Hypertrophic cardiomyopathy (HCM) is a common inherited myocardial disorder and a leading cause of sudden cardiac death (SCD) across all age groups. Accurate risk stratification remains a clinical challenge, as conventional algorithms fail to fully capture the heterogeneous arrhythmic substrate of the disease. In recent years, cardiac imaging has emerged as a pivotal tool for refining SCD prediction by providing detailed structural, functional, and tissue-characterisation data. This review offers a comprehensive synthesis of imaging-derived predictors of SCD in HCM. We examine established echocardiographic markers, including maximal left ventricular wall thickness, left ventricular ejection fraction and left ventricular outflow tract obstruction, together with advanced cardiovascular magnetic resonance parameters such as late gadolinium enhancement and apical aneurysm detection. In addition, we discuss the emerging role of extracellular volume expansion, quantitative mapping techniques, and strain abnormalities within the framework of contemporary risk stratification models. By bridging imaging biomarkers with underlying pathophysiological mechanisms, this review highlights current evidence, limitations, and future directions to improve precision in SCD risk assessment in HCM.

Cardiometabolic diseases are strongly socially patterned, with individuals of lower socioeconomic position experiencing a disproportionate burden of metabolic disorders. Obesity has been proposed as a potential explanatory factor that may partly account for the association between social disadvantage and adverse cardiometabolic profiles. This study aimed to evaluate whether obesity may partly explain the observed associations between socioeconomic position and multiple cardiometabolic outcomes.

A cross-sectional study was conducted in 3108 working-age adults undergoing occupational health examinations in the Balearic Islands, Spain. Socioeconomic position was assessed using educational attainment and occupational category. Cardiometabolic outcomes included obesity, FLI-defined probable steatotic liver disease (FLI ≥ 60), insulin resistance, atherogenic risk, and metabolic syndrome. Multivariable logistic regression models with sequential adjustment were performed. Additional models evaluated attenuation after inclusion of obesity. Mediation analyses were conducted using bootstrapping methods.

A clear socioeconomic gradient was observed across all cardiometabolic outcomes, with higher prevalence among individuals with lower educational attainment (p for trend < 0.001). In fully adjusted models, lower educational level remained significantly associated with obesity (OR 1.61; 95% CI 1.18-2.21), whereas associations with the remaining cardiometabolic outcomes were substantially attenuated after adjustment. Inclusion of obesity reduced effect estimates for FLI-defined probable steatotic liver disease (FLI ≥ 60), insulin resistance, atherogenic risk, and metabolic syndrome by approximately 53-72%. Exploratory mediation analyses suggested that obesity was associated with approximately 28% attenuation of the association with estimated steatotic liver disease risk and 8% attenuation of the association with insulin resistance.

Socioeconomic inequalities in cardiometabolic risk were evident across multiple metabolic domains. Obesity was associated with substantial attenuation of several downstream cardiometabolic associations and may represent an important explanatory factor associated with the observed socioeconomic differences in metabolic health, particularly for estimated steatotic liver disease risk. However, the magnitude of these associations varied across outcomes, and the cross-sectional design precludes causal interpretation. These findings support the importance of addressing obesity within its broader social context as a potential strategy to reduce metabolic health inequalities among employed working-age adults.

Pectus excavatum (PEX) is the most common congenital chest wall deformity and may result in cardiac compression and arrhythmias. The relationship between structural severity and exercise-induced electrocardiographic (ECG) abnormalities in pediatric patients remains unclear.

We performed a retrospective study of patients aged 10-19 years that underwent standardized preoperative evaluation for PEX between 2015 and 2021, including ECG, transthoracic echocardiography (TTE), computed tomography (CT), and cardiopulmonary exercise testing (CPET). PEX severity was assessed using the Haller index (HI), while right ventricular (RV) compression was evaluated on CT. Tricuspid valve annular size (TVAS) on TTE was used as a surrogate marker of RV compression. Exercise-induced ECG abnormalities, including premature ventricular complexes (PVCs), were analyzed and correlated with HI, RV compression, and TVAS.

Among 124 patients (85% male; median age 15 years), 33% exhibited exercise-induced ECG abnormalities, most commonly PVCs (24% overall). PVC occurrence was not associated with Haller index severity (p = 0.35) but was significantly associated with RV compression on CT (92.6% vs. 62.1%, OR 7.64, p = 0.02). Patients with ECG abnormalities had significantly smaller TVAS compared to those without (1.98 ± 0.31 cm vs. 2.09 ± 0.33 cm, p = 0.04). Although PVCs were more frequent in patients with TVAS z-score ≤ -2.0, this did not reach statistical significance.

