Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, associated with significant morbidity, mortality, and healthcare burden. Despite advances in AF management, challenges persist in early detection, risk stratification, and treatment optimization, necessitating innovative solutions. Artificial intelligence (AI) has emerged as a transformative tool in AF care, leveraging machine learning and deep learning algorithms to enhance diagnostic accuracy, improve risk prediction, and guide therapeutic interventions. AI-powered electrocardiographic screening has demonstrated the ability to detect asymptomatic AF, while wearable photoplethysmography-based technologies have expanded real-time rhythm monitoring beyond clinical settings. AI-driven predictive models integrate electronic health records and multimodal physiological data to refine AF risk stratification, stroke prediction, and anticoagulation decision making. In the realm of treatment, AI is revolutionizing individualized therapy and optimizing anticoagulation management and catheter ablation strategies. Notably, AI-enhanced electroanatomic mapping and real-time procedural guidance hold promise for improving ablation success rates and reducing AF recurrence. Despite these advancements, the clinical integration of AI in AF management remains an evolving field. Future research should focus on large-scale validation, model interpretability, and regulatory frameworks to ensure widespread adoption. This review explores the current and emerging applications of AI in AF, highlighting its potential to enhance precision medicine and patient outcomes.

Obesity-associated inflammation underlies much of cardiometabolic pathology, reflecting the convergence of chronic, low-grade systemic immune activation with region-specific maladaptation of adipose depots. Among these, epicardial adipose tissue (EAT)—a visceral fat layer contiguous with the myocardium and sharing its microvasculature—functions as a cardio-proximal immunometabolic interface that influences atrial fibrillation, heart failure with preserved ejection fraction, and coronary atherogenesis through paracrine crosstalk. These relationships extend beyond crude measures of adiposity, emphasizing the primacy of local inflammatory signaling, adipokine flux, and fibro-inflammatory remodeling at the EAT–myocardium interface. Of importance, substantial weight reduction only partially reverses obesity-imprinted transcriptional and epigenetic programs across subcutaneous, visceral, and epicardial depots, supporting the concept of an enduring adipose memory that sustains cardiovascular (CV) risk despite metabolic improvement. Accordingly, therapeutic strategies should move beyond weight-centric management toward mechanism-guided interventions. Resolution pharmacology—leveraging specialized pro-resolving mediators and their cognate G-protein-coupled receptors—offers a biologically plausible means to terminate inflammation and reprogram immune–stromal interactions within adipose and CV tissues. Although preclinical studies report favorable effects on vascular remodeling, myocardial injury, and arrhythmic vulnerability, clinical translation is constrained by pharmacokinetic liabilities of native mediators and by incomplete validation of biomarkers for target engagement. This review integrates mechanistic, depot-resolved, and therapeutic evidence to inform the design of next-generation anti-inflammatory strategies for obesity-related CV disease.

Atrial fibrillation (AF) is the most common sustained arrhythmia and a growing global health burden, yet conventional monitoring with Holter devices, event recorders and implantable loop recorders often fails to adequately capture recurrence. Rapid advances in digital health, wearable biosensors and artificial intelligence (AI) have transformed consumer smartwatches and wearables into potential clinical tools capable of continuous, real-world rhythm surveillance. This narrative review synthesizes contemporary evidence on smartwatch-based AF monitoring, spanning core technologies—photoplethysmography, single-lead electrocardiography and AI fusion algorithms—and validation studies across post-ablation follow-up. Compared with traditional modalities, smartwatch-based AF monitoring demonstrates improved detection of AF recurrence, enhanced characterization of AF burden, symptom–rhythm correlation, and greater patient engagement. At the same time, key limitations are critically examined, including motion artifacts, false-positive alerts, short recording windows, adherence dependence, digital literacy and access gaps, as well as unresolved issues around regulation, interoperability and data privacy. By integrating engineering advances with guideline-directed care pathways, smartwatch-based AF monitoring holds promise to complement, rather than immediately replace, established diagnostic tools and to enable more proactive, individualized AF management. Future work must focus on robust clinical validation, equitable implementation and clear regulatory frameworks to safely scale these technologies.

Baseline RV function potentially determines response to Cardiac Resynchronization Therapy (CRT) but is not included in the current selection criteria for CRT. In this meta-analysis, we examine the value of echocardiographic indices of RV function as potential predictors of CRT outcomes in patients with standard indications for CRT. Baseline tricuspid annular plane systolic excursion (TAPSE) was consistently higher in CRT responders, and this association appears independent of age, sex, ischemic etiology of HF, and baseline left-ventricular ejection fraction (LVEF). This proof-of-concept meta-analysis of observational data may justify a more detailed assessment of RV function as an additional component in the selection process of CRT candidates.

Background: Right ventricular (RV) failure is an important predicting factor regarding overall and event-free survival regardless of baseline left ventricular (LV) function in patients with severe heart failure (HF). Previous studies have indicated that cardiac resynchronization therapy (CRT) improves LV and RV reverse remodeling in patients with systolic dyssynchrony within the left ventricle. However, there is conflicting evidence regarding the role of CRT in RV function. The aim of this systematic review and meta-analysis was to examine the implications of CRT on RV function indices. Methods: A systematic literature search was conducted using the MedLine and EMBASE databases and the Cochrane Library from their inception until 18 March 2024. Eligible were studies providing information on RV function indices, both at baseline and after CRT. Evidence was summarized using random-effects meta-analytic models. Results: In total, 30 studies were deemed eligible. CRT resulted in a significant improvement in right ventricular fractional area change (mean difference (MD) 5.11%, 95% confidence interval (CI) 2.83 to 7.39), tricuspid annular plane systolic excursion (TAPSE, MD 1.63 mm, 95% CI 1.10 to 2.16), and myocardial systolic excursion velocity (MD 1.85 cm/s, 95% CI 1.24 to 2.47) as well as a significant decrease in pulmonary artery systolic pressure (MD −6.24 mmHg, 95% CI −8.32 to −4.16). A non-significant effect was observed on TAPSE to PASP ratio and right ventricular global longitudinal strain. Conclusions: Our meta-analysis demonstrates that CRT is associated with a significant improvement in echocardiographic parameters of RV function. Further investigation is necessary to elucidate how these changes, both independently and in conjunction with LV improvement, impact patients’ long-term prognosis, and to identify the specific patient populations expected to derive the greatest benefit.

Despite significant advancements in medical therapy, heart failure with reduced ejection fraction (HFrEF) continues to be a significant cause of death and disability. Reversible ischaemic left ventricular dysfunction due to viable myocardium is one such contributing factor. In these cases, coronary revascularization has shown promise in improving left ventricular function and prognosis. For patients with HFrEF and wide QRS, cardiac resynchronization therapy (CRT) is an effective option to address electromechanical dyssynchrony. However, approximately 30% of patients do not respond positively to CRT, highlighting the need to refine candidate selection for this treatment. In some patients with reduced HFrEF, there is a condition known as classical low-flow, low-gradient aortic stenosis (AS) that may be observed. This condition is characterized by a low transaortic flow, which leads to reductions in both the transaortic mean gradient and aortic valve area. Decision-making regarding revascularization, CRT, and pharmacological treatment play a crucial role in managing HFrEF. Cardiac imaging can be valuable in guiding decision-making processes and assessing the prognosis of patients with HFrEF. Among the imaging modalities, dobutamine stress echocardiography has come a long way in establishing itself as a feasible, safe, effective, relatively cheap non-invasive technique. The aim of this review is to explore the current literature on the utility of low-dose stress echocardiography in diagnosing and prognosticating patients with HFrEF.