Search Results (4,012)

Cardiovascular diseases (CVDs) remain a leading cause of mortality worldwide, and ageing is strongly associated with progressive arterial stiffening. Age-related alterations in extracellular matrix (ECM) mechanics influence vascular smooth muscle cell (VSMC) behaviour, while sympathetic innervation represents an additional regulator of vascular homeostasis. However, how neural signalling interacts with ageing-associated mechanical conditions to regulate VSMC behaviour remains unclear. In this study, an in vitro sympathetic neuron–VSMC co-culture model was established to investigate neuro-mechanical regulation. Primary rat sympathetic neurons and A7r5 VSMCs were cultured on glass or polydimethylsiloxane (PDMS) substrates with defined stiffness (20 and 130 kPa), representing healthy and ageing-associated stiffened arterial environments, respectively. VSMC behaviour was assessed through analysis of cell area, proliferation, migration, cellular Young’s modulus (YM), and DNA damage marker γH2AX. Sympathetic neuronal co-culture was associated with reduced VSMC spreading and decreased γH2AX levels. Under the conditions tested, neural signalling exerted limited effects on cell proliferation and migration. In contrast, increased substrate stiffness promoted cell proliferation and elevated YM. Both neuronal input and substrate stiffness were associated with increased cellular YM. Together, these findings indicate that neural and mechanical cues may jointly influence VSMC behaviour within ageing-associated mechanical environments. This co-culture system provides a controllable platform for studying neuro-mechanical interactions in vascular biology. Full article

Perirenal adipose tissue (PRAT) has emerged as a clinically relevant endocrine organ connecting obesity to cardiovascular disease (CVD), chronic kidney disease, and certain malignancies. Its unique anatomical location, surrounding the kidneys, accounts for PRAT’s role in altering intrarenal haemodynamics and hydrostatic pressure. Accordingly, PRAT’s expansion is associated with the activation of the renin–angiotensin–aldosterone system (RAAS), further increasing blood pressure. Adipokine dysregulation, together with overexpression of miR-24-3p, miR-155, miR-146a, and miR-21 in PRAT, modulates inflammation and oxidative stress, leading to endothelial dysfunction and increased risk of atherosclerosis and hypertension in obesity. Imaging assessment of PRAT thickness through computed tomography, magnetic resonance, or ultrasound has also emerged as a complementary measure for the evaluation of CVD risk. Potential therapeutic strategies targeting PRAT include lifestyle interventions, antidiabetic agents, RAAS inhibitors, adipose tissue browning agents, NOD-like receptor protein 3 (NLRP3) inflammasome inhibitors, peroxisome proliferator-activated receptor gamma (PPARγ) agonists, and surgery. Currently, novel therapeutic interventions targeting PRAT activity in CVD, such as senotherapeutic strategies, bioengineering approaches aimed at enhancing adipose-derived mesenchymal stem cell (ADMSC) function, gut microbiota modulation, and colchicine and bone morphogenetic protein 4 (BMP4) administration, are also being explored. In light of these findings, PRAT’s clinical relevance extends beyond its energy storage role, highlighting it as a metabolically active fat depot. Its assessment and therapeutic modulation may complement existing cardiovascular prevention strategies, particularly in patients with obesity. Full article

Background/Objectives: A body shape index (ABSI) has been proposed as an anthropometric measure reflecting abdominal body shape beyond body mass index (BMI). However, its relative cross-sectional discriminative ability compared with conventional anthropometric measures and surrogate markers of insulin resistance for prevalent diabetes and cardiovascular disease (CVD) remains poorly characterized in Korean adults. Methods: This cross-sectional study included 11,448 Korean adults aged 18–64 years from the 2019–2021 Korean National Health and Nutrition Examination Survey (KNHANES). Using receiver operating characteristic (ROC) curve analyses, we compared the discriminative ability of ABSI with BMI, waist circumference, waist-to-height ratio, homeostatic model assessment for insulin resistance (HOMA-IR), triglyceride-to-HDL cholesterol ratio (TG/HDL-C), and the triglyceride–glucose index (TyG) for prevalent diabetes and CVD. Multivariable logistic regression analyses assessed associations after adjustment for demographic and socioeconomic factors. Results: ABSI showed the highest ROC-AUC for both prevalent diabetes (74%) and CVD (74%) among the compared indices. In multivariable-adjusted analyses, individuals in the very high ABSI risk group had higher odds of prevalent CVD (OR, 3.75; 95% CI, 1.60–8.78) than those in the very low-risk group. Among individuals with diabetes, the odds of comorbid CVD were also higher in the very high ABSI group (OR, 3.38; 95% CI, 2.26–5.07). Similar patterns appeared in obesity-subgroup analyses. Conclusions: ABSI showed greater discriminative ability for prevalent diabetes and CVD than several conventional measures and insulin-resistance markers, supporting its potential utility as a simple marker of cardiometabolic disease burden. Prospective studies are needed to determine its prognostic value. Full article

