Prescription Medication Use and Expenditure for Atrial Fibrillation in the United States.

Objectives: To study the national trends of anticoagulants, antiarrhythmic drugs (AADs), and expenditures in the civilian noninstitutionalized atrial fibrillation (AF) population.

Methods: The Medical Expenditure Panel Survey was queried from January 2016 to December 2021 to identify adults (age ≥18 years) with a diagnosis of AF utilizing the International Classification of Diseases, Tenth Revision, Clinical Modification code I48. Prevalence of anticoagulants (AAD) and its expenditure and AF expenditure across clinical settings in the United States were estimated.

Broadening Perspectives of Artificial Intelligence in Echocardiography.

Echocardiography frequently serves as the first-line treatment of diagnostic imaging for several pathological entities in cardiology. Artificial intelligence (AI) has been growing substantially in information technology and various commercial industries. Machine learning (ML), a branch of AI, has been shown to expand the capabilities and potential of echocardiography.

Cardiac arrest in the setting of probable catastrophic antiphospholipid syndrome in young patient with a history of COVID infection and polyglandular disorder-Case report.

Antiphospholipid syndrome is an autoimmune disorder characterized by arterial and venous thrombosis and recurrent spontaneous abortions due to the persistent presence of antiphospholipid antibodies. Probable Catastrophic antiphospholipid (Catastrophic antiphospholipid-like syndrome) is a life-threatening presentation of antiphospholipid syndrome which manifests as intravascular thrombosis, leading to rapid onset of symptoms and involvement of multiple organ systems. We present a case of a 28-year-old woman with a history of polyglandular autoimmune syndrome, systemic lupus erythematosus, provoked bilateral deep vein thrombosis in the setting of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection 2 years prior, and hypothyroidism who presents with a cardiac arrest in the setting of an acute ST-elevation myocardial infarction with thromboembolic occlusion of two coronary arteries simultaneously in the setting of noncompliance with anticoagulation for the past 1 week.

Lung Metastasis From Uterine Leiomyosarcoma: An Asymptomatic Presentation for a Rare Tumor.

Uterine leiomyosarcoma (ULC) is an uncommon neoplasm characterized by poor prognosis, it can predispose to distant metastasis, causing various symptomatic presentations. We present a unique case of a large heterogeneous mass in the lung cavity arising from a ULC, with complete absence of pulmonary symptoms and with concurrent coronavirus disease 2019 (COVID-19) infection. A high degree of clinical suspicion is required for ULC with accompanying metastasis.

Non-Calcified Coronary Artery Plaque on Coronary Computed Tomography Angiogram: Prevalence and Significance.

Objective: We aimed to assess the prevalence of non-calcified plaque (NCP) on computed tomography angiography (CCTA) in symptomatic and asymptomatic individuals. In addition, we seek to compare plaque assessment on CCTA with intravascular ultrasound-virtual histology (IVUS-VH) and to assess the prognostic value of non-calcified plaques (NCPs).

Background: The CCTA can characterize coronary plaques and help quantify burden.

A Case Report on Uremic Toxins and Their Effects on Cardiac Rhythm: Understanding Junctional Ventricular Escape Rhythm in Renal Failure.

Understanding the reasons behind junctional ventricular escape rhythm is crucial for guiding the clinical management of patients. Various factors such as acidosis, hyperkalemia, metabolic toxins, digoxin toxicity, and BRASH syndrome (comprising bradycardia, renal failure, atrioventricular (AV) nodal blockade, shock, and hyperkalemia) should be considered when dealing with a symptomatic unstable patient in a hospital. In this case, we present an example where metabolic toxins, specifically uremia, in combination with other factors, lead the patient to enter a ventricular escape rhythm, ultimately resulting in cardiogenic shock.

Role of Deep Learning in Computed Tomography.

Computed tomography has played an instrumental role in the understanding of the pathophysiology of atherosclerosis in coronary artery disease. It enables visualization of the plaque obstruction and vessel stenosis in a comprehensive manner. As technology for computed tomography is constantly evolving, coronary applications and possibilities are constantly expanding.

Integrating Echocardiography Parameters With Explainable Artificial Intelligence for Data-Driven Clustering of Primary Mitral Regurgitation Phenotypes.

