Ibrahim, Ramzi

Abstract Background Loeys-Dietz Syndrome (LDS) is a rare connective tissue disorder characterized by mutations indifferent genes including TGFRB2, TGFBR1, TGFB2, TGFB3, and SMAD3, which significantly increase the risk of vascular abnormalities, including aneurysms and dissections. These vascular events can involve various arterial territories, although the thoracic aorta is of most concern. The current literature is limited on characterizing the aortic and extra-aortic vascular manifestation on larger cohorts of patients. Purpose This study aims at analyzing the rates of aneurysms and dissections across different vascular territories inpatients with LDS. Methods A retrospective analysis was conducted on a cohort of individuals diagnosed with LDS at our institution. Medical records were reviewed for imaging findings, including CT scans, MRIs, and ultrasounds, to identify the presence of aneurysms and dissections. Vascular territories involved included the aortic arch (ascending, and descending aorta), coronary, cerebral, carotid, vertebral, renal, splanchnic, and peripheral arteries. Results A total of 94 patients with LDS were included. 76 patients (81%) had an ascending aortic aneurysm, and 21 patients (22.5%) had an abdominal aortic aneurysm. 49 patients (52%) had aneurysms in other vascular territories, with some patients having multiple aneurysms in different regions. These included 9 patients (9.5%) with carotid, 3 patients (3.2%) with vertebral, 5 patients (5.3%) with splenic, 11 patients (11.7%) with mesenteric, 2 patients (2.1%) with renal, 15 patients (15.9%) with iliac/femoral, 6 patients (6.4%) with subclavian, 23 patients (24.5%) with cerebral, and 10 patients (10.6%) with coronary aneurysms. For aortic dissections, 13 patients (14%) had type A and 9 patients (9.5%) had type B dissections. Additionally, 20 patients had dissections in other vascular territories, with some patients experiencing dissections in multiple regions. These included 8 patients (8.5%) with carotid, 8 patients (8.5%) with vertebral, 1 patient (1.1%) with renal, 3 patients (3.2%) with iliac, 2 patients (2.1%) with coronary, and 3 patients (3.2%) with innominate artery dissections. Conclusion Aortic involvement is the most common in patients with LDS; however, these patients are also at an increased risk of developing aneurysms and dissections in various vascular territories. This highlights the importance of screening and close follow-up in these patients, potentially through whole-body imaging to identify such abnormalities. Further research is needed to identify patients at higher risk for aneurysms and dissections compared to others.

Abstract Background/Introduction Acute coronary syndrome (ACS) is common among elderly patients and is associated with a high risk of complications. Managing ACS, particularly dual antiplatelet therapy (DAPT), poses challenges due to the increased risk of recurrent hemorrhagic and ischemic events in this population. Purpose This study evaluated cardiovascular outcomes in patients ≥75 years that were initiated on DAPT with aspirin (ASA) plus either ticagrelor or clopidogrel following an acute myocardial infarction (AMI). Methods We used the TriNetX repository to identify adult patients (≥75 years) diagnosed with AMI between January 1, 2011, and December 31, 2021, who subsequently initiated DAPT and were not on anticoagulation. Patients were stratified into two cohorts: ASA + ticagrelor and ASA + clopidogrel. Outcomes assessed included major bleeding, repeat coronary intervention, all-cause mortality, all-cause hospitalizations, stroke, new-onset atrial fibrillation, and pacemaker implantation. Follow-up time was restricted to one year. A 1:1 propensity score matching algorithm was applied using the greedy nearest-neighbor method with a caliper of 0.1 pooled standard deviations to ensure balance (i.e., comorbidities, medications, laboratory values) between the two cohorts. Logistic regression models were used to calculate adjusted odds ratios (aOR), and Cox proportional hazards models estimated hazard ratios (HR). Results Before propensity score matching (PSM), 19,859 patients were in the ASA + ticagrelor cohort, and 47,032 were in the ASA + clopidogrel cohort. Post-PSM, 19,746 patients remained in each cohort, with a mean age of 82.2 years and a mean follow-up duration of 298.77 days for the ASA + ticagrelor cohort and 297.59 days for the ASA + clopidogrel cohort. The ASA + ticagrelor cohort had a higher incidence of major bleeding (aOR 1.19 [95% CI, 1.08–1.31]) and pacemaker implantation (aOR 1.14 [95% CI, 1.02–1.29]) compared to the ASA + clopidogrel cohort. Event-free survival analysis showed lower survival rates for major bleeding (HR 1.18 [95% CI, 1.07–1.30]) and pacemaker implantation (HR 1.14 [95% CI, 1.01–1.28]). No significant differences were observed between cohorts in repeat coronary interventions (aOR 0.95 [95% CI, 0.88–1.03]), atrial fibrillation (aOR 1.03 [95% CI, 0.97–1.08]), all-cause mortality (aOR 1.03 [95% CI, 0.96–1.12]), all-cause hospitalization (aOR 1.01 [95% CI, 0.97–1.05]), or stroke (aOR 0.95 [95% CI, 0.86–1.04]). Conclusions In elderly patients, DAPT with ASA + ticagrelor was associated with higher rates of major bleeding and need for pacemaker compared to ASA + clopidogrel. Given the similar risks of recurrent coronary intervention and mortality between the two regimens, these findings highlight the need for careful consideration when selecting ticagrelor over clopidogrel in this population.

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.

ABSTRACT Background Cardiac amyloidosis (CA) is frequently complicated by atrial fibrillation (AF), yet outcomes after left atrial appendage occlusion (LAAO) in this population remain poorly defined. Methods We conducted a retrospective TriNetX study of adults with AF undergoing LAAO, comparing patients with and without CA after 1:1 propensity matching. Outcomes were assessed using Kaplan–Meier analyses and Cox regression. Results Among 532 matched pairs, mortality and major adverse cardiovascular events were similar between groups, whereas major bleeding was higher in CA (HR 1.90). Conclusions LAAO yields comparable ischemic outcomes in CA, though bleeding risk is increased.

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.

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.

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.