Arrhythmias are increasingly recognized cardiovascular complications in patients with cancer, arising from both the malignancy and its therapies. Once considered unimportant compared to cancer treatment related heart failure, arrhythmias, particularly atrial fibrillation (AF) and ventricular arrhythmias (VA), are now recognized to play a major role in cardio-oncology due to their prognostic impact and effect on treatment continuity. Anthracyclines, immune checkpoint inhibitors and Bruton's tyrosine kinase inhibitors are linked to higher arrhythmic risk, ranging from asymptomatic ECG abnormalities to QT prolongation (QTp), conduction disorders and AF. Cellular therapies are linked to AF, mainly driven by cytokine-mediated myocardial inflammation. Cyclin-dependent kinase 4/6 inhibitors, especially ribociclib, may induce dose-related QTp and, less commonly, VA. Additionally, Takotsubo syndrome may occur in patients with active cancer due to stress and is often accompanied by early arrhythmic complications. Awareness and prevention of arrhythmias are essential to optimize patients' outcomes. Arrhythmias management requires individualized assessment, ECG surveillance, and multidisciplinary follow-up. We additionally propose a six-step framework to support early detection and prompt intervention of arrhythmias.

Cardiovascular diseases remain the leading cause of morbidity and mortality worldwide, and current risk scores based on personal history, physical examination and basic tests fail to identify a proportion of individuals who will experience cardiovascular events. In this context, handheld echocardiography (HHE) is an intermediate step between clinical assessment alone and comprehensive transthoracic echocardiography, with the potential to act as an imaging-based tool within cardiovascular prevention programmes. Through focused, bedside or outpatient examinations, HHE can detect early signs of hypertensive organ damage as well as left and right ventricular dysfunction and other structural cardiovascular abnormalities, beyond traditional clinical evaluation. Through an examination of current evidence, technological developments, and clinical implementation pathways, this review provides a comprehensive overview of the evolving role of HHE as an adjunct to standard cardiovascular assessment, highlighting its potential to enhance early risk stratification in preventive cardiology. In this context, it proposes a pragmatic worklist for focused HHE examinations in at-risk individuals and illustrates representative HHE use cases, with involvement of non-cardiologists and the potential contribution of teleconsultation and digital integration. Finally, unresolved challenges are highlighted, defining the research priorities for the systematic integration of HHE into cardiovascular prevention strategies.

Sleep is a multidimensional physiological state, and it is increasingly recognized as a core determinant of cardiovascular (CV) health. This review summarises the CV health attributes of important sleep dimensions, including sleep duration, regularity, timing, quality, efficiency, and napping. New device-measured data continue to demonstrate the importance of both direct and synergistic effects of sleep with movement and dietary lifestyle behaviours in relation to CV risk. Emerging adoption of the 24-hour framework by guidelines highlights the importance of addressing sleep, as part of the broader cluster of lifestyle-related health behaviours, for a more comprehensive understanding of health risks and intervention opportunities. The reviewed literature indicates that sleep, both independently and through its interrelationships with other lifestyle behaviours, plays an important role in shaping CV health. We identified potential interconnected mechanisms through which poor sleep may influence risk of cardiovascular disease (CVD), including heightened sympathetic drive, altered neuroendocrine activity, inflammatory and immune changes, metabolic dysregulation, and weight gain. Large-scale device-based prospective studies capturing multidimensional sleep characteristics are needed to further delineate causal pathways linking sleep dimensions to CV risk. Such an evidence base will advance holistic CVD prevention through better clinical interventions and public health policy.

The global burden of valvular heart disease (VHD) is increasingly burdensome, and precise early diagnosis combined with accurate risk stratification constitutes the core strategy for improving patient prognosis. As the first-line imaging modality for VHD assessment, echocardiography is constrained by interobserver variability and cumbersome, time-consuming data processing workflows, which prevent it from fully meeting the demands of precision medicine. In recent years, breakthroughs in artificial intelligence (AI), particularly deep learning (DL) technologies, have been reshaping the paradigm of imaging-based evaluation for VHD. This review systematically summarizes the latest advances in AI applications across the entire workflow of echocardiographic assessment in VHD: from the precise segmentation of valvular anatomical structures and identification of lesions using convolutional neural networks, to the automated grading of hemodynamic severity achieved through end-to-end learning. More importantly, this article explores how AI can surpass the limitations of traditional imaging indicators by leveraging unsupervised clustering to unearth potential high-risk phenotypes and integrating multimodal data to predict adverse outcomes. Finally, the paper critically analyzes the current challenges in data standardization, model interpretability, and clinical translation, and offers perspectives on future directions in the intersection of clinical medicine and engineering.

