Mapping of Neuro-Cardiac Electrophysiology: Interlinking Epilepsy and Arrhythmia.

The interplay between neurology and cardiology has gained significant attention in recent years, particularly regarding the shared pathophysiological mechanisms and clinical comorbidities observed in epilepsy and arrhythmias. Neuro-cardiac electrophysiology mapping involves the comprehensive assessment of both neural and cardiac electrical activity, aiming to unravel the intricate connections and potential cross-talk between the brain and the heart. The emergence of artificial intelligence (AI) has revolutionized the field by enabling the analysis of large-scale data sets, complex signal processing, and predictive modeling.

Prospective of Pancreatic Cancer Diagnosis Using Cardiac Sensing.

Pancreatic carcinoma (Ca Pancreas) is the third leading cause of cancer-related deaths in the world. The malignancies of the pancreas can be diagnosed with the help of various imaging modalities. An endoscopic ultrasound with a tissue biopsy is so far considered to be the gold standard in terms of the detection of Ca Pancreas, especially for lesions <2 mm.

Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives.

The measurement of physiologic pressure helps diagnose and prevent associated health complications. From typical conventional methods to more complicated modalities, such as the estimation of intracranial pressures, numerous invasive and noninvasive tools that provide us with insight into daily physiology and aid in understanding pathology are within our grasp. Currently, our standards for estimating vital pressures, including continuous BP measurements, pulmonary capillary wedge pressures, and hepatic portal gradients, involve the use of invasive modalities.

Methicillin-Resistant Sepsis and Orbital Cellulitis Leading to a Combined Central Retinal Artery and Vein Occlusion: A Case Report.

Combined central retinal artery and vein occlusion (CCRAVO) is a rare entity characterized by features of tortuous retinal veins, retinal hemorrhage, optic disk edema and pallor, macula edema, cherry-red spot, and cotton-wool spots. The occurrence of CCRAVO in the adult population is often in the setting of systemic disease; while CCRAVO in the pediatric population is frequently associated with infection of the sinuses, preseptal cellulitis, or orbital cellulitis. It has been hypothesized that CCRAVO can result from methicillin-resistant (MRSA) sepsis-induced coagulation disturbances, orbital cellulitis, and even orbital compartment syndrome; however, there are insufficient reports of this complication.

Targeted Atrial Fibrillation Therapy and Risk Stratification Using Atrial Alternans.

Atrial fibrillation (AF) is the most persistent arrhythmia today, with its prevalence increasing exponentially with the rising age of the population. Particularly at elevated heart rates, a functional abnormality known as cardiac alternans can occur prior to the onset of lethal arrhythmias. Cardiac alternans are a beat-to-beat oscillation of electrical activity and the force of cardiac muscle contraction.

Leflunomide-Induced Immune-Mediated Necrotizing Myopathy in a Patient With Rheumatoid Arthritis: A Case Report.

Immune-mediated necrotizing myopathy (IMNM) is a subtype of inflammatory myopathy that is characterized by proximal muscle weakness, markedly elevated serum creatine kinase, myopathic electromyographic findings, and muscle biopsies revealing necrosis or regeneration with sparse inflammatory infiltrate. IMNM tends to be idiopathic but has been associated with certain medications. This supports the possibility for other pharmacotherapies to induce IMNM-particularly leflunomide.

NATURAL LANGUAGE PROCESSING BASED MACHINE LEARNING MODEL USING CARDIAC MRI REPORTS TO IDENTIFY HYPERTROPHIC CARDIOMYOPATHY PATIENTS.

Hypertrophic Cardiomyopathy (HCM) is the most common genetic heart disease in the US and is known to cause sudden death (SCD) in young adults. While significant advancements have been made in HCM diagnosis and management, there is a need to identify HCM cases from electronic health record (EHR) data to develop automated tools based on natural language processing guided machine learning (ML) models for accurate HCM case identification to improve management and reduce adverse outcomes of HCM patients. Cardiac Magnetic Resonance (CMR) Imaging, plays a significant role in HCM diagnosis and risk stratification.