Depression and cardiovascular disease (CVD) frequently co-occur and contribute substantially to global morbidity and mortality. This narrative review synthesizes current evidence on the biological, psychological, and clinical mechanisms connecting these two conditions. The aim is to clarify the key pathways underlying their bidirectional relationship and to highlight therapeutic strategies that may improve outcomes in individuals affected by both disorders. Recent studies increasingly demonstrate that depression and CVD share multifaceted biological mechanisms, including hypothalamic–pituitary–adrenal axis dysregulation, systemic inflammation, autonomic imbalance, oxidative stress, endothelial dysfunction, and genetic and epigenetic alterations. Immunological activity, particularly cytokine-mediated neuroinflammation, has emerged as a central component linking mood dysregulation with vascular pathology. Behavioral and psychosocial pathways also contribute to cardiovascular risk. Adverse health behaviors, including physical inactivity, poor diet, smoking, substance use, sleep disturbance, and treatment nonadherence, may directly contribute to cardiovascular risk, while psychosocial factors such as chronic stress and social isolation may influence or amplify these behavioral and biological pathways. Additionally, precision-medicine strategies that incorporate genetic, metabolic, and psychosocial profiles are increasingly recognized as important for optimizing individualized care. Depression and CVD are interconnected through a complex web of biological and psychosocial pathways that mutually reinforce disease progression. Understanding these shared mechanisms is critical for improving prevention, diagnosis, and treatment. Integrated, multidisciplinary management, addressing inflammation, autonomic dysfunction, lifestyle factors, and mental health, is essential to reduce morbidity in this high-risk population. Future research should continue exploring biomarkers and personalized interventions to better manage this intertwined comorbidity.
Recently approved by the United States Food and Drug Administration, 18F-flurpiridaz for positron emission tomography (PET) myocardial perfusion imaging (MPI) enables high-quality assessment of myocardial blood flow (MBF). Its half-life of approximately 110 min supports regional distribution and allows unit-dose delivery. These features make this probe well suited for MBF quantitation and expand access to quantitative cardiac PET at smaller centers. During pharmacologic stress, absolute MBF and myocardial flow reserve provide incremental diagnostic information beyond relative perfusion imaging. These measures have been validated across multiple methods and software platforms. Further study of this tracer under peak exercise may provide clinically relevant assessment of myocardial demand-induced changes in flow. Potential investigational approaches include artificial intelligence (AI)-derived virtual MBF, exercise-adjusted standardized uptake value (SUV) ratio-derived myocardial flow reserve (MFR) surrogate, and direct kinetic modeling during in-scanner ergometry. While conceptually promising, limitations inherent to exercise-based approaches in stress MBF and/or MFR estimation highlight the need for pragmatic research strategies before potential clinical applicability.
This review aims to evaluate the contemporary and evolving role of cardiac magnetic resonance (CMR) imaging in arrhythmic risk stratification for patients with non-ischaemic cardiomyopathy, specifically focussing on dilated cardiomyopathy (DCM) and non-dilated left ventricular cardiomyopathy (NDLVC). This review synthesises current data on late gadolinium enhancement (LGE), parametric mapping, strain imaging and artificial intelligence (AI), and contextualises these among emerging genetic risk stratification approaches. Left ventricular ejection fraction has been the cornerstone for guideline-based arrhythmic risk stratification in patients with DCM, despite limited precision. Observational data and meta-analyses have established the presence of replacement fibrosis through LGE-CMR as a powerful independent predictor of ventricular arrhythmias (VAs) and sudden cardiac death. Crucially, the absence of LGE identifies a low-risk cohort. Much recent focus has been on understanding whether more precise characterisation of scar can further enhance arrhythmic risk stratification, for example through scar quantification. Although data exists supporting a potential role for T1 mapping for arrhythmic risk prediction in this cohort, further research is required to support its widespread adoption. Emerging multimodal approaches using artificial intelligence and personalised computational “digital twins” are areas of important interest, offering scope for integration of imaging, electrocardiographic and genomic data layers. Arrhythmic risk stratification in non-ischaemic cardiomyopathies remains challenging despite significant advances. Progressive refinement in precision has accompanied a shift from a restrictive, functional assessment towards an integrated, substrate-driven precision model. CMR represents the cornerstone of this evolution.
Fixed-dose combination therapy (the polypill) was developed to reduce treatment complexity and improve adherence to evidence-based cardiovascular therapies. This review evaluates contemporary evidence for its effects on major cardiovascular events and cardiovascular mortality across primary prevention, secondary prevention, and emerging heart failure applications, while addressing implementation barriers and remaining evidence gaps. Early pharmacodynamic and adherence trials established that co-formulation preserves the effects of individual components and improves medication adherence. Event-powered trials subsequently demonstrated clinical benefit: PolyIran and TIPS-3 reduced major cardiovascular events in predominantly primary prevention population, whereas SECURE reduced recurrent events after myocardial infarction. Individual-participant and aggregate-data meta-analyses showed relative reductions of approximately 20
Periodontal disease has been increasingly recognized as a chronic inflammatory condition with potential systemic implications, particularly in the cardiovascular system. Heart failure (HF), a pro-inflammatory syndrome with multisystem involvement, remains a major public health burden. This state-of-the-art narrative review aims to analyze the current scientific evidence on the association between periodontal disease and heart failure, emphasizing epidemiological data, cardiac biomarkers, inflammatory mediators, and future perspectives. Current evidence indicates a high prevalence of periodontal disease among patients with HF and suggests associations between periodontal disease and elevated cardiac biomarkers, including NT-proBNP and troponin T, as well as systemic inflammatory mediators such as C-reactive protein, IL-6, and TNF-α. Interventional studies have reported reductions in some of these biomarkers following periodontal treatment, suggesting a potential biological link between periodontal inflammation and HF. However, findings remain heterogeneous, and some studies have failed to demonstrate significant associations. Current evidence supports an association between periodontal disease and heart failure, with systemic inflammation representing a potential biological link. Nevertheless, the heterogeneity of study designs, small sample sizes, and predominance of observational and cross-sectional evidence limit causal inference. Longitudinal studies and randomized clinical trials are needed to clarify causal mechanisms and determine whether periodontal prevention and treatment can contribute to integrated strategies for patients with HF.