Background: Cardiovascular disease (CVD) prevention in ageing populations requires simple and clinically accessible markers that may help identify individuals at elevated risk. Tooth loss is a common oral condition in middle-aged and older adults and may reflect cumulative inflammatory burden, impaired oral function, and broader health vulnerability. However, longitudinal evidence from nationally representative populations across different countries remains limited. We investigated whether a baseline of missing teeth was independently associated with incident CVD in three nationally representative ageing cohorts from China, the United States, and England. Methods: We analyzed data from the China Health and Retirement Longitudinal Study (CHARLS), the Health and Retirement Study (HRS), and the English Longitudinal Study of Ageing (ELSA). Participants aged 45 years or older without baseline CVD and with available baseline tooth status were included. Missing teeth were assessed at baseline as a dichotomous exposure. Incident CVD was defined as newly reported heart disease and/or stroke during follow-up. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), with sequential adjustment for sociodemographic, lifestyle, and clinical covariates. Kaplan–Meier, subgroup, and sensitivity analyses were also performed. Results: A total of 31,805 participants were included, comprising 13,451 from CHARLS, 11,384 from HRS, and 6970 from ELSA. During follow-up, 2336 incident CVD events occurred in CHARLS, 2914 in HRS, and 545 in ELSA. In fully adjusted models, missing teeth was associated with a higher risk of incident CVD in all three cohorts, with HRs of 1.31 (95% CI, 1.14–1.50) in CHARLS, 1.43 (95% CI, 1.29–1.57) in HRS, and 1.86 (95% CI, 1.49–2.31) in ELSA. Kaplan–Meier analyses showed consistently lower CVD-free survival among participants with missing teeth, and the associations remained broadly robust across subgroup and sensitivity analyses. Conclusions: In three nationally representative cohorts from China, the United States, and England, a baseline of missing teeth was independently associated with a higher risk of incident CVD among middle-aged and older adults. These findings suggest that missing teeth may serve as a simple and clinically accessible marker of elevated cardiovascular risk and support greater integration of oral health into cardiovascular risk assessment and preventive strategies for ageing populations. Full article

Background: Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality worldwide. The Mediterranean diet (MD) and regular physical activity are established components of cardiovascular prevention, but evidence regarding their combined cardiometabolic effects remains heterogeneous. Objective: This narrative review critically summarizes current evidence on the joint role of the MD and physical exercise in cardiometabolic health. Methods: A structured literature search was conducted in PubMed, Web of Science, and Scopus using terms related to the MD, CVD, cardiometabolic health, physical activity, and exercise. Experimental and observational human studies published between 2016 and 2026 were considered, together with relevant systematic reviews and meta-analyses. Particular attention was given to 10 key human studies, including randomized intervention studies and observational cohorts. Owing to substantial heterogeneity in populations, interventions, comparators, follow-up periods, and outcomes, the evidence was synthesized narratively. Results: The key studies generally reported favorable changes in body weight and composition, blood pressure, glucose regulation, and lipid profiles. One observational study also found a lower likelihood of cardiovascular medication initiation among participants with sustained adherence to both lifestyle components. However, most outcomes were surrogate cardiometabolic markers, and the independent effects of diet and exercise were often difficult to isolate. Conclusions: The MD and regular physical activity appear to be complementary components of cardiometabolic prevention. However, current evidence does not establish a consistent additive or synergistic effect. Further long-term, well-controlled studies are needed to clarify their independent and combined contributions across different populations. Full article