Background: Primary mitral regurgitation (MR) is a heterogeneous clinical disease requiring integration of echocardiographic parameters using guideline-driven recommendations to identify severe disease.

Objectives: The purpose of this preliminary study was to explore novel data-driven approaches to delineate phenotypes of MR severity that benefit from surgery.

Methods: The authors used unsupervised and supervised machine learning and explainable artificial intelligence (AI) to integrate 24 echocardiographic parameters in 400 primary MR subjects from France (n = 243; development cohort) and Canada (n = 157; validation cohort) followed up during a median time of 3.

Acute effect of edge-to-edge repair of mitral regurgitation on left heart mechanics and health status.

Aims: Examine the impact of acute changes in left heart strain and volumes with percutaneous edge-to-edge MitraClip repair on improvement in health status assessed using Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) score.

Methods: Changes in left atrial strain, left ventricular (LV) global longitudinal strain (LVGLS), LV end-systolic volume (LVESV), and end-diastolic volume (LVEDV) were evaluated in 50 patients undergoing MitraClip repair for symptomatic primary mitral regurgitation (PMR) and secondary mitral regurgitation (SMR) on transthoracic echocardiography before and 1 month after MitraClip. Multivariable regression was used to evaluate changes in left heart strain and volumes as predictors of change in KCCQ-12 scores, adjusting for baseline clinical and echocardiographic characteristics.

Applications of Machine Learning in Cardiology.

In this digital era, artificial intelligence (AI) is establishing a strong foothold in commercial industry and the field of technology. These effects are trickling into the healthcare industry, especially in the clinical arena of cardiology. Machine learning (ML) algorithms are making substantial progress in various subspecialties of cardiology.

Community-Acquired Pneumonia Progressing to Necrotizing Pneumonia Due to Congenital Anatomical Abnormalities in the Lung.

Pneumonia is generally a treatable disease but there are instances when physicians are faced with rare circumstances such as congenital structural abnormalities. Structural abnormalities in the lungs may predispose to pneumonia and other complications. We present a patient with pneumonia, which progressed to necrotizing pneumonia.

Quantitative single photon emission computed tomography derived standardized uptake values on 99mTc-PYP scan in patients with suspected ATTR cardiac amyloidosis.

Technetium-99 pyrophosphate scintigraphy (99mTc-PYP) provides qualitative and semiquantitative diagnosis of ATTR cardiac amyloidosis (ATTR-CA) using the Perugini scoring system and heart/contralateral heart ratio (H/CL) on planar imaging. Standardized uptake values (SUV) with quantitative single photon emission computed tomography (xSPECT/CT) can offer superior diagnostic accuracy and quantification through precise myocardial contouring that enhances assessment of ATTR-CA burden. We examined the correlation of xSPECT/CT SUVs with Perugini score and H/CL ratio.

The Role of Cardiac Imaging in the Evaluation of Cardiac Involvement in Systemic Diseases.

For systemic diseases like rheumatoid arthritis, systemic lupus erythematosus (SLE), systemic sclerosis, systemic vasculitis, myopathies, and mixed connective tissue diseases, cardiac disease is a major contributing factor for morbidity and mortality. The cardiovascular manifestations are the result of various pathophysiological components, which complicate management. Furthermore, the signs and symptoms can be subtle and missed due to the complex nature of the underlying condition.

3D Transesophageal Echocardiography for Guiding Transcatheter Aortic Valve Replacement Without Prior Cardiac Computed Tomography in Patients With Renal Dysfunction.

Background: Pre-procedural chronic kidney disease (CKD) and in-hospital acute kidney injury (AKI) are associated with worse outcomes following transcatheter aortic valve replacement (TAVR). We tested the feasibility of reducing overall AKI by avoiding pre-procedural cardiac CT angiography (CCTA) by using direct 3D-TEE guidance in TAVR patients with known CKD.

Methods: An institutional TAVR database was examined from January 2016 to June 2020 to identify 396 patients in whom CCTA sizing was performed and 54 patients with creatinine (Cr) of >1.

Artificial intelligence and machine learning in cardiovascular computed tomography.

