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Background: Spontaneous Coronary Artery Dissection (SCAD) is a cause of acute coronary syndrome, particularly among women, and is associated with psychological distress, including depression, anxiety, and post-traumatic stress (PTSD) symptoms. Fibromuscular dysplasia (FMD), a vascular condition that alters the arteries, is often found in patients with SCAD, adding complexity and uncertainty with a second serious diagnosis. This study examined the differences in mental health symptoms between SCAD survivors with and without FMD to better understand their unique psychosocial needs and inform interventions to enhance patient outcomes. Methods: Patients diagnosed with SCAD within the past 3 years were recruited from 6 Canadian cardiac hospitals. Participants completed questionnaires assessing socio-demographics, comorbidities, and validated psychological measures, including Patient Health Questionnaire-9 (PHQ-9) for depression, Generalized Anxiety Disorder-7 (GAD-7) for generalized anxiety, Cardiac Anxiety Questionnaire (CAQ) for cardiac-related anxiety, and PTSD Checklist (PCL-5) for PTSD symptoms. Differences in mental health outcomes between SCAD survivors with and without FMD were analyzed using t-tests for continuous variables and chi-square tests for categorical variables. Results: The study included 326 participants (92.9% female; mean age 53.3 years), with 67 participants (20.6%) having a confirmed diagnosis of FMD at the time of questionnaire completion (39.3% FMD at study completion). Post-SCAD, patients with FMD reported significantly higher scores than patients without FMD on the GAD-7 (6.4±5.9 vs. 4.7±4.9, p = .028), CAQ (29.9±13.1 vs. 26.0±12.3, p = .023), and PCL-5 (17.2±15.4 vs. 13.3± 14.0, p = .048). The proportion of SCAD survivors with FMD scoring in the clinically diagnostic range was significantly higher than those in patients without FMD: 32.8% vs. 20.8% for depression, 31.3% vs. 17.4% for anxiety, 64.2% vs. 49.2% for cardiac anxiety, and 25.4% vs. 11.6% for PTSD (all p < .05). Conclusions: Our findings suggest that SCAD survivors with comorbid FMD experience significantly higher distress —depression, generalized anxiety, cardiac-related anxiety, and PTSD symptoms—compared to those without FMD. Longitudinal research is needed to explore the role of these mental health concerns in long-term mental health and cardiac outcomes. Enhanced psychological interventions for those with FMD may be required.

Background: Whether oral anticoagulation (OAC) can be discontinued after the resolution of left ventricular thrombus (LVT) remains controversial, particularly in patients without risk factors such as left ventricular aneurysms. This study aimed to identify patients who may safely discontinue OAC. Methods: We conducted a retrospective cohort study of patients with LVT resolution who completed their anticoagulation course and excluded patients with left ventricular (LV) aneurysm. Clinical and echocardiographic factors were compared between patients who experienced LVT recurrence (n = 22) and those without recurrence during follow-up (n = 94). Results: The cohort had a mean age of 64.5 ± 15.0 years, and half (50%) were male. Most had an ischemic cardiomyopathy (64.6%). LVT recurred in 19% (22/116) of patients following initial resolution. Patients with recurrence were older (mean age 71.3 ± 11.9 vs. 63.4 ± 15.7 years, p = 0.03) and were more likely to have prior ischemic stroke and arterial thromboembolism (18.2% vs. 4.3%, p = 0.02 for both). At the time of thrombus resolution, LVEF was significantly lower among patients who had recurrence (33.4 ± 13.6% vs. 42.5 ± 15.5%, p = 0.012). Stroke, systemic embolism, and mortality rates were similar regardless of recurrence status. Recurrence risk by presence or absence of stroke and LEVF >50% on the LVT resolution echocardiogram is shown in Figure 1. Notably, no recurrences were observed among patients with both LVEF > 50% and no history of stroke (0/32), which was statistically significant compared to each other category. Conclusion: Among patients without left ventricular aneurysm who discontinued oral anticoagulation after LVT resolution, those with preserved LVEF (>50%) and no prior history of stroke had a very low risk of recurrence, with no events observed in this subgroup. These findings suggest that some patients may safely discontinue anticoagulation after LVT resolution.