Chronic noncommunicable diseases, including cardiovascular disease (CVD), type 2 diabetes (T2D), and cancer, constitute leading causes of global mortality, with suboptimal diet identified as a primary modifiable risk factor. Plant-based dietary patterns (PBDPs) can be conceptualized along a continuum of quality, with whole-food PBDPs consistently linked to lower risks of CVD, T2D, and all-cause mortality, though much of this evidence derives from studies of vegan or healthy plant-based dietary index patterns rather than whole-plant-food diets directly. Evidence further indicates that minimizing or eliminating added salt, oil, and sugar (SOS) within whole-food PBDPs may provide additional cardiometabolic benefits, primarily by favorably modifying three graded intermediate biomarkers: low-density lipoprotein cholesterol (LDL-C), blood pressure (BP), and adiposity. Dietary sodium increases BP in a linear, dose-dependent manner and enhances food palatability, potentially promoting passive overconsumption and increased adiposity. Although added oil is preferable to saturated fat for LDL-C reduction, preliminary evidence suggests that adding olive oil to an already oil-restricted whole-food PBDP may reduce its LDL-C and body-weight benefits; these findings are hypothesis-generating and require confirmation in larger, longer-term trials. Whole-food fat sources such as nuts and seeds may offer cardiovascular benefits at least equivalent to those of oils, without this attenuating effect. Added sugar promotes excess caloric intake, contributing to increased adiposity, and may impair insulin sensitivity; these effects are most clearly and consistently established for sugar-sweetened beverages (SSBs), whereas the evidence for solid added sugars is weaker and may depend more on excess energy intake and broader dietary context. This narrative review synthesizes evidence from systematic reviews, meta-analyses, Mendelian randomization studies, and key clinical trials to evaluate whether whole-food PBDPs minimizing or eliminating SOS may provide incremental benefit for chronic disease risk reduction and management compared to whole-food PBDPs that include these additives. Direct long-term randomized evidence comparing SOS-restricted to SOS-inclusive whole-food PBDPs remains limited, and the possible incremental benefit of SOS restriction within an already health-promoting dietary pattern warrants further investigation. Complete SOS elimination has not yet been shown to provide incremental benefit beyond a high-quality PBDP, and any benefit is likely greatest in individuals with hypertension, obesity, elevated cardiometabolic risk, or high baseline SOS intake. Full article

Background: Although cardiovascular disease (CVD) significantly impacts the quality of life of millions of patients worldwide, the high costs of developing new drugs and conducting clinical trials for CVD hinder therapeutic development in this field. Repurposing approved drugs, of which the safety has already been tested can significantly reduce the time and cost required for treating CVD. From the perspective of pharmacology, repurposed drugs are selected to specifically target CVD patients carrying the matching drug targets, enabling tailored, personalized intervention. In the context of drug repurposing, therapeutic target mapping is a process used to assess the enrichment of molecules that can be affected by a drug in order to produce a therapeutic effect. Methods: This narrative review summarizes the workflows and challenges of performing therapeutic target mapping to assess the potential of repurposing existing drugs for treating CVD. We also share our perspective of how retrospective studies of human specimens can contribute to therapeutic target mapping based on experience from the Bruce McManus Cardiovascular Biobank (BMCB), a large explanted heart biobank located in Vancouver, Canada. The literature we discuss was identified by non-systematic searches of PubMed, using search terms “human-derived specimens”, “drug repurposing”, and “cardiovascular disease”. We reviewed articles from 2012 to 2026 and prioritized studies conducted after 2019 to discuss recent advances in the field. Conclusions: Human specimens of high molecular quality are needed for evaluating the enrichment of drug targets in CVD. Therapeutic target mapping in diseased cardiovascular tissue requires integrated expertise from medical, translational, and applied sciences to identify suitable human specimens for molecular phenotyping, and to design hypothesis-driven approaches to validate the drugs suggested for repurposing. Full article

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, driving the need for reliable tools for early risk prediction. Artificial intelligence (AI) applied to electrocardiograms (ECGs) has shown strong predictive performance for future cardiac events, yet its clinical adoption remains limited by the lack of transparency and trust associated with black-box models. This systematic review examines recent advances in AI-based cardiovascular prediction, focusing on the combined challenges of multi-modal data fusion and clinically actionable explainability. Following PRISMA 2020 guidelines, we analyzed 65 peer-reviewed studies published between 2018 and 2025, identified through a systematic search of PubMed, IEEE Xplore, Web of Science, Scopus, ACM Digital Library, and Google Scholar. The reviewed literature reveals that while most AI-ECG models achieve high predictive accuracy, typically AUC 0.85–0.95, the majority rely on post hoc explainability techniques that offer limited clinical insight, and 61.5% of included studies implement no explainability method at all. External validation remains critically underutilized, performed by only 12.3% of studies, and multi-modal approaches integrating ECG data with electronic health records, biomarkers, or genomics represent only 27.7% of the reviewed literature. While these multi-modal models demonstrate improved contextualization and predictive performance, they remain insufficiently validated and inconsistently interpretable. Among studies employing XAI techniques, attention mechanisms were the most prevalent approach (28% of XAI studies), followed by saliency maps (20%), SHAP (16%), and LIME (8%). Only 9.2% of studies were prospective or clinical trials, underscoring the gap between algorithmic development and real-world clinical deployment. Applying a pre-specified four-level clinical actionability scoring framework (Level 0–3), we found that the majority of studies (61.5%) scored at Level 0 (no actionability), with only 9.2% reaching Level 3 (demonstrated clinical impact), confirming that the clinical translation gap extends beyond trial design to encompass the broader absence of clinically contextualised evaluation of AI-ECG systems. This review highlights a persistent and critical gap between predictive performance and clinical usability, and outlines four key directions for developing AI-ECG systems that can better support trustworthy clinical decision-making: (1) developing inherently interpretable architectures, (2) advancing unified multi-modal fusion and explanation frameworks, (3) establishing standardized benchmarks for explainability evaluation, and (4) conducting robust prospective validation measuring real-world patient outcomes. Full article

