Citations

Abstract Background Vascular Ehlers-Danlos syndrome (VEDS) and Marfan’s syndrome are associated with cardiovascular complications, including arrhythmias. However, ventricular tachycardia (VT) risk in these populations has not been frequently reported. Purpose This study aims to assess the VT risk in VEDS and Marfan's syndrome patients through an international database. Methods The TriNetX database was used to pull patients with a diagnosis of VEDS and Marfan's Syndrome. Baseline characteristics (e.g., demographics, cardiovascular comorbidities, etc.) were collected, and propensity score matching was performed to balance the cohorts. Risk analysis and Kaplan-Meier survival were used to assess outcomes. Results A total of 1,114 and 23,172 patients had VEDS and Marfan’s syndrome, respectively. After propensity score matching, each cohort included 1,091 balanced patients regarding demographics and clinical characteristics. The cohorts were balanced with a mean age of 37.7 ± 16.0 years in both groups. 68.7% and 68.8% were females in the VEDS and Marfan cohorts, the majority being White (82.2% in VEDS, 82.9% in Marfan’s). VT Incidence was lower in VEDS (0.9%) compared to Marfan’s syndrome (2.6%), with a risk difference of -0.016 (p = 0.003). Kaplan-Meier survival showed higher survival in VEDS (99.44%) vs. Marfan’s (94.04%, log-rank p = 0.002). The risk ratio for VT in VEDS was 0.357 (95% CI: 0.174, 0.732). Conclusion VEDS patients have a significantly lower VT risk compared to those with Marfan’s syndrome. These findings suggest significant differences in the arrhythmic burden between these connective tissue disorders, which can direct future risk stratification and management strategies.

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.

Abstract Background/Introduction Patients with transthyretin cardiac amyloidosis (ATTR-CA) and atrial fibrillation (AF) have increased risk for left atrial thrombi, necessitating anticoagulation therapy if bleeding risk is not prohibitive. Limited data is available comparing the use of direct oral anticoagulants (DOACs) to warfarin in this population. Purpose To evaluate and compare clinical efficacy and safety outcomes of DOACs versus warfarin in patients with ATTR-CA and AF. Methods We conducted a retrospective cohort study using the TriNetX Network, which includes data from over 140 million patients, between 2014 and 2022. Adults (aged ≥18 years) with ATTR-CA and AF were identified. These patients were further categorized into two groups: one cohort which utilized DOACs for oral anticoagulation and the other cohort on warfarin. 1:1 propensity score matching (PSM) was utilized to balance baseline characteristics between the two cohorts. The primary outcome was rate of stroke, with secondary outcomes including all-cause death, all-cause hospitalizations, and acute heart failure exacerbations. Safety outcomes included intracranial hemorrhage, gastrointestinal hemorrhage, and hematuria. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were calculated. Results Among 8,214 adults with ATTR-CA and AF, 5,774 patients were on a DOAC while 2,440 patients were on warfarin. After PSM, 2,425 patients were included in each group. The use of DOACs for AF in patients with ATTR-CA was associated with a significantly lower risk of ischemic stroke compared to warfarin (5.7% versus 7.3%, aOR 0.771 [95% CI, 0.612-0.971]) by the end of the one year follow up. There were no differences in all-cause mortality (19.8% versus 21%, aOR 0.927 [95% CI, 0.806-1.066]), all-cause hospitalizations (19.2% versus 21.6%, aOR 0.863 [95% CI, 0.624-1.195]) or heart failure exacerbations (43.6% versus 46%, aOR 0.906 [95% CI, 0.809-1.015]). Safety outcomes favored DOACs over warfarin, with a lower risk of intracranial hemorrhage (4.5% versus 7.8%, aOR 0.565 [95% CI, 0.444-0.720]), and comparable rates of GI hemorrhage and hematuria. Conclusions DOACs may be safely used in ATTR-CA patients with AF, offering a lower risk of stroke compared to warfarin and a more favorable safety profile. These findings emphasize the potential advantages of DOACs in this population and underline the need for prospective studies to validate these results.

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.