High-sensitivity C-reactive protein (hsCRP) is gaining recognition as an important prognostic biomarker in cardiovascular diseases (CVDs), including atherosclerotic CVD (ASCVD), with and without chronic kidney disease (CKD), and heart failure (HF). Evidence suggests that systemic inflammation, measured by hsCRP, is prevalent in individuals with ASCVD, CKD, and HF, and is linked to increased risk of cardiovascular events. This review explores the interconnectedness of ASCVD, CKD, and HF within the cardiovascular-kidney-metabolic axis, with systemic inflammation emerging as a common underlying driver. Prevalence estimates show that systemic inflammation (hsCRP ≥ 2 mg/L) is found in 38% to 59% of patients with ASCVD, in 42% to 65% of those with both ASCVD and CKD, and in over 50% in various HF cohorts. Elevated levels of hsCRP are consistently associated with higher rates of major adverse cardiovascular events and mortality across these populations. Although hsCRP is frequently found to carry prognostic value independent of traditional biomarkers such as low-density lipoprotein cholesterol, its clinical adoption in practice is held back in part by guideline variability, lack of standardized cutoffs, and debate over how results may change clinical management with currently available therapies. The review calls for further research to define optimal hsCRP thresholds, examines the role of hsCRP in cardiovascular risk assessment, and reviews the ongoing development programs for emerging anti-inflammatory therapies. Addressing systemic inflammation could become a cornerstone of CVD management, potentially reducing residual risk beyond traditional targets.

Late presentation in ST-segment elevation myocardial infarction (STEMI) remains common and clinically challenging, as the duration of myocardial ischemia has traditionally been considered the main determinant of infarct size. However, the conventional 12-hour cut-off, derived from fibrinolytic-era evidence, no longer fully reflects contemporary understanding of ischemia pathophysiology, advances in percutaneous coronary intervention (PCI), and the ability to assess residual myocardial viability. The optimal management of late-presenting STEMI therefore remains debated, as reflected by divergent international guideline recommendations and the heterogeneity of available randomized clinical trials. While early studies failed to demonstrate a clear benefit of late reperfusion, more recent observational and imaging-based data suggest that selected patients may still experience myocardial salvage and improved outcomes even when revascularization is performed beyond traditional temporal thresholds. Collectively, these observations indicate that time from symptom onset represents an imprecise surrogate of myocardial infarct evolution. Focusing exclusively on symptom duration oversimplifies a complex pathophysiological process and risks denying reperfusion to patients who may still derive meaningful benefit. This state-of-the-art review critically appraises current evidence on late-presenting STEMI and proposes a physiology- and imaging-guided framework that integrates clinical presentation, electrocardiographic dynamics, biomarker kinetics, and cardiac imaging to support biologically informed decision-making beyond rigid time-based cut-off.

Sudden cardiac death (SCD) causes 4 to 5 million deaths each year globally. Electrical vortices (tornadoes or rotors) are the origin of ventricular fibrillation (VF), which often causes SCD. Cardiac electrical vortices have complex dynamics and have been shown in many mammalian species. During VF, the heart fails to contract suitably and is unable to pump blood. Once VF is initiated, drug treatments are ineffective and even make things worse. The only effective treatment is electrical shock to the ventricles. Our current understanding of VF mechanisms is fragmentary, hindering the development of personalized therapies. Yet recent insights into the roles of the most critical sarcolemmal ion channels in VF in controlling the excitation-recovery process provide hope. Substantial evidence indicates that the molecular interplay between the main cardiac sodium channel (NaV1.5) and the strong inward-rectifier potassium current (Kir2.1) controls cardiac excitability, wave propagation velocity, and rotor formation, as well as rotor stability and frequency during VF. Studies at the cellular, molecular, and ion channel levels are helping us understand how rotors generate the turbulence that characterizes VF, providing insights into how to prevent their initiation and identifying new therapeutic targets to avert premature death.