Nhat, Hoang

Background: Disparities exist in the representation of genders in cardiovascular clinical trials. Atrial fibrillation (AF) is associated with significant morbidity and mortality; however, understanding regarding the representation of women in AF-related clinical trials remains limited. Therefore, this systematic review sought to evaluate the representation of women in AF-related clinical trials. Methods: We conducted a systematic review of clinical trials using the PubMed, Scopus, and EMBASE databases from 1996 to January 1st, 2024, focusing on AF-related lifestyle interventions, pharmacological treatments, catheter ablation, and device therapies for AF. Data extraction and analysis encompassed trial characteristics, participant demographics, and funding sources. The primary outcome was the prevalence of female enrollees, quantified through participation-to-prevalence ratios (PPRs). This was estimated overall and stratified by funding source, intervention type, and enrollment region. Results: Of the 103 clinical trials involving 218,322 participants (39.5% female), the PPR ranged from 0.00 to 1.73, with an average PPR of 1.03. Meanwhile, 43% of the trials exhibited female under-representation (PPR, <0.8). University-funded trials showed higher female enrollment (mean PPR, 0.951) compared to industry/government-funded trials (mean PPR, 0.800). No differences were observed in the representation of women when comparing enrollment regions or intervention types. Conclusions: Despite advancements in AF management, gender disparities persist in AF-related clinical trial representation, particularly in industry/government-funded studies compared to university-funded trials. Thus, addressing implicit biases and enforcing sex equality guidelines are critical steps toward more inclusive cardiovascular research.

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.

Heart failure (HF) remains a major cause of morbidity and mortality worldwide, with its prevalence continuing to rise due to an aging population and the increasing burden of cardiometabolic diseases. Advances in understanding HF pathophysiology—neurohormonal, inflammatory, and metabolic mechanisms—have led to significant improvements in diagnosis and management, emphasizing earlier detection and patient-centered approaches. Novel biomarkers have the potential to enhance risk assessment beyond traditional natriuretic peptides. Imaging advances can enhance structural and functional assessment, enabling more accurate phenotyping, disease characterization, and risk stratification. Recent advances and real-world data have been used to implement and optimize guideline-directed medical therapy (GDMT) for HF to reduce HF hospitalizations and cardiovascular mortality across the spectrum of HF etiologies. Adjunctive therapies are reserved for select patients with persistent symptoms or high-risk features despite optimal GDMT. Device- and transcatheter-based interventions include established and emerging technologies that address persistent symptoms, structural abnormalities, and hemodynamic abnormalities despite optimal GDMT, thereby expanding treatment options for high-risk patients. Collectively, these advancements highlight a paradigm shift toward precise, personalized approaches to HF management, thereby improving long-term outcomes across the spectrum of HF etiologies.

Background To compare the effectiveness of glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) versus bariatric surgery on cardiovascular outcomes in patients with heart failure (HF) with preserved ejection fraction and obesity. Methods Using the TriNetX research network, we conducted a retrospective cohort study of adults (aged ≥18 years) with HF with preserved ejection fraction and obesity (body mass index >30 kg/m 2 ) from 2017 to 2022. Patients were categorized into 2 cohorts: those receiving GLP‐1 RAs (semaglutide or tirzepatide) and those who underwent bariatric surgery. Propensity score matching (1:1) was used to balance baseline characteristics. Primary outcomes included acute HF events and all‐cause hospitalizations. Secondary outcomes included all‐cause death, myocardial infarction, stroke, and follow‐up body mass index. Cox proportional hazard models were used to estimate hazard ratios (HRs). Results A total of 2747 patients were included per cohort (mean age, 68 years). GLP‐1 RA therapy was associated with lower incidence of acute HF events (38.9% versus 44.6%; HR, 0.78 [95% CI, 0.72–0.85]), all‐cause death (11.1% versus 14.8%; HR, 0.71 [95% CI, 0.61–0.82]), and all‐cause hospitalizations (66.4% versus 77.3%; HR, 0.62 [95% CI, 0.58–0.66]). Rates of myocardial infarction (13.8% versus 13.4%; HR 0.99 [0.86–1.14]) and stroke (9.7% versus 10.7%; HR, 0.87 [0.74–1.02]) were similar between groups. Mean body mass index at follow‐up was 38.0 in the GLP‐1 RA cohort versus 37.7 after bariatric surgery ( P =0.34). Hemoglobin A 1c at follow‐up was higher in the GLP‐1 RA group (7.4 versus 6.8; P <0.001). Conclusions In patients with HF with preserved ejection fraction and obesity, GLP‐1 RA therapy was associated with improved outcomes compared with bariatric surgery, supporting the need for prospective trials to evaluate GLP‐1 RAs as a therapeutic alternative.

