The 143 low- and middle-income countries (LMICs) of the world constitute 80% of the world's population or roughly 5.86 billion people with much variation in geography, culture, literacy, financial resources, access to health care, insurance penetration, and healthcare regulation. Unfortunately, their burden of cardiovascular disease in general and acute ST-segment-elevation myocardial infarction (STEMI) in particular is increasing at an unprecedented rate. Compounding the problem, outcomes remain suboptimal because of a lack of awareness and a severe paucity of resources. Guideline-based treatment has dramatically improved the outcomes of STEMI in high-income countries. However, no such focused recommendations exist for LMICs, and the unique challenges in LMICs make directly implementing Western guidelines unfeasible. Thus, structured solutions tailored to their individual, local needs, and resources are a vital need. With this in mind, a multicountry collaboration of investigators interested in LMIC STEMI care have tried to create a consensus document that extracts transferable elements from Western guidelines and couples them with local realities gathered from expert experience. It outlines general operating principles for LMICs focused best practices and is intended to create the broad outlines of implementable, resource-appropriate paradigms for management of STEMI in LMICs. Although this document is focused primarily on governments and organizations involved with improvement in STEMI care in LMICs, it also provides some specific targeted information for the frontline clinicians to allow standardized care pathways and improved outcomes.

Late gadolinium enhancement (LGE) is an important prognostic marker in hypertrophic cardiomyopathy and an extent >15% it is associated with high risk of sudden cardiac death. We proposed a novel method, the LGE-dispersion mapping, to assess heterogeneity of scar, and evaluated its prognostic role in patients with hypertrophic cardiomyopathy.

Cardiac resynchronization therapy (CRT) improves heart failure outcomes but has significant nonresponse rates, highlighting limitations in ECG selection criteria: QRS duration (QRSd) ≥150 ms and subjective labeling of left bundle branch block (LBBB). We explored unsupervised machine learning of ECG waveforms to identify CRT subgroups that may differentiate outcomes beyond QRSd and LBBB.

Dofetilide is one of the only anti-arrhythmic agents approved for atrial fibrillation (AF) in patients with reduced left ventricular ejection fraction (LVEF). However, postapproval data and safety outcomes are limited. In this study, we assessed the incidence and predictors of LVEF improvement, safety, and outcomes in patients with AF with LVEF ≤35% without prior implantable cardioverter defibrillator, cardiac resynchronization therapy, or AF ablation.

To facilitate ablation of ventricular tachycardia (VT), an automated localization system to identify the site of origin of left ventricular activation in real time using the 12-lead ECG was developed. The objective of this study was to prospectively assess its accuracy.

Scientific research on atrial fibrosis in atrial fibrillation (AF) has mainly focused on quantitative or molecular features. The purpose of this study was to perform a clinicoarchitectural/structural investigation of fibrosis to provide one key to understanding the electrophysiological/clinical aspects of AF.

Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a methodology that combines machine learning (ML) and personalized computational modeling to predict, before PVI, which patients are most likely to experience AF recurrence after PVI.

Mutations in the gene encoding the cardiac voltage-gated sodium channel Nav1.5 cause various cardiac arrhythmias. This variety may arise from different determinants of Nav1.5 expression between cardiomyocyte domains. At the lateral membrane and T-tubules, Nav1.5 localization and function remain insufficiently characterized.

Early risk stratification is essential for in-hospital management of ST-segment-elevation myocardial infarction. Acute heart failure confers a worse prognosis, and although lung ultrasound (LUS) is recommended as a first-line test to assess pulmonary congestion, it has never been tested in this setting. Our aim was to evaluate the prognostic ability of admission LUS in patients with ST-segment-elevation myocardial infarction.

Coronavirus disease 2019 (COVID-19) has presented substantial challenges to patient care and impacted healthcare delivery, including cardiac electrophysiology practice throughout the globe. Based upon the undetermined course and regional variability of the pandemic, there is uncertainty as to how and when to resume and deliver electrophysiology services for patients with arrhythmia. This joint document from representatives of the Heart Rhythm Society, American Heart Association, and American College of Cardiology seeks to provide guidance for clinicians and institutions reestablishing safe electrophysiological care. To achieve this aim, we address regional and local COVID-19 disease status, the role of viral screening and serological testing, return-to-work considerations for exposed or infected health care workers, risk stratification and management strategies based on COVID-19 disease burden, institutional preparedness for resumption of elective procedures, patient preparation and communication, prioritization of procedures, and development of outpatient and periprocedural care pathways.

Abnormal QT interval responses to heart rate (QT dynamics) is an independent risk predictor for cardiovascular disease in patients, but its genetic basis and prognostic value in a population-based cohort have not been investigated.

Complications of percutaneous coronary intervention (PCI) may have significant impact on patient survival and healthcare costs. PCI procedural complexity and patient risk are increasing, and operators must be prepared to recognize and treat complications, such as perforations, dissections, hemodynamic collapse, no-reflow, and entrapped equipment. Unfortunately, few resources exist to train operators in PCI complication management. Uncertainty regarding complication management could contribute to the undertreatment of patients with high-complexity coronary disease. We, therefore, coordinated the Learning From Complications: How to Be a Better Interventionalist courses to disseminate the collective experience of high-volume PCI operators with extensive experience in chronic total occlusion and high-risk PCI. From these conferences in 2018 and 2019, we developed algorithms that emphasize early recognition, effective treatment, and team-based care of PCI complications. We think that an algorithmic approach will result in a logical and systematic response to life-threatening complications. This construct may be useful for operators who plan to perform complex PCI procedures.