Introduction/Background: Peripheral arterial disease (PAD) exhibits reduced hyperemic response in the affected legs following stimuli such as pressure-cuff-induced occlusion or exercise. Therefore, an analysis of the perfusion changes in the calf muscle using a widely available imaging modality such as ultrasound could serve as a complementary tool to existing methods such as ankle-brachial index (ABI) for PAD detection. Research Questions/Hypothesis: This study evaluates the utility of ultrasound perfusion imaging and estimation technique in the calf muscle to differentiate PAD affected legs based on their flow response to external pressure and exercise. Methods/Approach: Data acquisition was performed using a research ultrasound system (Vantage NXT, Verasonics) with an ultrasound probe secured inside a probe fixation device and positioned to the calf muscle of the subject. Two separate studies were performed on each subject: 1) A flow variations response to external pressure study, 2) a flow variation response to exercise. For the pressure study, a pressure cuff was wrapped around the subject’s thigh and inflated during the study using an automatic rapid cuff inflation device. Data was continuously acquired for 6 minutes including 1 minute of baseline, 3 minutes of pressure cuff occlusion, 2 minutes of post-occlusion acquisition. The exercise study consisted of data acquisition in the seated position with 1 minute of baseline, 30 repetitions of plantar flexion using a calf training device, and 2 minutes of post-exercise acquisition. The acquired data were then clutter-filtered and denoised for perfusion visualization. Four metrics including post-occlusion/post-exercise to baseline flow intensity/density variation (POBFIV, PEBFIV, POBFDV, PEBFDV) were obtained for analysis. Results/Data: Figure 1 shows perfusion imaging results during the pressure and the exercise studies for two example legs, one healthy and one of a clinically diagnosed PAD patient (mild disease), respectively. Percentage-wise POBFIV, PEBFIV, POBFDV, and PEBFDV values were 44%, 57%, 197%, and 2231% for the healthy leg and 12%, 27%, 63%, and 181% for the PAD leg, respectively, shown in Table 1. Conclusion: The proposed method shows promise in differentiating PAD-affected legs from healthy individual’s through evaluating the hyperemic response to external pressure and exercise. Statistical analysis of the results for a cohort of healthy and PAD-affected legs will constitute future work.

Introduction: Dyslipidemia remains a major driver of cardiovascular disease. Monoclonal antibodies (mAb) that block angiopoietin-like protein 3 (ANGPTL3) lower atherogenic lipids by a mechanism distinct from statins. Earlier evidence centred on the Evinacumab. A new trial now evaluate the investigational antibody SHR-1918. Hypothesis: We hypothesized that treatment with ANGPTL3 mAbs whether evinacumab or SHR-1918 would significantly improve lipid parameters compared to placebo without increasing adverse events. Aims: To Quantify the pooled effect of ANGPTL3 mAbs on low-density lipoprotein cholesterol (LDL-C), Triglycerides, apolipoprotein B (ApoB) and non-high-density lipoprotein cholesterol (non-HDL-C) and Compare efficacy and safety between Evinacumab and SHR-1918 subgroups. Methods: A systematic search of Pubmed, Google Scholar MEDLINE, Embase, and ClinicalTrials.gov untill 1 April 2025 was done and relevant randomised controlled trials (RCT's) comparing ANGPTL3 mAbs with placebo in dyslipidaemic patients were included. Data was extracted on spreadsheet and Data analysis was done in RevMan 5.4. Results: 5 RCT's comprising of 603 patients met inclusion criteria. The pooled analysis showed marked reductions in atherogenic lipids with ANGPTL3 monoclonal antibodies versus placebo, including low-density lipoprotein cholesterol (SMD = –2.73, 95 % CI –4.16 to –1.31, P < 0.001), triglycerides (SMD = –3.54, 95 % CI –4.71 to –2.37, P < 0.001), apolipoprotein B (SMD = –1.98, 95 % CI –2.97 to –1.00, P < 0.001) and non-HDL-C (SMD = –2.89, 95 % CI –4.00 to –1.78, P < 0.001). Sub-group analyses demonstrated directionally consistent lipid lowering for both evinacumab and the newer agent SHR-1918. Adverse-event due to treatment evaluation revealed no significant increase in Adverse events due to treatment (RR = 1.05, 95 % CI 0.87 to 1.27, P = 0.63) or serious events (RR = 1.37, 95 % CI 0.54 to 3.44, P = 0.49), indicating good overall tolerability. Conclusion: monoclonal antibodies targeting ANGPTL3 encompassing both evinacumab and the newer agent SHR-1918 consistently reduced LDL-C, triglycerides, and related lipid markers with a favourable tolerability profile. Further large, long-term studies are needed to fully establish their safety, clinical effectiveness, and potential to improve cardiovascular outcomes.

