTx) and is associated with worse clinical outcomes. Artificial intelligence electrocardiography (AI-ECG) algorithms have demonstrated efficacy in predicting risk of new-onset AF in the general population; however, their prognostic value in KTx recipients is relatively unknown. Methods Retrospective analysis was conducted on KTx recipients without AF, with at least one pretransplant ECG between 2011 and 2021 across three tertiary centers in the United States (Mayo Clinic sites in MN, AZ, and FL). A previously validated AI-ECG algorithm estimated the probability of incident AF for each patient. Based on AI-ECG probabilities, patients were categorized into high-risk and low-risk groups, with the optimal AI-ECG score cutoff determined. The incidence of new-onset AF, allograft failure, and mortality was compared between groups. Results Overall, 6246 patients (age 53.5±13.8 years; 58.9% male) were included. Pretransplant AI-ECG probability of AF ≥5% was the optimal cutoff for high risk of incident AF (sensitivity 72%, specificity 62%). High-risk scores were associated with true new-onset AF at 30 days (adjusted hazard ratio [aHR], 2.89; 95% confidence intervals [CI], 2.05 to 4.09; P < 0.001), 3 years (aHR, 2.54; 95% CI, 1.99 to 3.26, P < 0.001), and 5 years post-transplant (aHR, 2.48; 95% CI, 1.99 to 3.09, P < 0.001). High-risk AI-ECG scores were also associated with increased mortality (aHR, 1.56; 95% CI, 1.30 to 1.88, P < 0.001) and overall allograft failure (aHR, 1.50; 95% CI, 1.30 to 1.75, P < 0.001) through the 5-year follow-up. Conclusions This pretransplant AI-ECG parameter identified patients at increased risk of new-onset AF post-KTx and provided prognostic utility. Overall, this easy to obtain tool allows for risk stratification of patients who may benefit from closer monitoring, targeted risk factor modification, and early intervention.

Coronary artery disease (CAD) remains the leading cause of cardiovascular morbidity and mortality worldwide, with plaque composition and morphology being as key determinants of disease progression and clinical outcomes. Accurate plaque characterization is essential for risk stratification and therapeutic decision-making, yet conventional image interpretation is limited by inter-observer variability and time-intensive workflows. Artificial intelligence (AI) models have emerged as a transformative tool for automated coronary plaque analysis across multiple imaging modalities. AI-driven models demonstrate high diagnostic accuracy for plaque detection, segmentation, quantification, and vulnerability assessment. Integration of AI-derived imaging biomarkers with clinical risk scores can further enhance prediction of major adverse cardiovascular events and supports personalized management. These advances position AI-enhanced imaging as a powerful adjunct for both invasive and non-invasive evaluation of CAD. Despite its promise, important barriers to widespread clinical adoption remain, including data heterogeneity, algorithmic bias, limited model transparency, insufficient prospective validation, regulatory challenges, and incomplete integration into clinical workflows. Addressing these challenges will be essential to ensure safe, generalizable, and cost-effective implementation of AI in routine cardiovascular care.