Exercise-induced ventricular ectopy in pediatric PEX is associated with right ventricular compression rather than structural severity as defined by HI. Echocardiographic measures such as TVAS may serve as noninvasive markers of clinically significant compression. These findings highlight the importance of cardiac-thoracic relationships in predicting arrhythmic risk and suggest a potential for reversibility with surgical correction.

Background: The Langendorff isolated heart model remains one of the most widely used experimental platforms for cardiovascular research. However, conventional bubble oxygenation is associated with several limitations, including inefficient gas utilization and incompatibility with protein-containing perfusates due to excessive foam formation. The present study evaluated whether membrane oxygenation could improve myocardial preservation and facilitate the use of a protein-enriched perfusion solution in a constant-pressure Langendorff system. Methods: A total of 48 male Wistar rats were allocated to six experimental groups (n = 8 per group). In the first experimental series, myocardial performance was compared between a conventional bubble oxygenator, a Terumo CAPIOX^® FX05 membrane oxygenator, and a Novalung iLA membrane oxygenator. In the second series, standard Krebs-Henseleit buffer was compared with a bovine serum albumin-enriched perfusate under membrane oxygenation. Hemodynamic parameters, coronary flow, and perfusate pH were assessed throughout a 180 min ischemia-reperfusion protocol. Results: Both membrane oxygenators demonstrated significantly improved myocardial preservation compared with the conventional bubble oxygenator, as evidenced by superior systolic and diastolic function, enhanced coronary flow, and improved overall cardiac performance. No significant differences were observed between the two membrane oxygenators. Membrane oxygenation additionally enabled stable supplementation of the perfusate with bovine serum albumin, which resulted in further improvements in ventricular function and coronary perfusion. Perfusate pH remained comparable among groups. Furthermore, membrane oxygenation reduced Carbozen consumption by approximately 33%, increasing the number of experiments that could be performed using a standard gas cylinder. Conclusions: The present findings suggest that membrane oxygenation may represent a simple and effective refinement of the Langendorff isolated heart model. Beyond improving myocardial preservation, it enables the use of protein-enriched perfusates and substantially reduces gas consumption. These findings support the incorporation of membrane oxygenation into modern Langendorff systems and provide a foundation for the development of more physiologically relevant isolated organ perfusion models.

Background/Objectives: This study aimed to evaluate longitudinal changes in physical and cognitive function in individuals with chronic stroke over five years and to explore factors associated with long-term outcomes. Methods: This ambispective cohort study included individuals with chronic stroke who had participated in a previous cross-sectional study conducted between 2018 and 2019. Assessments were performed at baseline and five-year follow-up (2023-2024). Primary outcomes were physical function, assessed using the six-minute walk test (6MWT), comfortable and fast gait speeds measured by the ten-meter walk test (10MWT), and cognitive function, assessed using the Mini-Mental State Examination (MMSE). Results: Thirty-two individuals participated (mean age 63.5 ± 10.3 years; median time since stroke 7.0 years). The six-minute walk distance declined by 22% (263.7 to 206.8 m, p < 0.001), whereas no significant changes were observed in gait speed or cognitive function. Age, baseline National Institutes of Health Stroke Scale (NIHSS) score, baseline values of the 6MWT and 10MWT, and nutritional status (Mini Nutritional Assessment-Short Form; MNA-SF) showed associations with physical outcomes. For cognitive outcomes, baseline NIHSS score, baseline MMSE score, MNA-SF score, and education level showed associations. However, sensitivity analyses suggested that the associations involving MNA-SF and education level were not robust. Conclusions: Physical function declines over five years in individuals with chronic stroke, highlighting the importance of long-term follow-up. While global cognition (MMSE) remained stable, domain-specific declines cannot be ruled out. Baseline stroke severity, nutritional status, and initial functional and cognitive performance may be associated with long-term outcomes.

BMI is widely used for obesity classification, yet it does not adequately reflect adiposity distribution and related metabolic risk. Normal-weight obesity (NWO), defined as excess adiposity despite normal BMI, has emerged as a clinically relevant phenotype associated with increased cardiometabolic risk. However, its prevalence and implications in young populations remain insufficiently characterized.