Background: Pulmonary hypertension (PH) is a life-threatening disease affecting up to 1% of the global population. Diagnosis can be challenging and is often delayed due to the need for advanced imaging and invasive procedures. The use of artificial intelligence applied to ECGs (ECG-AI) has been shown to detect subtle patterns in voltage-time data and may be a valuable tool for the early detection of PH. Hypothesis and Purpose: To evaluate the performance of a previously trained, ECG-AI algorithm to detect PH (ECG-AI PH) using real-world data (RWD) collected in a multicenter, validation study. A joint primary hypothesis required sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) to exceed the null values of 76%, 70%, 10% and 90%. Study Design and Methods: This retrospective validation study was conducted at 5 geographically diverse U.S. health systems. Adult subjects were eligible for inclusion if they had a 12-lead ECG paired with an echocardiogram (Echo) in which tricuspid regurgitation velocity (TRV) was recorded, following presentation with dyspnea. Patients were classified according to echocardiographic criteria as either PH (PH+, TRV >3.4 m/s) or controls (PH-, TRV ≤2.8 m/s) to simulate the real-world use of ECG-AI, where a positive result could lead to a follow-up Echo. The study database was locked before processing the digital ECGs with ECG-AI PH. Performance was also estimated in a subset of subjects that later had a right heart catheterization using mPAP ≥ 20mmHg as the definition of PH. Results: A total of 14281 subjects (53% female, 63% aged 50+ years) met the inclusion criteria, including 3019 PH+ cases and 11262 PH- controls (Figure). Sn and Sp were 84.0% (95% CI: 82.6%, 85.3%) and 71.7% (95% CI: 70.9%, 72.6%), respectively. The positive and negative predictive values were 18.9% (95% CI: 18.4%, 19.4%) and 98.3% (95% CI: 98.1%, 98.4%), respectively, at 7.3% prevalence. Each endpoint met pre-defined performance criteria. In the subset of 1683 subjects with a follow up RHC, performance remained robust (Sn 85% (1155/1358); Sp 46% (151/325)). Conclusion: While ECG-AI PH was first developed as an investigational tool to detect PH, continued development as software as a medical device for clinical use demonstrated that the algorithm retained strong performance to detect PH in diverse, non-overlapping clinical settings and patient populations.

Introduction: Pulmonary hypertension (PH) is a life-threatening, progressive disease with non-specific symptoms, often leading to delayed diagnosis. Early identification of World Health Organization Group 1 (Pulmonary Arterial Hypertension, PAH) and Group 4 (Chronic Thromboembolic Pulmonary Hypertension, CTEPH) is essential, as effective therapies can improve outcomes. Hypothesis: An electrocardiogram-based AI algorithm for PH detection (ECG-AI PH) may enable earlier diagnosis and reduce healthcare utilization, including hospitalizations and procedures. Methods: Retrospective analysis used a de-identified data platform of >7M clinical records from a multistate integrated health system. Adult precapillary PH patients (mPAP >20 mmHg, PVR >2 WU, PCWP ≤15 mmHg) were identified as PAH or CTEPH based on ICD codes, use of approved therapies, or surgical interventions (for CTEPH) between 2002 and 2024. ECG-AI PH was applied to ECGs within 30 days of diagnostic right heart catheterization, using a 5:1 randomly sampled PH-negative control cohort. Training set patients were excluded. Clinical event frequency was compared between two intervals: from first possible PH symptom (dyspnea, syncope, chest pain, fatigue, lower limb swelling) to diagnosis, and from symptom onset to first positive ECG-AI PH prediction. Results: A total of 1882 PAH and 359 CTEPH patients met inclusion criteria. Of these, 1340 PAH and 258 CTEPH patients had symptom codes prior to diagnosis. Both groups showed prolonged intervals from symptom onset to diagnosis, with multiple diagnostic procedures and hospitalizations (Figure). ECG-AI PH performance evaluation on the test set included 647 PAH and 152 CTEPH patients. ECG-AI PH achieved AUCs of 0.90 and 0.89 for PAH and CTEPH, sensitivities of 80.3% and 76.8%, and specificities of 83.4% and 82.4%. Among those tested, 576 PAH and 95 CTEPH patients had a positive ECG-AI PH prediction after symptom onset but before diagnosis. Compared to the current patient journey, the interval between initial symptoms and a positive output from ECG-AI PH was shorter and had fewer diagnostic tests/visits. Conclusion: ECG-AI PH demonstrated strong performance in detecting PAH and CTEPH. It may reduce diagnostic delays, support earlier PH-focused screening (e.g., echocardiograms evaluating the right heart), enable earlier intervention, and reduce pre-diagnosis healthcare burden, benefitting both patient outcomes and healthcare system efficiency.