Computed tomography (CT) is emerging as a prominent diagnostic modality in the field of cardiovascular imaging. Artificial intelligence (AI) is making significant strides in the field of information technology, the commercial industry, and health care. Machine learning (ML), a branch of AI, can optimize the performance of CT and augment the assessment of coronary artery disease.

Cardiovascular Imaging and Intervention Through the Lens of Artificial Intelligence.

Artificial Intelligence (AI) is the simulation of human intelligence in machines so they can perform various actions and execute decision-making. Machine learning (ML), a branch of AI, can analyse information from data and discover novel patterns. AI and ML are rapidly gaining prominence in healthcare as data become increasingly complex.

Case of Supracristal Ventricular Septal Defect and Aortic Regurgitation Detected by Cardiac Auscultation but Missed by Diagnostic Imaging.

Imaging technology has diminished the reliance on cardiac auscultation as a definitive diagnostic tool. However, it retains relevance in its immediacy, minimal preparation, and power source independence. We present a case of clinically detected continuous murmur raising specific diagnostic possibilities not accounted for advanced imaging.

Artificial Intelligence and Machine Learning in Cardiovascular Imaging.

Cardiovascular disease is the leading cause of mortality in Western countries and leads to a spectrum of complications that can complicate patient management. The emergence of artificial intelligence (AI) has garnered significant interest in many industries, and the field of cardiovascular imaging is no exception. Machine learning (ML) especially is showing significant promise in various diagnostic imaging modalities.

The Role of Artificial Intelligence in Cardiovascular Imaging: State of the Art Review.

In this current digital landscape, artificial intelligence (AI) has established itself as a powerful tool in the commercial industry and is an evolving technology in healthcare. Cutting-edge imaging modalities outputting multi-dimensional data are becoming increasingly complex. In this era of data explosion, the field of cardiovascular imaging is undergoing a paradigm shift toward machine learning (ML) driven platforms.

CT assessment of the left atrial appendage post-transcatheter occlusion - A systematic review and meta analysis.

Background: Transesophageal echocardiography (TEE) is the standard imaging modality used to assess the left atrial appendage (LAA) after transcatheter device occlusion. Cardiac computed tomography angiography (CCTA) offers an alternative non-invasive modality in these patients. We aimed to conduct a comparison of the two modalities.

High Prevalence of Pericardial Involvement in College Student Athletes Recovering From COVID-19.

Objectives: This study sought to explore the spectrum of cardiac abnormalities in student athletes who returned to university campus in July 2020 with uncomplicated coronavirus disease 2019 (COVID-19).

Background: There is limited information on cardiovascular involvement in young individuals with mild or asymptomatic COVID-19.

Methods: Screening echocardiograms were performed in 54 consecutive student athletes (mean age 19 years; 85% male) who had positive results of reverse transcription polymerase chain reaction nasal swab testing of the upper respiratory tract or immunoglobulin G antibodies against severe acute respiratory syndrome coronavirus type 2.

Preoperative multidetector computed tomography for isolated surgical aortic valve replacement: Planning for future transcatheter options.

Background: Valve-in-valve (ViV) transcatheter aortic valve replacement (TAVR) has become a valuable option in patients with bioprosthetic failure. However, potential issues with ViV TAVR may occur in patients with high-risk anatomy for coronary obstruction and patients with baseline smaller bioprosthetic valves at risk for patient prosthesis mismatch. The purpose of this study was, therefore, to use preoperative electrocardiography-gated, multidetector computed tomography (MDCT) in patients undergoing isolated surgical aortic valve replacement (SAVR) to (1) identify which would be high risk for coronary occlusion with ViV TAVR, and (2) predict intraoperative SAVR sizing.

Infective Endocarditis After Surgical and Transcatheter Aortic Valve Replacement: A State of the Art Review.

Prosthetic valve endocarditis (PVE) after surgical aortic valve replacement and transcatheter aortic valve replacement (TAVR) carries significant morbidity/mortality. Our review aims to compare incidence, predisposing factors, microbiology, diagnosis, management, and outcomes of PVE in surgical aortic valve replacement/TAVR patients. We searched PubMed and Embase to identify published studies from January 1, 2015 to March 13, 2020.