To evaluate the prevalence of normal-weight obesity and its association with cardiometabolic risk markers in a cohort of young adults undergoing occupational health assessments.

A cross-sectional study was conducted in 12,874 adults aged 22-30 years undergoing routine occupational health assessments. NWO was defined using a strict criterion (normal BMI with a waist-to-height ratio ≥ 0.5) and an expanded definition including additional adiposity markers derived from body fat percentage and visceral fat estimates. Anthropometric, adiposity-related, biochemical, and lifestyle data were collected using standardized protocols. Multivariable logistic regression models adjusted for age and sex were used to assess associations between NWO and cardiometabolic risk markers.

Among individuals with normal BMI (n = 9290), the prevalence of NWO was 1.79% (n = 166) using the strict definition and 2.30% (n = 214) with the expanded definition. Compared with metabolically healthy normal-weight individuals, those with NWO exhibited higher triglycerides, fasting glucose, and atherogenic lipid indices, along with lower HDL cholesterol (all p < 0.05). In multivariable analyses, NWO was independently associated with elevated triglycerides (OR 4.99; 95% CI 2.90-8.58), an unfavorable triglyceride-to-HDL ratio (OR 7.44; 95% CI 5.19-10.65), and impaired fasting glucose (OR 3.87; 95% CI 2.19-6.82). Associations were consistent across sensitivity and sex-stratified analyses.

Normal-weight obesity is present in a measurable proportion of young adults and is associated with an unfavorable cardiometabolic profile despite normal BMI. The triglyceride-to-HDL ratio was consistently associated with normal-weight obesity and showed marked differences across adiposity-defined phenotypes. These findings highlight the limitations of BMI-based classification alone and suggest that additional anthropometric and metabolic markers may help identify individuals with less favorable cardiometabolic characteristics.

Background: Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, with over 75% of deaths occurring in low- and middle-income countries, where conventional risk models often demonstrate poor calibration and limited generalizability. Objective: This study aimed to develop an interpretable, pharmacotherapy-informed machine learning model for cardiovascular risk prediction using national electronic health record (EHR) data from Jordan. Methods: A retrospective cohort study was conducted using approximately 600,000 individuals from the national Hakeem EHR system (2018-2022). Demographic, clinical, blood pressure, laboratory, and medication data were integrated to construct three datasets reflecting varying levels of feature completeness. Multiple machine learning models were benchmarked, followed by optimization, hybrid modeling, and probability calibration. Model interpretability was assessed using SHAP analysis. Results: The national cohort demonstrated a high cardiometabolic burden, with prevalence of hypertension (50.2%), hyperlipidemia (54.9%), and diabetes (47.9%). Antihypertensive and lipid-lowering therapies were more frequently used among CVD patients (56.9% and 49.6%, respectively). Treatment patterns were dominated by amlodipine (19.9%) and atorvastatin (74.4%). The final calibrated seed-bagged gradient boosting model achieved robust performance (ROC-AUC 0.844; PR-AUC 0.813) with consistent generalization across datasets. Key predictors included antihyperlipidemic therapy, systolic blood pressure variability, age, and sex. Conclusions: This study presents JoRisk, a calibrated and interpretable machine learning framework that integrates pharmacotherapy and clinical data for short-term cardiovascular risk prediction. The model demonstrates strong performance using routinely available EHR variables and offers a scalable decision-support tool for risk stratification in resource-constrained healthcare systems.