Introduction: PH increases RV afterload, often leading to RV systolic and diastolic failure. The metabolic mechanisms underlying RV dysfunction remain poorly understood and are largely unexplored across non-PAH forms of PH. Aims: We aimed to identify which metabolites and metabolic pathways associated with imaging measures of RV systolic function. Methods: We analyzed data from the multi-center PVDOMICS cohort, which includes echo, CMR, invasive hemodynamics, clinical phenotyping, and untargeted plasma metabolomics (via Metabolon). RV systolic function metrics selected as the outcome measures for this study were fractional area change (echo), global longitudinal strain (echo), and RVEF (CMR). Associations between non-xenobiotic, named metabolites and RV function measures were assessed using linear regression adjusted for age, sex, BMI, and PH group, with significance defined by FDR <0.05. Metabolite set enrichment analysis (MSEA) was performed to identify significantly enriched pathways (FDR <0.20). To complement MSEA, we conducted mean-aggregation analysis: we averaged metabolite concentrations within each pathway and tested associations with RV function using the same covariate adjustments (FDR <0.05). Results: We identified 979 participants with plasma metabolomics and at least one available outcome measure (317 Group 1 PH; 106 Group 2 PH; 140 Group 3 PH; 51 Group 4 PH; 26 Group 5 PH; 81 Healthy Controls; 258 Disease Comparators). Linear regression identified 170 metabolites from the 647 named metabolites significantly associated with all 3 RV metrics (Top 10 by average ranked p-value displayed in Image 1 ). MSEA revealed seven enriched pathways across all RV metrics: Androgenic Steroids, Pregnenolone Steroids, Progestin Steroids, Fatty Acid Metabolism (Acyl Choline), Histidine metabolism, Vitamin A metabolism, Gamma-glutamyl Amino Acid ( Image 2) . Mean aggregation analysis showed that higher concentrations of Androgenic/Pregnenolone Steroids and Vitamin A metabolites strongly associated with improved RV function, while higher levels of Fatty Acid Metabolism (Acyl Carnitine) and Acetylated Peptides associated with worse function ( Image 3 ). Conclusions: Using data from the multi-institutional PVDOMICS cohort, we provide a blueprint of metabolites and metabolic pathways associated with RV systolic function across the spectrum of PH. Steroid hormones as well as Vitamin A and fatty acid metabolites emerged as central to RV systolic function.

