Phoenixville Hospital

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    Electrocardiographic Clues to Arrhythmogenic Right Ventricular Cardiomyopathy

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    Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterized by fibrofatty replacement of the right ventricular (RV) myocardium, predisposing to ventricular arrhythmias, RV dysfunction, and sudden cardiac death. Early recognition relies heavily on electrocardiographic (ECG) findings, which often precede overt structural changes. We report a case of a 28-year-old woman presenting with intermittent chest pressure, palpitations, and mild exertional dyspnea. Vital signs were stable, and troponin was normal. Initial 12-lead ECG demonstrated normal sinus rhythm with frequent premature ventricular contractions (PVCs) and T-wave inversions in leads V1–V3. Continuous telemetry revealed frequent runs of monomorphic non-sustained ventricular tachycardia (NSVT) with left bundle-branch block (LBBB) morphology, consistent with RV origin. Transthoracic echocardiography showed RV dilation and regional hypokinesis, with preserved left ventricular size and systolic function. The combination of anterior precordial T-wave inversions, frequent ventricular ectopy of RV origin, and echocardiographic RV abnormalities fulfilled the diagnostic criteria for ARVC. The patient had no sustained or hemodynamically significant VT and no history of syncope or sudden cardiac death. She was initiated on beta-blocker therapy, resulting in significant improvement of arrhythmias, and was recommended for cardiac magnetic resonance imaging and genetic testing for confirmation and familial assessment. Key electrocardiographic markers of ARVC include: T-wave inversions in V1–V3, ventricular arrhythmias with LBBB morphology, and epsilon waves or prolonged terminal QRS activation in right precordial leads. Early recognition using these ECG clues is essential for risk stratification, guiding further imaging, genetic evaluation, and appropriate management

    TCT-161 AI-Assisted Versus Interventional Cardiologist-Guided Intravascular Imaging for PCI in Calcified Coronary Artery Disease: A Comparative Analysis

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    Background: Heavily calcified coronary lesions present a major challenge during percutaneous coronary intervention (PCI), where optimal stent expansion is critical for long-term success. Intravascular imaging modalities such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT) assist in procedural planning, but their interpretation is often subjective. Artificial intelligence (AI)-enhanced image analysis may improve decision-making consistency and outcomes. Out study objective was to compare procedural and clinical outcomes between AI-assisted versus interventional cardiologist-guided intravascular imaging for PCI in patients with severely calcified coronary artery disease. Methods: We retrospectively analyzed 800 patients undergoing PCI for calcified coronary lesions using IVUS or OCT, with 400 managed via AI-guided imaging interpretation and 400 via manual interpretation by experienced interventional cardiologists. Primary endpoint was optimal stent expansion (\u3e90%). Secondary endpoints included procedural success, 12-month major adverse cardiovascular events (MACE), target lesion revascularization (TLR), contrast volume, and radiation exposure. Results: Baseline characteristics were similar between groups. Optimal stent expansion was significantly higher in the AI-guided group (87.0% vs. 77.0%, p=0.0018), with greater procedural success (97.5% vs. 93.5%, p=0.018) and lower contrast volume (146.3 ± 28.7 mL vs. 158.5 ± 30.2 mL, p\u3c 0.001). TLR at 12 months was reduced in the AI group (3.0% vs. 5.5%, p=0.045), while MACE rates were comparable (7.0% vs. 9.0%, p=0.29). Radiation exposure was also lower with AI guidance (p\u3c 0.001). Conclusion: AI-assisted intravascular imaging guidance during PCI for calcified coronary lesions is associated with improved stent optimization, higher procedural success, and lower procedural burden compared to cardiologist-guided interpretation. These results support the integration of AI in intraprocedural imaging workflows to enhance PCI outcomes. Categories: IMAGING AND PHYSIOLOGY: Artificial Intelligence: Imaging and Physiolog

    TCT-225 Artificial Intelligence-Based Versus 3mensio Software-Based Preprocedural Planning for TAVR: A Comparative Analysis of Clinical Outcomes

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    Background: 3mensio is a widely adopted software for TAVR preprocedural planning. Recently, AI-driven automated platforms have emerged, offering faster, operator-independent planning. This study aims to compare clinical outcomes between TAVR procedures planned with AI-based software and those planned with 3mensio. Methods: We conducted a retrospective cohort study of 980 patients undergoing transfemoral TAVR from 2021–2024. Patients were stratified into two groups: AI planning (n = 420) and 3mensio-based planning (n = 560). Baseline characteristics, procedural metrics, and clinical outcomes—including device success, paravalvular leak (PVL), new permanent pacemaker implantation (PPI), and 30-day mortality—were compared. Results: Device success was significantly higher in the AI group compared to 3mensio (96.2% vs. 92.5%, p = 0.03). Moderate or severe PVL occurred in 2.1% of AI-planned cases vs. 5.6% in the 3mensio group (p = 0.01). PPI rate was lower in the AI group (8.5% vs. 11.3%, p = 0.04). There was no significant difference in 30-day all-cause mortality (2.3% vs. 2.9%, p = 0.52). Planning time was significantly reduced in the AI group (12 ± 3 min vs. 34 ± 5 min, p \u3c 0.001). Conclusion: AI-based TAVR planning was associated with improved procedural outcomes, reduced PVL and PPI, and faster planning time compared to 3mensio. These findings support broader integration of AI into structural heart planning workflows. Categories: STRUCTURAL: Artificial Intelligence: Structura

    Cardiovascular outcomes of patients with atrial fibrillation and concomitant cardiac amyloidosis undergoing percutaneous catheter ablation.

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    BACKGROUND: Atrial fibrillation has been linked with poor outcomes in patients with cardiac amyloidosis. We evaluate the in-hospital outcomes of patients with atrial fibrillation and concomitant cardiac amyloidosis with and without catheter ablation. METHODS: The National Inpatient Sample databases (2016 to 2021) were queried to identify patients admitted with atrial fibrillation and concomitant cardiac amyloidosis using ICD 10 codes. The study population aged \u3e18 years was divided into two cohorts; ablation (AB) vs. no ablation (NAB). Multivariate logistic regression model adjusting for baseline characteristics and comorbidities. The primary outcome was all-cause in-hospital mortality. Secondary outcomes were acute heart failure, cardiogenic shock, ventricular fibrillation, major bleeding, stroke, length of stay, and hospitalization cost. RESULTS: 73,160 patients were identified. 595(0.8 %) underwent ablation and 72,656 (99.2 %) did not. Both NAB and AB patients were predominantly white (69.6 % and 60.3 %) respectively. AB patients were younger with median age [74 years (IQR 66-80) vs. 78 years (IQR 71-84), p \u3c 0.01], compared with NAB patients. AB patients were more likely to have heart failure (76.5 % vs. 65.3 %, p = 0.04), and have a family history of CAD (11.1 % vs. 4.8 %, p = 0.03). Contrarily, NAB patients were more likely to have dementia (11.5 % vs. 2.5 %, p = 0.01). After adjusting for baseline characteristics and comorbidity, there was no difference in all-cause mortality (OR 0.3, CI 0.08-1.35, p = 0.12), stroke (OR 1.1, CI 0.4-2.8, p = 0.87), or major bleeding (OR 1.4, CI 0.7-2.6, p = 0.37). Undergoing ablation was associated with higher odds of acute heart failure (OR 1.9, CI 1.1-3.3, p CONCLUSION: Atrial fibrillation and concomitant cardiac amyloidosis in patients undergoing catheter ablation are associated with an increased risk of acute heart failure, higher cost, and a longer length of stay

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