Abstract Aims We evaluated clinical outcomes with GLP-1 RA use post-TAVI in patients with T2D. GLP-1 receptor agonists (GLP1-RAs) lower cardiovascular risk in type 2 diabetes (T2D), but their impact in patients with valvular heart disease, including those undergoing transcatheter aortic-valve implantation (TAVI), remained unexplored. Methods and results We conducted a retrospective cohort study using the TriNetX network, including 25 184 adults (≥18 years) with T2D who underwent TAVI (2015–2023). Patients were stratified based on GLP1-RA initiation within 14 days post-TAVI. Baseline characteristics, comorbidities, medications, and laboratory data were balanced using 1:1 propensity score matching (PSM). Cox models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for events from one-month post-TAVI until the most recent follow-up. PSM yielded 1101 patients per group, with a mean age of 73 years and 39% female. Mean follow-up duration was 2.2 ± 1.1 and 2.6 ± 1.8 years for GLP1-RA users and non-users, respectively. GLP1-RA use was also associated higher survival probability (HR: 0.708 [95% CI: 0.583–0.859]), and lower rates of all-cause hospitalization (HR: 0.790 [95% CI, 0.706–0.885]), major cardiovascular events (HR: 0.849 [95% CI: 0.749–0.963]), and acute heart failure exacerbation (HR: 0.785 [95% CI: 0.677–0.909]), acute kidney injury (HR: 0.843 [95% CI: 0.719–0.988]), and major kidney events (HR: 0.665 [95% CI: 0.510–0.866]). No differences were observed in acute myocardial infarction, cerebral infarction, or cardiac arrest. Conclusion In patients with T2D undergoing TAVI, GLP1-RA use is associated with significant survival benefits and improved cardiorenal outcomes. However, these findings are limited by the observational design, high comorbidity burden, lack of data on medication compliance, and specific cause of death. Prospective trials are warranted to confirm these benefits.

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.

Arrhythmogenic cardiomyopathies (ACMs) are a phenotypically and etiologically heterogeneous group of myocardial disorders characterized by fibrotic or fibro-fatty replacement of ventricular myocardium, electrical instability, and an elevated risk of sudden cardiac death. Initially identified as a right ventricular disease, ACMs are now recognized to include biventricular and left-dominant forms. Genetic causes account for a substantial proportion of cases and include desmosomal variants, non-desmosomal variants, and familial gene-elusive forms with no identifiable pathogenic mutation. Nongenetic etiologies, including post-inflammatory, autoimmune, and infiltrative mechanisms, may mimic the phenotype. In many patients, the disease remains idiopathic despite comprehensive evaluation. Cardiac magnetic resonance imaging has emerged as a key tool for identifying non-ischemic scar patterns and for distinguishing arrhythmogenic phenotypes from other cardiomyopathies. Emerging classifications propose the unifying concept of scarring cardiomyopathies based on shared structural substrates, although global consensus is evolving. Risk stratification remains challenging, particularly in patients without overt systolic dysfunction or identifiable genetic markers. Advances in tissue phenotyping, multi-omics, and artificial intelligence hold promise for improved prognostic assessment and individualized therapy.

Advances in plaque imaging have transformed cardiovascular diagnostics through detailed characterization of atherosclerotic plaques beyond traditional stenosis assessment. This review outlines the clinical applications of varying modalities, including dual-layer spectral CT, photon-counting CT, dual-energy CT, and CT-derived fractional flow reserve (CT-FFR). These technologies offer improved spatial resolution, tissue differentiation, and functional assessment of coronary lesions. Additionally, artificial intelligence has emerged as a powerful tool to automate plaque detection, quantify burden, and refine risk prediction. Collectively, these innovations provide a more comprehensive approach to coronary artery disease evaluation and support personalized management strategies.