Evaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems.

Background: While universal screening for Lp(a; lipoprotein[a]) is increasingly recommended, <0.5% of patients undergo Lp(a) testing. Here, we assessed the feasibility of deploying Algorithmic Risk Inspection for Screening Elevated Lp(a; ARISE), a validated machine learning tool, to health system electronic health records to increase the yield of Lp(a) testing.

Sodium-Glucose Cotransporter 2 Inhibitors and Changes in Epicardial Adipose Tissue: A Systematic Literature Review And Meta-Analysis.

Introduction: Sodium-glucose cotransporter 2 (SGLT2) inhibitors have emerged as a groundbreaking class of antidiabetic medications renowned for their glucose-lowering effects and cardiovascular benefits. Recent studies have suggested that SGLT2 inhibitors may extend their influence beyond glycemic control to impact adipose tissue physiology, particularly within the epicardial adipose depot. Epicardial adipose tissue (EAT), an actively secretory organ surrounding the heart, has been implicated in the modulation of cardiovascular risk.

Heart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study.

Background And Aims: Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF risk.

Methods: Across multinational cohorts in the Yale New Haven Health System (YNHHS), UK Biobank (UKB), and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), individuals without baseline HF were followed for the first HF hospitalization.

Endothelial Glycocalyx Damage and Arterial Thickness in Patients with Retinal Vein Occlusion (RVO).

: Retinal vein occlusion (RVO) is a relatively uncommon condition with a complex pathophysiology. However, its association with traditional cardiovascular risk factors is well established. In this study, we compared arterial stiffness and endothelial function between patients with RVO and healthy controls.

Navigating Heart-Lung Interactions in Mechanical Ventilation: Pathophysiology, Diagnosis, and Advanced Management Strategies in Acute Respiratory Distress Syndrome and Beyond.

Patients in critical condition who require mechanical ventilation experience intricate interactions between their respiratory and cardiovascular systems. These complex interactions are crucial for clinicians to understand as they can significantly influence therapeutic decisions and patient outcomes. A deep understanding of heart-lung interactions is essential, particularly under the stress of mechanical ventilation, where the right ventricle plays a pivotal role and often becomes a primary concern.

Dulaglutide and Dapagliflozin Combination Concurrently Improves the Endothelial Glycocalyx and Vascular and Myocardial Function in Patients with T2DM and Albuminuria vs. DPP-4i.

: The association between diabetic nephropathy and arterial elasticity and endothelial function is well established. In this study, we compared the effect of the combination of dulaglutide and dapagliflozin versus DPP-4 inhibitors on the endothelial glycocalyx, arterial stiffness, myocardial function, and albuminuria. : Overall, 60 patients were randomized to combined dulaglutide and dapagliflozin treatment (n = 30) or DPP-4 inhibitors (DPP-4i, n = 30) (ClinicalTrials.

Cancer Therapy-Related Cardiac Dysfunction: A Review of Current Trends in Epidemiology, Diagnosis, and Treatment.

Cancer therapy-related cardiac dysfunction (CTRCD) has emerged as a significant concern with the rise of effective cancer treatments like anthracyclines and targeted therapies such as trastuzumab. While these therapies have improved cancer survival rates, their unintended cardiovascular side effects can lead to heart failure, cardiomyopathy, and arrhythmias. The pathophysiology of CTRCD involves oxidative stress, mitochondrial dysfunction, and calcium dysregulation, resulting in irreversible damage to cardiomyocytes.

International Validation of Echocardiographic AI Amyloid Detection Algorithm.

Background: Diagnosis of cardiac amyloidosis (CA) is often missed or delayed due to confusion with other causes of increased left ventricular wall thickness. Conventional transthoracic echocardiographic measurements like global longitudinal strain (GLS) has shown promise in distinguishing CA, but with limited specificity. We conducted a study to investigate the performance of a computer vision detection algorithm in across multiple international sites.

Oxidative Stress Biomarkers in Hypertension.

Arterial hypertension is a silent and progressive disease with deleterious vascular implications on all target organs, including the heart, the brain, the kidneys, and the eyes. Oxidative stress, defined as the overproduction of Reactive Oxygen Species (ROS) over antioxidants, is capable of deteriorating not only the normal endothelial but also the cellular function with further cardiovascular implications. Xanthine oxidase activity, NADPH oxidase overexpression, and ROS production lead to hypertension and high arterial tone, culminating in end-organ damage.

Tailored Therapies for Cardiogenic Shock in Hypertrophic Cardiomyopathy: Navigating Emerging Strategies.

