Search Results (580)

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

Left ventricular systolic dysfunction (LVSD) is associated with increased mortality and is sometimes reversible when found early. Artificial intelligence (AI)-enabled electrocardiogram (ECG) has emerged as an efficient screening tool for LVSD, but has not been validated in left bundle branch block (LBBB) patients. The clinical significance of developing an AI prediction model for LBBB patients lies in the fact that LBBB can be a cause, consequence, or both of LVSD. This pilot study was designed to develop an AI model for LVSD detection in the LBBB population using a limited dataset. ECG data from 508 patients with sinus rhythm and LBBB were labeled based on an LVSD threshold of 35%. To enhance the performance of a model derived from such a small and skewed dataset, we combined an autoencoder-based anomaly detection model with a convolutional neural network (CNN). We used a lead-wise ensemble technique for the final classification. Experimental results showed an accuracy of 0.81, precision of 0.87, recall of 0.56, and an area under the receiver operating characteristic curve of 0.75 in LVSD prediction among LBBB patients. Despite the limited dataset size, our study findings suggest the potential of deep learning techniques in detecting LVSD in patients with LBBB. Full article

Primary aldosteronism (PA), the most common cause of secondary hypertension, is increasingly recognized as an independent driver of adverse cardiac remodeling, mediated through mechanisms beyond elevated blood pressure alone. Chronic aldosterone excess leads to myocardial fibrosis, left ventricular hypertrophy, and diastolic dysfunction via mineralocorticoid receptor activation, oxidative stress, inflammation, and extracellular matrix dysregulation. These changes culminate in a distinct cardiomyopathy phenotype, often underrecognized in early stages. Multimodality cardiac imaging, led primarily by conventional and speckle-tracking echocardiography, and complemented by exploratory cardiac magnetic resonance (CMR) techniques such as T1 mapping and late gadolinium enhancement, enables non-invasive assessment of structural, functional, and tissue-level changes in aldosterone-mediated myocardial damage. While numerous studies have established the diagnostic and prognostic relevance of imaging in PA, several gaps remain. Specifically, the relative sensitivity of different modalities in detecting subclinical myocardial changes, the long-term prognostic significance of imaging biomarkers, and the differential impact of adrenalectomy versus medical therapy on cardiac reverse remodeling require further clarification. Moreover, the lack of standardized imaging-based criteria for defining and monitoring PA-related cardiomyopathy hinders widespread clinical implementation. This narrative review aims to synthesize current knowledge on the pathophysiological mechanisms of aldosterone-induced cardiac remodeling, delineate the strengths and limitations of existing imaging modalities, and critically evaluate the comparative effects of surgical and pharmacologic interventions. Emphasis is placed on early detection strategies, identification of imaging biomarkers with prognostic utility, and integration of multimodal imaging into clinical decision-making pathways. By outlining current evidence and highlighting key unmet needs, this review provides a framework for future research aimed at advancing personalized care and improving cardiovascular outcomes in patients with PA. Full article

Right ventricular apex (RVA) pacing has historically been the default approach for cardiac pacing; however, it is associated with the development of progressive left ventricular dysfunction and heart failure (HF), particularly in patients with high pacing burdens. While advances in device programming and modern algorithms have sought to mitigate these effects, preserving physiological activation has proven to be more critical than reducing ventricular pacing. Conduction system pacing (CSP) techniques—namely, His-bundle pacing (HBP) and particularly left bundle branch area pacing (LBBAP)—have emerged as superior alternatives, enabling improved left ventricular function and reduced rates of pacing-induced cardiomyopathy (PICM). Nevertheless, despite the clinical advantages of these procedures over RVA, they face limitations including variable implantation success rates, increased pacing thresholds and lead revision rates, technical challenges, and occasional procedure prolongation. Thus, while CSP approaches represent the future of physiological pacing, RVA pacing continues to provide a necessary and reliable option in the current clinical practice. Full article

