Search Results (1,116)

Background/Objectives: Chronological age (CA) is commonly used in clinical decision-making, yet it may not accurately reflect biological aging. Recent advances in artificial intelligence (AI) allow estimation of electrocardiogram (ECG)-derived heart age, which may serve as a non-invasive biomarker for physiological aging. This study aimed to develop and validate a deep learning model to predict ECG-heart age in individuals with no structural heart disease. Methods: We trained a convolutional neural network (DenseNet-121) using 12-lead ECGs from 292,484 individuals (mean age: 51.4 ± 13.8 years; 42.3% male) without significant cardiac disease. Exclusion criteria included missing age data, age <18 or >90 years, and structural abnormalities. CA was used as the target variable. Model performance was evaluated using the coefficient of determination (R²), Pearson correlation coefficient (PCC), mean absolute error (MAE), and root mean square error (RMSE). External validation was conducted using 1191 independent ECGs. Results: The model demonstrated strong predictive performance (R² = 0.783, PCC = 0.885, MAE = 5.023 years, RMSE = 6.389 years). ECG-heart age tended to be overestimated in younger adults (≤30 years) and underestimated in older adults (≥70 years). External validation showed consistent performance (R² = 0.703, PCC = 0.846, MAE = 5.582 years, RMSE = 7.316 years). Conclusions: The proposed AI-based model accurately estimates ECG-heart age in individuals with structurally normal hearts. ECG-derived heart age may serve as a reliable biomarker of biological aging and support future risk stratification strategies. Full article

Ventricular tachycardia (VT) remains a major cause of morbidity and mortality in patients with structural heart disease. While catheter ablation has become a cornerstone in VT management, recurrence rates remain substantial due to limitations in electroanatomic mapping (EAM), particularly in cases of deep or heterogeneous arrhythmogenic substrates. Cardiac imaging, especially when multimodal and integrated with mapping systems, has emerged as a critical adjunct to enhance procedural efficacy, safety, and individualized strategy. This comprehensive review explores the evolving role of various imaging modalities, including echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), positron emission tomography (PET), and intracardiac echocardiography (ICE), in the preprocedural and intraprocedural phases of VT ablation. We highlight their respective strengths in substrate identification, anatomical delineation, and real-time guidance. While limitations persist, including costs, availability, artifacts in device carriers, and lack of standardization, future advances are likely to redefine procedural workflows. Full article

Heart failure (HF) is a major global health challenge, characterized by high morbidity, mortality, and frequent hospital readmissions. Despite the advent of guideline-directed medical therapies (GDMTs), the burden of HF continues to grow, necessitating a shift toward comprehensive, multidisciplinary care models. Heart Failure Disease Management Programs (HF-DMPs) have emerged as structured frameworks that integrate evidence-based medical therapy, patient education, telemonitoring, and support for social determinants of health to optimize outcomes and reduce healthcare costs. This review outlines the key components of HF-DMPs, including patient identification and risk stratification, pharmacologic optimization, team-based care, transitional follow-up, remote monitoring, performance metrics, and social support systems. Incorporating tools such as artificial intelligence, pharmacist-led titration, and community health worker support, HF-DMPs represent a scalable approach to improving care delivery. The success of these programs depends on tailored interventions, interdisciplinary collaboration, and health equity-driven strategies. Full article

The pivotal role of angiotensin II (AngII) in cardiovascular disease has been firmly established, as evidenced by a robust body of literature and the broad clinical application of AngII-inhibiting therapies. AngII type 1 receptor is the primary mediator of AngII action, and its activation initiates a multitude of cellular responses that contribute to the development of hypertension, structural changes in the heart and vasculature, and damage to target organs. This review examines AngII from a different perspective, exploring the link between the renin–angiotensin–aldosterone system and cardiovascular risk beyond hypertension, with particular emphasis on atherosclerosis development and progression. Full article