Hypertrophic cardiomyopathy (HCM) is a complex and heterogeneous cardiac disorder, often complicated by cardiogenic shock, a life-threatening condition marked by severe cardiac output failure. Managing cardiogenic shock in HCM patients presents unique challenges due to the distinct pathophysiology of the disease, which includes dynamic left ventricular outflow tract obstruction, diastolic dysfunction, and myocardial ischemia. This review discusses current and emerging therapeutic strategies tailored to address the complexities of HCM-associated cardiogenic shock and other diseases with similar pathophysiology that provoke left ventricular outflow tract obstruction.

Acellular Appendix Vermiform Mucinous Neoplasm.

Appendiceal neoplasms are usually asymptomatic or associated with mild, nonspecific symptoms. Due to the rarity of the disease and the lack of specific symptoms, this clinical entity escapes the diagnostic consideration of the gynecologist, when women come in with right iliac fossa pain. A case is presented of a 56-year-old woman with a mass in the right small pelvis, which was preoperatively diagnosed as originating from the ovary.

An Updated Review on Arterial Stiffness Measurement Techniques and Arterial Stiffness Alterations After Aortic Aneurysm Repair.

Background: Studies over the last years have revealed the possible impact of endovascular repair of abdominal or thoracic aortic aneurysms on the arterial stiffness and secondary on the cardiac function and the central hemodynamics.

Methods: A literature search was conducted to collect data on current methods of arterial stiffness assessment and the induced changes in arterial stiffness after endovascular or open surgical repair of abdominal or thoracic aortic aneurysms.

Results: Seventeen studies were analyzed.

A deep learning approach to real-time Markov modeling of ion channel gating.

The patch-clamp technique allows us to eavesdrop the gating behavior of individual ion channels with unprecedented temporal resolution. The signals arise from conformational changes of the channel protein as it makes rapid transitions between conducting and non-conducting states. However, unambiguous analysis of single-channel datasets is challenging given the inadvertently low signal-to-noise ratio as well as signal distortions caused by low-pass filtering.

Physical Activity Habits Among Physicians: Data From the Athens Medical Association.

Background: Physicians' exercise habits vary across different medical specialties and health service infrastructure. We assessed physicians' exercise performance according to the recommendations of the 2020 European Society of Cardiology Guidelines.

Methods: This cross-sectional study comprised 742 physicians of the Athens Medical Association (AMA), Greece.

Cannabis Use during Pregnancy: An Update.

The use of cannabis during pregnancy has emerged as a mounting cause for concern due to its potential adverse consequences on both the mother and her offspring. This review will focus on the dangers associated with prenatal exposure to cannabis, particularly those related to neurodevelopment. It will also discuss the features of maternal and placental functioning that are likely to have long-term effects on the offspring's development.

Multifaceted Impact of SGLT2 Inhibitors in Heart Failure Patients: Exploring Diverse Mechanisms of Action.

Heart failure (HF) is a growing concern due to the aging population and increasing prevalence of comorbidities. Despite advances in treatment, HF remains a significant burden, necessitating novel therapeutic approaches. Sodium-glucose cotransporter 2 inhibitors (SGLT2is) have emerged as a promising treatment option, demonstrating benefits across the entire spectrum of HF, regardless of left ventricular ejection fraction (LVEF).

Wearable Activity Trackers and Physical Activity Levels Among Members of the Athens Medical Association in Greece.

Introduction: Wearable Activity Trackers (WATs) offer real-time feedback on activity levels. We assessed the impact of WAT usage on physicians' exercise habits.

Methods: Physicians from the Athens Medical Association, Greece (n = 742) responded to a self-administered questionnaire evaluating usage of WAT, demographic characteristics, specialty, and physical exercise habits.

Development and Multinational Validation of an Ensemble Deep Learning Algorithm for Detecting and Predicting Structural Heart Disease Using Noisy Single-lead Electrocardiograms.

Background And Aims: AI-enhanced 12-lead ECG can detect a range of structural heart diseases (SHDs) but has a limited role in community-based screening. We developed and externally validated a noise-resilient single-lead AI-ECG algorithm that can detect SHD and predict the risk of their development using wearable/portable devices.

Methods: Using 266,740 ECGs from 99,205 patients with paired echocardiographic data at Yale New Haven Hospital, we developed ADAPT-HEART, a noise-resilient, deep-learning algorithm, to detect SHD using lead I ECG.

An Ensemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images: PRESENT SHD.

Background: Identifying structural heart diseases (SHDs) early can change the course of the disease, but their diagnosis requires cardiac imaging, which is limited in accessibility.

Objective: To leverage images of 12-lead ECGs for automated detection and prediction of multiple SHDs using an ensemble deep learning approach.

Methods: We developed a series of convolutional neural network models for detecting a range of individual SHDs from images of ECGs with SHDs defined by transthoracic echocardiograms (TTEs) performed within 30 days of the ECG at the Yale New Haven Hospital (YNHH).