Background and Objectives: Despite significant advances in surgical techniques and perioperative care, major adverse cardiovascular events (MACE) remain a leading cause of postoperative morbidity and mortality in patients undergoing coronary artery bypass grafting and/or aortic valve replacement. Accurate preoperative risk stratification is essential yet often limited by models that overlook atrial mechanics and underutilized biomarkers. Materials and Methods: This study aimed to develop an interpretable machine learning model for predicting perioperative MACE by integrating clinical, biochemical, and echocardiographic features, with a particular focus on novel physiological markers. A retrospective cohort of 131 patients was analyzed. An Extreme Gradient Boosting (XGBoost) classifier was trained on a comprehensive feature set, and SHapley Additive exPlanations (SHAPs) were used to quantify each variable’s contribution to model predictions. Results: In a stratified 80:20 train–test split, the model initially achieved an AUC of 1.00. Acknowledging the potential for overfitting in small datasets, additional validation was performed using 10 independent random splits and 5-fold cross-validation. These analyses yielded an average AUC of 0.846 ± 0.092 and an F1-score of 0.807 ± 0.096, supporting the model’s stability and generalizability. The most influential predictors included total atrial conduction time, mitral and tricuspid annular orifice areas, and high-density lipoprotein (HDL) cholesterol. These variables, spanning electrophysiological, structural, and metabolic domains, significantly enhanced discriminative performance, even in patients with preserved left ventricular function. The model’s transparency provides clinically intuitive insights into individual risk profiles, emphasizing the significance of non-traditional parameters in perioperative assessments. Conclusions: This study demonstrates the feasibility and potential clinical value of combining advanced echocardiographic, biochemical, and machine learning tools for individualized cardiovascular risk prediction. While promising, these findings require prospective validation in larger, multicenter cohorts before being integrated into routine clinical decision-making. Full article

Background/Objectives: Heart failure (HF) is a growing global health burden, yet early detection remains challenging due to the limitations of traditional diagnostic tools such as electrocardiograms (ECGs). Recent advances in deep learning offer new opportunities to identify left ventricular systolic dysfunction (LVSD), a key indicator of HF, from ECG data. This study validates AiTiALVSD, our previously developed artificial intelligence (AI)-enabled ECG Software as a Medical Device, for its accuracy, transparency, and robustness in detecting LVSD. Methods: This retrospective single-center cohort study involved patients suspected of LVSD. The AiTiALVSD model, based on a deep learning algorithm, was evaluated against echocardiographic ejection fraction values. To enhance model transparency, the study employed Testing with Concept Activation Vectors (TCAV), clustering analysis, and robustness testing against ECG noise and lead reversals. Results: The study involved 688 participants and found AiTiALVSD to have a high diagnostic performance, with an AUROC of 0.919. There was a significant correlation between AiTiALVSD scores and left ventricular ejection fraction values, confirming the model’s predictive accuracy. TCAV analysis showed the model’s alignment with medical knowledge, establishing its clinical plausibility. Despite its robustness to ECG artifacts, there was a noted decrease in specificity in the presence of ECG noise. Conclusions: AiTiALVSD’s high diagnostic accuracy, transparency, and resilience to common ECG discrepancies underscore its potential for early LVSD detection in clinical settings. This study highlights the importance of transparency and robustness in AI-ECG, setting a new benchmark in cardiac care. Full article