Introduction and Objectives: Risk-sharing agreements (RSAs) have emerged as a key strategy for financing high-cost medical technologies while ensuring financial sustainability. These payment mechanisms mitigate clinical and financial uncertainties, optimizing pricing and reimbursement decisions. Despite their widespread adoption globally, Latin America has reported limited implementation, particularly for high-cost medical devices. This study aims to share insights from designing RSAs in the form of Outcome Protection Programs (OPPs) for medical devices in Latin America from the perspective of a medical devices company. Methods: The report follows a structured approach, defining key OPP dimensions: payment base, access criteria, pricing schemes, risk assessment, and performance incentives. Risks were categorized as financial, clinical, and operational. The framework applied principles from prior models, emphasizing negotiation, program design, implementation, and evaluation. A multidisciplinary task force analyzed patient needs, provider motivations, and payer constraints to ensure alignment with health system priorities. Results: Over two semesters, a panel of seven experts from the manufacturer designed n = 105 innovative payment programs implemented in Argentina (n = 7), Brazil (n = 7), Colombia (n = 75), Mexico (n = 9), Panama (n = 4), and Puerto Rico (n = 3). The programs targeted eight high-burden conditions, including Coronary Artery Disease, atrial fibrillation, Heart Failure, and post-implantation arrhythmias, among others. Private providers accounted for 80% of experiences. Challenges include clinical inertia and operational complexities, necessitating structured training and monitoring mechanisms. Conclusions: Outcome Protection Programs offer a viable and practical risk-sharing approach to financing high-cost medical devices in Latin America. Their implementation requires careful stakeholder alignment, clear eligibility criteria and endpoints, and robust monitoring frameworks. These findings contribute to the ongoing dialogue on sustainable healthcare financing, emphasizing the need for tailored approaches in resource-constrained settings. Full article

Cardiovascular disease encompasses a wide group of conditions that affect the heart and blood vessels. Of these diseases, cardiomyopathies and arrhythmias specifically have been well-studied in their relationship to cardiac dyads, nanoscopic structures that connect electrical signals to muscle contraction. The proper development and positioning of dyads is essential in excitation–contraction (EC) coupling and, thus, beating of the heart. Three proteins, namely CMYA5, JPH2, and BIN1, are responsible for maintaining the dyadic cleft between the T-tubule and junctional sarcoplasmic reticulum (jSR). Various other dyadic proteins play integral roles in the primary function of the dyad—translating a propagating action potential (AP) into a myocardial contraction. Ca²⁺, a secondary messenger in this process, acts as an allosteric activator of the sarcomere, and its cytoplasmic concentration is regulated by the dyad. Loss-of-function mutations have been shown to result in cardiomyopathies and arrhythmias. Adeno-associated virus (AAV) gene therapy with dyad components can rescue dyadic dysfunction, which results in cardiomyopathies and arrhythmias. Overall, the dyad and its components serve as essential mediators of calcium homeostasis and excitation–contraction coupling in the mammalian heart and, when dysfunctional, result in significant cardiac dysfunction, arrhythmias, morbidity, and mortality. Full article

Pathologies of the heart (e.g., ischemic disease, valve fibrosis and calcification, progressive myocardial fibrosis, heart failure, and arrhythmogenic disorders) stem from the irreversible deterioration of cardiac tissues, leading to severe clinical consequences. The limited regenerative capacity of the adult myocardium and the architectural complexity of the heart present major challenges for tissue engineering. However, recent advances in biomaterials and biofabrication techniques have opened new avenues for recreating functional cardiac tissues. Particularly relevant in this context is the integration of biomimetic design principles, such as structural anisotropy, mechanical and electrical responsiveness, and tissue-specific composition, into 3D bioprinting platforms. This review aims to provide a comprehensive overview of current approaches in cardiac bioprinting, with a focus on how structural and functional biomimicry can be achieved using advanced hydrogels, bioprinting techniques, and post-fabrication stimulation. By critically evaluating materials, methods, and applications such as patches, vasculature, valves, and chamber models, we define the state of the art and highlight opportunities for developing next-generation bioengineered cardiac constructs. Full article

