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Right ventricular myocardial infarction (RVMI) is a significant and distinct form of acute myocardial infarction associated with considerable morbidity and mortality. It occurs most commonly due to proximal right coronary artery obstruction, often in conjunction with inferior myocardial infarction. RVMI poses unique diagnostic and therapeutic challenges due to the anatomical and functional differences between the right and left ventricles.

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Purpose Of Review: What is the pathophysiology and clinical findings as well as management of patients presenting with INOCA/MINOCA (Ischemia/Myocardial Infarction with Non-Obstructive Coronary Arteries).

Recent Findings: INOCA/MINOCA has a complex pathophysiology. In this review article, we aim to summarize the complex pathophysiology and clinical diagnosis, and review the current management options.

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This review considers high-risk electrocardiographic patterns in the acute coronary syndrome (ACS) patient; we review 7 electrocardiogram presentations lacking diagnostic criteria for ST-segment elevation myocardial infarction (STEMI) yet likely representing either STEMI equivalent syndromes or ACS presentations with significant short-and long-term risk. The STEMI equivalent presentations include acute posterior wall myocardial infarction, the hyperacute T-wave of early STEMI, de Winter syndrome, first diagonal of the left anterior descending artery occlusion, and left bundle branch block modified Sgarbossa positive findings. High-risk presentation, not felt to be STEMI equivalent entities yet still possessing significant risk of short-and long-term adverse outcome, include lead aVR ST-segment elevation and Wellens syndrome.

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Peripartum cardiomyopathy (PPCM) and takotsubo cardiomyopathy (TCM) are cardiac conditions that can occur in the peripartum period. They have distinct characteristics and incidence rates; although rare, both contribute to the second leading cause of all-cause maternal mortality in the state of Missouri. PPCM can lead to heart failure, and TCM can cause acute arrhythmias leading to sudden cardiac death in otherwise healthy individuals.

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Background: Acute Stanford Type A aortic dissection (AAD-type A) and acute myocardial infarction (AMI) present with similar symptoms but require distinct treatments. Efficient differentiation is critical due to limited access to radiological equipment in many primary healthcare. This study develops a multimodal deep learning model integrating electrocardiogram (ECG) signals and laboratory indicators to enhance diagnostic accuracy for AAD-type A and AMI.

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