Heart failure (HF) is a well-known leading cause of mortality, associated with a high symptom burden in advanced stages, frequent hospitalizations, and increasing economic costs. HF is typically classified into three main subgroups, based on left ventricular ejection fraction (LVEF): HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF), and HF with preserved ejection fraction (HFpEF). Recently, two additional subgroups have been proposed: HF with improved ejection fraction (HFimpEF) and HF with supernormal ejection fraction (HFsnEF). These five phenotypes exhibit distinct risk factors, clinical presentations, therapeutic responses, and prognosis. However, the LVEF thresholds used to define these subgroups remain a subject of considerable debate, with significant differences in opinions among leading experts. A major criticism concerns the reliability of LVEF in accurately classifying HF subgroups. Due to substantial intra and interobserver variability, determining the appropriate therapy and prognosis can be challenging, particularly in patients with HFmrEF. Additionally, patients classified under HFpEF are often too heterogeneous to be effectively managed as a single group. This narrative review explores these issues, and suggests a possible need for a new approach to HF classification, one that involves revising the LVEF reference values for HF phenotypes and highlighting LVEF trajectories rather than relying on a single measurement. Moreover, in light of the relatively limited therapeutic options for patients with LVEF > 40%, a new, simplified classification may be proposed: HF with reduced EF (LVEF ≤ 40%), HF with below-normal EF (41% ≤ LVEF ≤ 55%), and HF with normal EF (LVEF > 55%). This mindset would better equip clinical cardiologists to manage the diverse spectrum of HF syndromes, always with the patient at the center. Full article

Background: The Da Silva Cone procedure for Ebstein anomaly has dramatically improved tricuspid valve competence and clinical outcomes. However, preoperative left ventricular (LV) dysfunction and immediate postoperative right ventricular (RV) systolic dysfunction are frequently observed. While excellent valve outcomes are well established, recovery of biventricular function following the Cone remains less defined. This study aimed to evaluate longitudinal changes in RV and LV function postoperatively and over a minimum of six months post-Cone operation. Methods: A single center retrospective review of 134 patients who underwent Cone repair for Ebstein’s anomaly from 2016 to 2024 was performed. Echocardiograms were analyzed at three time points: preoperative (Time 1), hospital discharge (Time 2), and ≥6 months postoperative (Time 3). RV parameters included fractional area change (FAC), tricuspid annular plane systolic excursion (TAPSE), and tricuspid S′. LV parameters included left ventricular ejection fraction (LVEF), end-diastolic volume indexed to body surface area (LVEDVi), left ventricular stroke volume (LVSVi), and mitral E/E′. Subgroup analyses examined outcomes by prior Glenn, Starnes procedure, and degree of RV dilation. Paired two sample t-tests were used to compare serial measures. Results: Median age at surgery was 7.8 years (IQR: 2.3–17.7). All patients had discharge echocardiograms; 70 had follow-up studies at ≥6 months. RV function declined postoperatively with reductions in FAC (35% to 21%), TAPSE (2.0 to 0.8 cm), and S′ (13 to 5 cm/s), all p < 0.001. By Time 3, these measures improved (FAC to 29%, TAPSE to 1.3 cm, S′ to 7 cm/s) but did not fully return to baseline. LVEDVi and LVSVi increased significantly by Time 3 (LVEDVi: 47 to 54 mL/m²; LVSVi: 30 to 34 mL/m²; p < 0.001), while LVEF remained unchanged. Patients with prior Glenn or Starnes had greater Time 1 LV volumes and lower RV function, but by Time 3, most differences resolved. Moderate–severe preoperative RV dilation was associated with worse RV function at Time 2 and normalized by Time 3. Conclusions: The Da Silva Cone procedure leads to early postoperative RV dysfunction with partial recovery over the mid-term follow-up. Concurrently, LV filling and stroke volume improve, reflecting favorable interventricular interaction. These findings support echocardiographic surveillance to guide functional recovery post-Cone and inform patient counseling. Full article