Cardiac devices have transformed the management of heart failure, ventricular arrhythmias, ischemic cardiomyopathy, and valvular heart disease. Technologies such as cardiac resynchronization therapy (CRT), conduction system pacing, left ventricular assist devices (LVADs), and implantable cardioverter-defibrillators have contributed to abated global cardiovascular risk through action onto pathophysiological processes such as mechanical unloading, electrical resynchronization, or hemodynamic optimization, respectively. While their clinical benefits are well established, their long-term molecular and structural effects on the myocardium remain under investigation. Cardiac devices dynamically interact with myocardial and vascular biology, inducing molecular and extracellular matrix adaptations that vary by pathology. CRT enhances calcium cycling and reduces fibrosis, but chronic pacing may lead to pacing-induced cardiomyopathy. LVADs and Impella relieve ventricular workload yet alter sarcomeric integrity and mitochondrial function. Transcatheter valve therapies influence ventricular remodeling, conduction, and coronary flow. Understanding these remodeling processes is crucial for optimizing patient selection, device programming, and therapeutic strategies. This narrative review integrates the current knowledge on the molecular and structural effects of cardiac devices, highlighting their impact across different disease settings. Full article

Accurate segmentation of cardiac MR images using deep neural networks is crucial for cardiac disease diagnosis and treatment planning, as it provides quantitative insights into heart anatomy and function. However, achieving high segmentation accuracy relies heavily on extensive, precisely annotated datasets, which are costly and time-consuming to obtain. This study addresses this challenge by proposing a novel data augmentation framework based on a condition-guided diffusion generative model, controlled by multiple cardiac labels. The framework aims to expand annotated cardiac MR datasets and significantly improve the performance of downstream cardiac segmentation tasks. The proposed generative data augmentation framework operates in two stages. First, a Label Diffusion Module is trained to unconditionally generate realistic multi-category spatial masks (encompassing regions such as the left ventricle, interventricular septum, and right ventricle) conforming to anatomical prior probabilities derived from noise. Second, cardiac MR images are generated conditioned on these semantic masks, ensuring a precise one-to-one mapping between synthetic labels and images through the integration of a spatially-adaptive normalization (SPADE) module for structural constraint during conditional model training. The effectiveness of this augmentation strategy is demonstrated using the U-Net model for segmentation on the enhanced 2D cardiac image dataset derived from the M&M Challenge. Results indicate that the proposed method effectively increases dataset sample numbers and significantly improves cardiac segmentation accuracy, achieving a 5% to 10% higher Dice Similarity Coefficient (DSC) compared to traditional data augmentation methods. Experiments further reveal a strong correlation between image generation quality and augmentation effectiveness. This framework offers a robust solution for data scarcity in cardiac image analysis, directly benefiting clinical applications. Full article

Background/Objectives: Heart rate variability (HRV) has been widely investigated as a predictor of disease and mortality across diverse patient populations; however, there remains no consensus on the optimal set or combination of time and frequency domain nor on nonlinear features for reliable prediction across clinical contexts. Given the relevance of the COVID-19 pandemic and the unique clinical profiles of these patients, this retrospective observational study explored the potential of HRV analysis for early prediction of in-hospital mortality using ECG signals recorded during the initial moments of ICU admission in COVID-19 patients. Methods: HRV indices were extracted from four ECG leads (I, II, III, and aVF) using sliding windows of 2, 5, and 7 min across observation intervals of 15, 30, and 60 min. The raw data posed significant challenges in terms of structure, synchronization, and signal quality; thus, from an original set of 381 records from 321 patients, after data pre-processing steps, a final dataset of 82 patients was selected for analysis. To manage data complexity and evaluate predictive performance, two feature selection methods, four feature reduction techniques, and five classification models were applied to identify the optimal approach. Results: Among the feature aggregation methods, compiling feature means across patient windows (Method D) yielded the best results, particularly for longer observation intervals (e.g., using LDA, the best AUC of $0.82\pm 0.13$ was obtained with Method D versus $0.63\pm 0.09$ with Method C using 5 min windows). Linear Discriminant Analysis (LDA) was the most consistent classification algorithm, demonstrating robust performance across various time windows and further improvement with dimensionality reduction. Although Gradient Boosting and Random Forest also achieved high AUCs and F1-scores, their performance outcomes varied across time intervals. Conclusions: These findings support the feasibility and clinical relevance of using short-term HRV as a noninvasive, data-driven tool for early risk stratification in critical care, potentially guiding timely therapeutic decisions in high-risk ICU patients and thereby reducing in-hospital mortality. Full article