Background: Osteoporosis is increasingly understood as a complex population health condition shaped by interacting behavioral, metabolic, pharmacological, and healthcare system determinants rather than isolated skeletal risk factors. However, comparative studies integrating these dimensions across distinct healthcare and sociocultural settings remain scarce. We aimed to characterize cross-national differences in osteoporosis-related risk clustering between Romanian and Tunisian adults using an integrative multidimensional framework. Methods: We performed a comparative cross-sectional analysis of harmonized data from two pharmacy-based studies conducted in Romania and Tunisia, including adults aged ≥ 40 years (n = 349). Osteoporosis-related knowledge, lifestyle and metabolic risk factors, pharmacological exposures, preventive behaviors, and treatment patterns were assessed. Multivariable regression and mediation analyses were used to identify independent predictors of screening uptake and to evaluate the relationship between knowledge and preventive behavior. An exploratory cumulative preventive deficit score was used to estimate overall preventive burden within the pharmacy-based study sample. Results: Romanian participants demonstrated significantly higher osteoporosis knowledge than Tunisian participants (8.90 ± 2.20 vs. 7.83 ± 2.99; p < 0.001); however, knowledge was not independently associated with Dual-Energy X-ray Absorptiometry (DXA) uptake and did not mediate country-related differences in screening behavior. Compared with the Romanian cohort, the Tunisian cohort exhibited lower DXA screening rates (11.2% vs. 22.8%; p = 0.005), lower vitamin D supplementation (11.9% vs. 38.6%; p < 0.001), greater sedentary behavior, and a significantly higher cumulative preventive deficit burden (3.39 ± 1.08 vs. 2.77 ± 1.26; p < 0.001). Medication-related osteoporosis risk was also greater in Tunisia, particularly due to markedly higher corticosteroid exposure (7.5% vs. 0.5%; p = 0.002). Despite this less favorable preventive profile, the treatment gap among participants with diagnosed osteoporosis was significantly lower in Tunisia than in Romania (4.8% vs. 42.9%; p = 0.003). Conclusions: Distinct but convergent osteoporosis-related risk patterns were identified across the two populations, suggesting that osteoporosis vulnerability emerges through context-specific clustering of behavioral, pharmacological, and healthcare-access determinants rather than through isolated risk factors alone. The dissociation between knowledge and preventive behavior highlights the limited impact of awareness-based strategies when structural barriers remain unaddressed. These findings support a shift toward integrated, population-tailored osteoporosis prevention models that incorporate healthcare-system, medication-related, and behavioral determinants, in addition to conventional educational approaches.

Cardiovascular disease remains a leading cause of mortality despite major advances in lipid lowering and risk-factor control, highlighting the importance of residual cardiovascular risk. Inflammation is a central driver of atherosclerosis, while obesity promotes chronic low-grade inflammation, adipose tissue dysfunction, ectopic fat accumulation, and vascular injury. This narrative review focuses on obesity-associated inflammation as an upstream contributor to residual atherosclerotic risk and evaluates whether incretin-based therapies modify this pathway through weight loss, metabolic improvement, and additional inflammatory or vascular mechanisms. Data from mechanistic studies, biomarker analyses, vascular imaging studies, and cardiovascular outcome trials are reviewed. Anti-inflammatory trials support inflammation as a modifiable therapeutic pathway, although clinical benefit depends on the therapeutic target, timing, and patient selection. Glucagon-like peptide-1 receptor agonists reduce inflammatory and oxidative stress biomarkers and show anti-atherosclerotic effects in experimental models, but human vascular imaging data remain inconclusive. Cardiovascular outcome trials establish benefit with several GLP-1 receptor agonists, including semaglutide in selected patients with overweight or obesity without diabetes. However, direct human evidence for receptor-mediated anti-inflammatory or anti-atherosclerotic effects remains limited, and the relative contributions of weight loss, metabolic improvement, and additional mechanisms remain uncertain.

With the growing of the global population aging, the comorbidity of cardiovascular disease (CVD) and Alzheimer's disease (AD) has gradually become a major contributor to global disease burden, with the two diseases exhibiting interacting pathological characteristics. This review summarizes the mechanisms underlying CVD-AD comorbidity, including cerebral hypoperfusion and protein aggregation, oxidative stress and inflammation, as well as metabolic disorders and genetic factors. We also assess the value of blood biomarkers in this comorbidity, such as p-tau217, NT-proBNP, NfL, GFAP, and miRNAs. We then review the role of exercise in ameliorating this comorbidity, integrating its potential mechanisms into five aspects: repairing cerebral hypoperfusion and endothelial injury, accelerating Aβ clearance and inhibiting Tau protein hyperphosphorylation, reducing inflammation, protecting neuronal structure and the blood-brain barrier, and improving metabolic disorder. We also analyze in detail the relationship between exercise targets and blood biomarkers. Finally, we discussed the impact and application of different exercise modalities in this comorbidity, concluding with suitable exercise prescriptions and relevant safety considerations for each modality, further organized the mainstream pharmacological and nutritional intervention strategies for CVD-AD comorbidity, and objectively explored their potential interactions when combined with exercise interventions. Future research should integrate multi-omics technologies and gradually refine clinical data on comorbidity, with the aim of developing more targeted, personalized exercise prescriptions for patients with comorbidities, thereby providing scientific theoretical guidance for early risk prevention and disease management in patients with co-occurring CVD and AD.