Background/Objectives: Anatomical and functional damage of the mitral valve (MV) apparatus in patients with dilated cardiomyopathy (DCM) is secondary to left ventricular (LV) injury, leading to functional mitral regurgitation (FMR). Real-time four-dimensional echocardiography (RT 4DE) is a useful imaging technique in different pathologies, including DCM. Left atrial (LA) strain, as measured by left atrium quantification software, is an accurate technique for evaluating increased filling pressure. The MV has a complex three-dimensional morphology and motion. Four-dimensional echocardiography (4DE) has revolutionized clinical imaging of the mitral valve apparatus. This study aims (1) to characterize the mitral annulus (MA) parameters in patients with DCM and advanced-stage heart failure (HF) according to etiology and (2) to find correlations between left atrial function and MA remodeling in this group of patients, using 4DE quantification software. Methods: A total of 82 patients with DCM and an LV ejection fraction ≤ 40% were recruited. Conventional 2DE and RT 4DE were conducted in DCM patients with a compensated phase of HF before discharge. The measured parameters were left atrial reservoir strain (LASr), annular area (AA), annular perimeter (AP), anteroposterior diameter (A-Pd), posteromedial to anterolateral diameter (PM-ALd), commissural distance (CD), interregional distance (ITD), annular height (AH), nonplanar angle (NPA), tenting height (TH), tenting area (TA), and tenting volume (TV). Results: Measured parameters revealed more advanced damage of LA and MA parameters in ischemic compared to nonischemic etiology. Univariate analysis identified AA, AP, A-Pd, PM-ALd, CD, ITD, TH, TA, and TV (p < 0.0001) as determinants of LASr. Including these parameters in a stepwise multivariate logistic regression, PM-ALd (p = 0.03), TH (p = 0.043), and TV (p = 0.0001) were the best predictors of LAsr in these patients. Conclusions: The results of this study revealed the correlation between LA function depression and MA remodeling in patients with DCM. 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

Background: Well-designed endurance training leads to improved cardiovascular fitness and sports performance in prolonged exercise tasks, with the adaptations depending on multiple factors, including the training modality and the population in question. It is still disputable how the type of training affects myocardial remodeling, and the information on myocardial remodeling by high-intensity interval training (HIIT) is particularly scarce. Methods: The current study investigated changes in cardiac structure after volume-progressive HIIT in running mode. As part of their conditioning program, amateur athletes (mean ± SD age of 18.2 ± 1.0 years) exclusively conducted HIIT in a volume-progressive fashion over 7 weeks (a total of 21 sessions). Peak oxygen uptake as well as 200 m and 2000 m running performance were measured, and transthoracic two-dimensional echocardiography was conducted before and after the intervention. Results: Training improved running performance, increased the peak oxygen uptake and left atrium diameter (from 32.0 ± 2.5 to 33.5 ± 2.3 mm; p = 0.01), and induced ~11% thickening of the left-ventricular posterior wall (7.5 ± 0.7 to 8.2 ± 0.4 mm; p = 0.01) and interventricular septum (7.6 ± 0.7 to 8.6 ± 0.9 mm; p = 0.02), but not the dilation of left-ventricular, right-ventricular, or right atrium chambers. Conclusions: HIIT of just 127 km of running per 8.5 h during 7 weeks was sufficient to improve aerobic capacity and running performance, and induce left-ventricular wall hypertrophy and left atrium dilation, in young healthy athletes. Full article

Background/Objectives: Patients with normal sinus rhythms undergoing cardiac resynchronization therapy defibrillator (CRT-D) implantation may benefit from a novel two-lead CRT-D system (CRT-DX), which features an atrial sensing dipole integrated into the right ventricular lead. This single-arm, international, non-controlled investigation focused on the safety and clinical efficacy of CRT-DX devices in CRT-D candidates who do not require atrial pacing. Methods: Patients indicated for CRT-D implantation (resting heart rates > 40 bpm and ≥100 bpm during exercise, no second or higher-degree AV block, and no history of persistent or permanent atrial fibrillation) were enrolled across 21 sites in four European countries. The primary endpoint was the need for an additional RA lead implantation within 12 months. Secondary endpoints comprised any invasive re-intervention to the CRT-DX system or infection. Results: Among the 110 patients (mean age 62 years, 70% male), 60% had an underlying non-ischemic cardiac disease. During 12 months of follow-up, RA lead implantation was required in two patients for atrial undersensing or chronotropic incompetence (RA lead implantation-free rate: 98.2% (95% CI: 92.7–99.5%)). Atrial sensing amplitudes were stable (mean: 4.7 ± 1.7 mV), AV-synchrony was maintained at >99%, and the median percentage of biventricular pacing exceeded 98%. The left ventricular ejection fraction improved by an absolute 14.7%. Conclusions: Using simple, clinically applicable inclusion criteria, the two-lead CRT-DX system demonstrated a low rate of subsequent RA lead implantations (1.8%) and maintained adequate RA sensing amplitudes throughout the observation period. The two-lead CRT-DX concept appears to be a feasible alternative for patients with preserved chronotropic competence. Full article