Background and Objectives: Cardiac transplantation is currently the elective treatment choice in end-stage heart failure, and cellular rejection is a predictive factor for morbidity and mortality after surgery. We proposed an evaluation of the clinicopathologic factors involved in the mechanism of rejection. Materials and Methods: This study included 146 patients who underwent transplantation at the Institute of Cardiovascular Diseases and Transplantation in Targu Mures between 2010 and 2023, and we evaluated the function and structure of the myocardium after surgery by using endomyocardial biopsy. Results: Overall, 120 men and 26 women underwent transplantation, with an approximately equal proportion under and over 40 years old (48.6% and 51.4%). Evaluating the degree of acute cellular rejection according to the International Society for Heart and Lung Transplantation classification showed that most of the patients presented with acute cellular rejection (ACR) and antibody-mediated rejection (AMR) grade 0, and most cases of ACR and AMR were reported with mild changes (13% or 10.3% patients). Therefore, the most frequent histopathologic diagnoses were similar to lesions unrelated to rejection (45.2% of patients) and ischemia–reperfusion lesions (25.3% patients), respectively. Conclusions: Although 82.2% of the transplanted cases showed no rejection (ISHLT score 0), non-rejection-related lesion-like changes were present in 45.2% of cases, and because more of the non-rejection-related criteria could be detected, it may be necessary to adjust the grading of the rejection criteria. The histopathologic changes that characterize rejection are primarily represented by the mononuclear inflammatory infiltrate; in our study, inflammatory changes were mostly mild (71.9%), with myocyte involvement in all cases. These changes are associated with and contribute to the maintenance of the rejection phenomenon. Full article

Inflammatory bowel disease (IBD), encompassing Crohn’s disease and ulcerative colitis, is increasingly recognized as a systemic condition with cardiovascular implications. Among these, heart failure has emerged as a significant complication. The aim of this narrative review was to explore the cellular and molecular pathways that link IBD and heart failure. Drawing upon findings from epidemiologic studies, experimental models, and clinical research, we examined the pathways through which IBD may promote cardiac dysfunction. Chronic systemic inflammation in IBD, driven by cytokines such as TNF-α and IL-1β, can impair myocardial structure and function. Furthermore, intestinal barrier dysfunction and gut dysbiosis can facilitate the translocation of proinflammatory microbial metabolites, including lipopolysaccharide and phenylacetylglutamine, and deplete cardioprotective metabolites like short-chain fatty acids, thereby exacerbating heart failure risk. Additional contributing factors include endothelial and microvascular dysfunction, autonomic dysregulation, nutritional deficiencies, shared genetic susceptibility, and adverse pharmacologic effects. IBD contributes to heart failure pathogenesis through multifactorial and interrelated mechanisms. Recognizing the role of the gut–heart axis in IBD is crucial for the early identification of cardiovascular risk, providing guidance for integrating care and developing targeted therapies to reduce the risk of heart failure in this vulnerable population. Full article