Background: A key determinant of prognosis in pulmonary hypertension (PH) is the right ventricle’s (RV) ability to adapt to increased pulmonary vascular resistance. Consequently, markers of RV-pulmonary artery (PA) coupling may improve prognostic prediction in PH. The ratio of tricuspid annular plane systolic excursion (TAPSE) to systolic PA pressure (sPAP) has been proposed as a surrogate for RV-PA coupling and a reliable prognostic marker, however, the existing data on the prognostic value of the ratio between RV longitudinal strain (RVLS) and sPAP as a surrogate for RV-PA coupling is scarce. Hypothesis: To evaluate the prognostic role of RVLS/RVSP in PH patients and to compare this novel marker with established markers of RV-PA coupling. Methods: This is a single-center study that included adult patients with PH classified as group I or IV, all of whom had undergone a transthoracic echocardiogram (TTE) within one year prior to the initiation of PH-specific treatment. Certified sonographers procured RV strain measurements using a specific software (Epsilon Imaging, Ann Arbor, MI). Receiver operating characteristic (ROC) analysis was used to determine the best cutoff for predicting all-cause mortality at one-year for RVLS/RVSP and TAPSE/RVSP. The association of RVLS/RVSP and TAPSE/RVSP with mortality at one year was assessed using the Kaplan-Meier analysis and multivariate Cox regression analysis (adjusted for REVEAL LITE 2.0 risk score). Results: A total of 160 patients were included with a median age of 67.2 (56.8, 73.7) years and 47 (29.2%) were male . ROC analysis revealed optimal cutoffs of 0.265 (AUC = 0.83) for RVLS/RVSP and 0.185 (AUC = 0.77) for TAPSE/RVSP to predict all-cause mortality at one year. One-year cumulative incidence of all-cause mortality was lower among patients with RVLS/RVSP ≥ 0.265 (0 % vs 13.7 %, p = 0.001) and patients with TAPSE/RVSP ≥ 0.185 (1.8 % vs 16.7 %, p = 0.001) (Figure 1) . In the multivariate analysis, RVLS/RVSP < 0.265 was associated with higher risk of mortality at one year (HR: 2.38, 95 % CI: 1.05 to 5.38, p = 0.036) while TAPSE/RVSP < 0.185 was not (HR: 2.01, 95 % CI: 0.93 to 4.31, p = 0.072). Conclusions: RVLS/ RVSP may be a valuable prognostic marker in PH patients and could outperform conventional TTE parameters as a surrogate for detecting RV-PA coupling.

Introduction: The ankle-brachial index (ABI) is the most common method for detecting peripheral arterial disease (PAD), but its sensitivity is limited, especially in patients with poorly compressible vessels. This study proposes a novel ultrasound-based approach for PAD diagnosis by analyzing calf muscle perfusion responses to pressure-cuff occlusion and exercise, interpreted using machine learning (ML) techniques. Methods: Under an IRB approved protocol and signed IRB-approved written consent, 48 participants, 43 symptomatic with abnormal ABI and 5 healthy volunteers were recruited for this study. High-frame-rate ultrasound B-mode image data (500 frames/s) were collected from 64 legs and categorized into two classes based on clinical diagnosis: Abnormal ABI (54 legs) and Healthy (10 legs). Legs with normal ABI from symptomatic patients were excluded to avoid diagnostic ambiguity, as these cases may lie within the diagnostic gray zone for PAD. Each leg underwent a 9-minute scanning protocol comprising 1 minute of baseline, 3 minutes of pressure cuff occlusion (using an automatic rapid inflation/deflation device), 2 minutes post-occlusion, 1 minute of plantar flexion exercise, and 2 minutes post-exercise. The ultrasound data were processed using singular-value decomposition (SVD) clutter filtering and noise equalization to generate Power-Doppler perfusion images at 2 frames per second. The PAD prediction pipeline involved data augmentation to address class imbalance and limited sample size, followed by histogram-based thresholding to extract blood pixels—intensity thresholding was avoided due to variability in pixel intensities. Blood pixel counts were calculated over time and used to train nine machine learning classification models (Figure 1). Results: The best-performing ML classification model achieved an accuracy of 77%, with the median accuracy across all models ranging between 70% and 72%. Notably, an ensemble model that combined Logistic Regression, Gradient Boosting, and Support Vector Machines using a majority voting strategy yielded the highest accuracy of 81% (Table 1). Conclusion: We proposed a novel ultrasound-based perfusion estimation method for diagnosing peripheral arterial disease (PAD), with data analyzed using ML approach. Although this is a feasibility study, the observed diagnostic accuracy exceeding 80% is promising. With further research and larger datasets, this approach has the potential to become a valuable tool for PAD.