Background: This study investigates the potential mechanisms behind changes in cardiac structure and function in long COVID patients. Methods: This study involved 176 consecutive outpatients in follow-up care (average age 55.9 years; 58.5% male) who experienced symptoms for over 12 weeks (average 6.2 ± 2.7 months), following coronavirus infection (COVID-19). Results: The patients with long COVID and cardiovascular manifestations were significantly more hospitalized (88.5% vs. 75.9%) and had longer hospital stays. Significant echocardiography changes were observed in the left ventricular ejection fraction (LVEF) (59.6 ± 5.4% vs. 62.5 ± 3.8%); longitudinal strain (LS) in the sub-endocardium and intra-myocardium layers (−20.9 vs. −22.0% and −18.6 vs. −19.5%); circumferential strain (CS) in the sub-epicardium layers (−9.6 vs. −10.5%); and CS post-systolic shortening (CS PSS) (0.138 vs. 0.088 s). Additionally, pathological cardiac magnetic resonance (CMR) findings were seen in 58.2% of the group of patients with long COVID and cardiovascular manifestation; 43.3% exhibited positive late gadolinium enhancement (LGE), 21.0% had elevated native T1 mapping, and 22.4% had elevated native T2 mapping. Conclusions: Most patients with long COVID showed structural and functional changes in their cardiovascular systems, primarily caused by prolonged inflammation. Using multimodality imaging is important for uncovering the mechanisms to predict chronic myocarditis, early-stage heart failure, and pre-ischemic states, which can lead to serious complications. Recognizing the specific cardiovascular phenotypes associated with long COVID is essential in order to provide timely and appropriate treatment. Full article

Background: Transthoracic echocardiography (TTE) is the primary imaging modality to assess cardiac morphology and function. In athletes, distinguishing physiological adaptations from pathological changes is essential. This study aimed to evaluate long-term cardiac structural and functional changes in professional soccer players. Methods: This retrospective study included 20 healthy male professional soccer players (mean age 21.2 ± 3.4 years) from the German first division, examined annually from 2016 to 2024 (mean follow-up 5.6 ± 2.0 years). TTE parameters associated with the “athlete’s heart” were assessed, including left ventricular end-diastolic diameter (LVEDD), interventricular septal thickness (IVSD), relative wall thickness (RWT), indexed LV mass (LVMi), and left atrial volume index (LAVi), along with 3D-derived LV and RV volumes. Advanced deformation imaging included global longitudinal strain (GLS), right ventricular strain (RVS), and left/right atrial reservoir strain (LASr and RASr, respectively). Baseline and final follow-up values were compared. Results: No significant changes were observed over time in conventional or advanced echocardiographic parameters (e.g., LVEDD: 54.5 ± 3.1 mm vs. 54.6 ± 3.9 mm; p = 0.868; GLS: −18.7% ± 2.2% vs. −18.4% ± 1.9%; p = 0.670). Ventricular volumes and strain values also remained stable throughout follow-up. Conclusions: Over a mean follow-up of more than five years, professional soccer players showed stable cardiac morphology and function without evidence of pathological remodeling. These findings support the concept that long-term high-level training in mixed-discipline sports leads to balanced, physiological cardiac adaptation. Full article