Background and Objectives: Congenital heart defects (CHD) affect around 1% of the population, making them the most common congenital disease worldwide. Thanks to advances in treatment, over 90% of affected children are able to reach adulthood, shifting focus to long-term outcomes such as disease-specific quality of life (DsQoL). To date, there has been no validated, standardized instrument for assessing DsQoL in young German CHD patients. This study introduces the Congenital Heart Disease Specific Inventory (CHDSI), the first freely available German-language instrument for measuring DsQoL in children and adolescents with CHD. Materials and Methods: The CHDSI was developed at the German Heart Center Munich in collaboration with affected children and adolescents and validated nationwide via the National Register for Congenital Heart Defects (NRCHD) with 1201 participants (46 kindergarten children, 530 children, 625 adolescents). Two age-specific versions (36/37 items) and a 31-item preschool version were created, alongside a 6-item short form (CHDSI-SF) for rapid screening. Reliability was assessed using Cronbach’s alpha and split-half methods; construct validity via confirmatory factor analysis (CFA) using DWLS; and score interpretation through standardized stanine scales. The small sample size of kindergarten children precluded a model test for this group. The standard values given for this subsample should therefore be interpreted with caution. Results: The CHDSI showed excellent internal consistency (Cronbach’s α = 0.856 to 0.900) and high split-half reliability (>0.95). CFA confirmed a robust six-factor structure with excellent model fit (CFI and TLI ≥ 0.991, RMSEA ≤ 0.05). Subscales showed strong discriminant validity, and significant differences were found by CHD severity and sex. Conclusions: The CHDSI is a psychometrically valid, age-appropriate, and freely available instrument for assessing DsQoL in children and adolescents with CHD. It provides valuable support for clinical decision-making and research. Further studies should explore international validation and cultural adaptation. Full article

Hypertensive left ventricular hypertrophy (LVH) is an ominous cardiovascular sequel to chronic hypertension, marked by structural and functional alterations in the heart. Identified as a significant risk factor for adverse cardiovascular outcomes, LVH is typically detected through echocardiography and is characterized by pathological thickening of the left ventricular wall. This hypertrophy results from chronic pressure overload (increased afterload), leading to concentric remodelling, or from increased diastolic filling (preload), contributing to eccentric changes. Apoptosis, a regulated process of cell death, plays a critical role in the pathogenesis of LVH by contributing to cardiomyocyte loss and subsequent cardiac dysfunction. Given the substantial clinical implications of LVH for cardiovascular health, this review critically examines the role of cardiomyocyte apoptosis in its disease progression, evaluates the impact of pharmacological interventions, and highlights the necessity of a comprehensive, multifaceted treatment approach for the prevention and management of hypertensive LVH. Finally, we address the health disparities associated with LVH, with particular attention to the disproportionate burden faced by African Americans and other Black communities, as this remains a key priority in advancing equity in cardiovascular care. Full article

Background: Cardiovascular diseases are the leading cause of global mortality, with 80% of coronary heart disease in patients over 65. Understanding aging cardiovascular structures is crucial. Photon-counting computed tomography (PCCT) offers improved spatial and temporal resolution and better signal-to-noise ratio, enabling texture analysis in clinical routines. Detecting structural changes in aging left-ventricular myocardium may help predict cardiovascular risk. Methods: In this retrospective, single-center, IRB-approved study, 90 patients underwent ECG-gated contrast-enhanced cardiac CT using dual-source PCCT (NAEOTOM Alpha, Siemens). Patients were divided into two age groups (50–60 years and 70–80 years). The left ventricular myocardium was segmented semi-automatically, and radiomics features were extracted using pyradiomics to compare myocardial texture features. Epicardial adipose tissue (EAT) density, thickness, and other clinical parameters were recorded. Statistical analysis was conducted with R and a Python-based random forest classifier. Results: The study assessed 90 patients (50–60 years, n = 54, and 70–80 years, n = 36) with a mean age of 63.6 years. No significant differences were found in mean Agatston score, gender distribution, or conditions like hypertension, diabetes, hypercholesterolemia, or nicotine abuse. EAT measurements showed no significant differences. The Random Forest Classifier achieved a training accuracy of 0.95 and a test accuracy of 0.74 for age group differentiation. Wavelet-HLH_glszm_GrayLevelNonUniformity was a key differentiator. Conclusions: Radiomics texture features of the left ventricular myocardium outperformed conventional parameters like EAT density and thickness in differentiating age groups, offering a potential imaging biomarker for myocardial aging. Radiomics analysis of left ventricular myocardium offers a unique opportunity to visualize changes in myocardial texture during aging and could serve as a cardiac risk predictor. Full article