Despite advances in lipid-lowering and antithrombotic therapy, patients with acute coronary syndromes remain at elevated risk for recurrent events due to persistent atherosclerotic inflammation. This review evaluates inflammation as a therapeutic target in secondary prevention and discusses established, investigational, and emerging strategies. Colchicine, now FDA-approved for cardiovascular risk reduction, lowered major adverse cardiovascular events in COLCOT and LoDoCo2. Canakinumab (IL-1β inhibition) reduced recurrent events in proportion to IL-6 and hsCRP suppression, while ziltivekimab (IL-6 inhibition) achieved profound biomarker reductions but remains investigational. Early-phase studies of anakinra (IL-1 receptor antagonist) and dapansutrile (oral NLRP3 inhibitor) showed anti-inflammatory effects in early trials, whereas varespladib and darapladib illustrated the challenges of targeting lipid-associated pathways. Beyond direct immunomodulators, GLP-1 receptor agonists and SGLT2 inhibitors provide both cardioprotective and anti-inflammatory benefits, reinforcing their expanding role post-ACS. Additional emerging avenues include triptolidiol, dasatinib, and BTK or JAK/STAT inhibitors, while novel approaches, such as nanozyme delivery systems and CRISPR-based editing, extend the therapeutic horizon. This review highlights the potential of inflammation-targeted therapies to advance secondary prevention in ACS by integrating current evidence and perspectives on future therapeutic developments.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, contributing to significant morbidity and mortality worldwide. The relationship between physical exercise and AF is complex, with studies showing both beneficial and potentially adverse effects. Moreover, evidence suggests a U-shaped association between exercise intensity and AF risk. Moderate exercise has been shown to reduce AF burden by improving cardiovascular risk factors, enhancing autonomic regulation, and mitigating atrial fibrosis. In contrast, excessively high-intensity endurance exercise may increase AF risk, particularly in young athletes, due to atrial stretching, dilation, fibrosis, autonomic imbalances, and heightened inflammation. The current guidelines emphasize exercise as a core lifestyle intervention for AF management, recommending moderate-intensity aerobic activity for optimal outcomes. This review examines the current evidence on the effects of exercise on AF, identifies knowledge gaps, and proposes potential future research directions.

Abstract Background Inadvertent temporary transvenous pacing (TTVP) of left ventricle (LV) is rare and likely underreported, posing significant embolic risk. We present a case of TTVP with atypical trajectory identified on computed tomography (CT) imaging. Summary A 62-year-old male with metastatic renal cell carcinoma on chemotherapy and bifascicular block presented with symptomatic bradycardia and non–ST-elevation myocardial infarction (NSTEMI), raising concerns for complete heart block on ECG. Intermittent asystole occurred during TTVP placement with appropriate capture. Post-procedure, ECG showed ventricular-paced rhythm with pseudo-right bundle branch block, and chest X-ray suggested lead placement in right ventricle; however, suboptimal echocardiography limited lead visualization. Coronary angiography revealed non-obstructive coronary artery disease. Positron emission tomography–computed tomography (PET-CT), performed to evaluate immune checkpoint inhibitor myocarditis, incidentally noted TTVP wire entering right subclavian artery and traversing to LV. Patient underwent TTVP removal, endovascular repair, and pacemaker implantation; however, course was unfortunately complicated by embolic stroke and haemorrhagic conversion. Discussion Early detection and management of lead malposition remain critical to minimizing complications. Management strategies for inadvertent lead malposition (ILM) depend on duration of implantation, clinical presentation, and associated risks. This case highlights importance of recognizing this high-risk complication, preventive strategies, and evidence-based management. While existing data primarily focus on ILM in permanent devices, further research is needed to elucidate incidence, predictors, and outcomes of ILM in TTVP, particularly in resource-limited settings.

Myocardial deformation imaging has emerged as a valuable clinical tool for assessing right ventricular (RV) systolic function, providing additional diagnostic and prognostic insights compared to traditional indices of RV function. Two-dimensional speckle-tracking echocardiography is currently the standardized method of choice for measuring RV longitudinal strain (RVLS) in clinical practice. RVLS provides a more sensitive indicator of subtle myocardial dysfunction than conventional parameters for RV function assessment (i.e., tricuspid annular plane systolic excursion, tissue Doppler systolic velocity, fractional area change, or RV ejection fraction), with utility for the risk stratification and surveillance of conditions affecting the right heart. However, accurate interpretation of RVLS requires a comprehensive understanding of RV mechanics, pathology, and loading conditions across various cardiovascular conditions, as well as the effects of image quality and technical aspects of image acquisition and tracking in RV strain measurements. This review provides an updated overview of current practical guidelines for RV strain analysis, current clinical applications, and future directions for its potential use in clinical practice.