Abstract Introduction Cardiovascular disease (CVD) is the leading cause of death among patients with kidney failure on dialysis. Social determinants of health may worsen this risk but are seldom incorporated into prognostic models. ICD-10 Z-codes provide standardized documentation of social determinants of health, yet their prognostic value in dialysis populations remains uncertain. This study examined whether Z-coded social determinants of health are associated with adverse cardiovascular outcomes and mortality among patients receiving dialysis for kidney failure. Methods A retrospective cohort study was conducted using the TriNetX Research Network (2010–2024), encompassing de-identified data from 103 institutions. Adults with kidney failure on chronic dialysis were stratified by the presence of ICD-10 Z-codes (Z55–Z65). Propensity score matching (1:1) balanced demographics, comorbidities, medications, and laboratory values. Primary outcomes were all-cause mortality and hospitalization; secondary outcomes included acute heart failure, myocardial infarction, stroke, cardiac arrest, bradyarrhythmias, and ventricular tachycardia. Results After matching, mean age was 62 years, and 42.4% were female in the Z-code cohort versus 41.2% in controls. Over one year, mortality occurred in 12.5% versus 10.9% (hazard ratio [HR], 1.22; 95% confidence interval [CI], 1.15–1.29) and all-cause hospitalizations in 57.3% versus 53.1% (HR, 1.22; 95% CI, 1.19–1.26). Cardiovascular complications were consistently higher in Z-coded patients, including heart failure (24.3% vs 20.5%; HR, 1.29), myocardial infarction (8.0% vs 7.1%; HR, 1.19), stroke (6.6% vs 6.2%; HR, 1.13), cardiac arrest (3.8% vs 3.1%; HR, 1.29), and bradyarrhythmias (6.9% vs 5.5%; HR, 1.33). Discussion Among patients with kidney failure, documented Z-coded social risk factors were associated with greater mortality and cardiovascular morbidity. Incorporating social determinants of health documentation into nephrology care may improve risk stratification and inform targeted interventions.

Coronary artery bypass grafting (CABG) remains a cornerstone of treatment for patients with advanced or complex coronary artery disease, yet long-term success is influenced by graft patency, progression of native disease, and ventricular remodeling. Optimizing the follow-up of these patients requires a structured approach in which multimodality cardiovascular imaging plays a central role. Echocardiography remains the first-line modality, providing readily available assessment of ventricular function, valvular competence, and wall motion, while advanced techniques, such as strain imaging and myocardial work, enhance sensitivity for subclinical dysfunction. Coronary computed tomography angiography (CCTA) offers excellent diagnostic accuracy for graft patency and native coronary anatomy, with emerging applications of CT perfusion and fractional flow reserve derived from CT (FFR-CT) expanding its ability to assess lesion-specific ischemia. Cardiovascular magnetic resonance (CMR) provides comprehensive tissue characterization, quantifying scar burden, viability, and inducible ischemia, and stress CMR protocols have demonstrated both safety and independent prognostic value in post-CABG cohorts. Nuclear imaging with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) remains essential for quantifying perfusion, viability, and absolute myocardial blood flow, with hybrid PET/CT approaches offering further refinement in patients with recurrent symptoms. In patients after CABG, multimodality imaging is tailored to the patient’s characteristics, symptoms, and pre-test probability of disease progression. In asymptomatic patients, imaging focuses on surveillance, risk stratification, and the early detection of subclinical abnormalities, whereas in symptomatic individuals, it focuses on establishing the diagnosis, defining prognosis, and guiding therapeutic interventions. Therefore, the aim of our review is to propose updated and comprehensive guidance on the crucial role of multimodality cardiovascular imaging in the evaluation and management of post-CABG patients and to provide a practical, evidence-based framework for optimizing outcomes.

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.

Positive inotropic agents have an important role in the management of acute decompensated heart failure patients with reduced cardiac output and poor end-organ perfusion. However, despite their acute hemodynamic benefits, the role of inotropes in the management of chronic advanced heart failure remains limited to palliative therapy or as a bridging strategy to mechanical support or heart transplantation. Milrinone is one of the most common inotropic agents used in advanced heart failure to provide symptomatic relief and improved hemodynamics. This review discusses the current evidence of milrinone’s efficacy, indications, outcomes in advanced heart failure, evidence gap, and future directions.

Ventricular arrhythmias after electrical cardioversion for AF are rare. Most of these arrhythmias are related to QT prolongation, resulting from marked and sudden slowing of heart rates, treatment with Class III antiarrhythmic drugs or other QT-prolonging medications, and the ventricular repolarisation remodelling effect of electrical cardioversion. A case of polymorphic ventricular tachycardia post-cardioversion of rapid AF in a patient with tachycardia-induced cardiomyopathy and the use of amiodarone is reported.