Non-communicable diseases (NCDs), including type 2 diabetes mellitus (DM), hypertension (HTA), obesity (OB), and cardiovascular disease (CVD), represent a major global health burden and disproportionately affect socially vulnerable populations. Small extracellular vesicles (EVs) are stable carriers of proteins and regulatory RNAs that may reflect endothelial dysfunction and cardiometabolic stress. This study explored plasma-derived EV-associated biomarkers in adults from La Guajira, Colombia, with emphasis on miR-126-3p, miR-21-5p, miR-92a-3p, and SNAIL. Anthropometric, clinical, and biochemical data were obtained from a cross-sectional cohort. Representative plasma samples were selected for EVs isolation by size-exclusion chromatography. Vesicles were characterized by nanoparticle tracking analysis, scanning transmission electron microscopy, protein quantification, Western blotting, and bead-based flow cytometry. Candidate miRNAs were identified by small RNA sequencing and validated by stem-loop RT-qPCR. Bioinformatic enrichment analyses were performed using miRNet 2.0 and KEGG pathway analysis. The epidemiological cohort showed a high cardiometabolic burden, with waist-to-height ratio (WHtR) and triglyceride-glucose (TyG) index emerging as key markers of central adiposity and metabolic dysfunction. Plasma-derived EVs displayed the expected nanoscale morphology and expressed canonical vesicle markers. Protein cargo analyses revealed EMT- and remodeling-associated proteins, including SNAIL and GAL-3. EV-associated miR-126-3p, miR-21-5p, and miR-92a-3p were enriched predominantly in hypertensive and hypertensive-diabetic groups. In an exploratory sub-cohort, CD31-positive EVs showed a trend toward increased expression in individuals with previous myocardial infarction or stroke (p = 0.057). KEGG enrichment analysis linked the identified miRNA signature to pathways involved in endothelial dysfunction, inflammation, vascular remodeling, apoptosis, and extracellular matrix organization. Plasma-derived EVs from individuals with cardiometabolic disorders carry molecular signatures consistent with endothelial stress and vascular remodeling. These findings identify miR-126-3p, miR-21-5p, miR-92a-3p, SNAIL, and CD31-positive EVs as exploratory candidate biomarkers that require validation in larger prospective cohorts. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) and arterial hypertension (AH) frequently coexist and are major risk factors for cardiovascular disease (CVD) and chronic kidney disease. Although the Mediterranean diet (MeDi) is widely recommended in cardiometabolic management, longitudinal real-world evidence regarding dietary adherence, body composition, and the role of continuous dietitian-led follow-up remains limited. Methods: This three-year prospective observational study included 158 adults with T2DM and AH treated at the Outpatient Clinic for Clinical Nutrition, University Hospital Centre Split, Croatia. Body composition was assessed using multi-frequency bioelectrical impedance analysis, dietary adherence using the Mediterranean Diet Serving Score (MDSS), and renal and metabolic parameters using standard laboratory methods. Participants were stratified according to attendance at scheduled dietitian-led follow-up visits. Results: Significant reductions were observed in body weight, body mass index (BMI), waist circumference, muscle mass, skeletal muscle index, and phase angle (PhA) during follow-up (all p < 0.001). Lipid profile improved, with reductions in total cholesterol and low-density lipoprotein levels and an increase in high-density lipoprotein concentrations. In contrast, renal function declined, as evidenced by increased creatinine and urea levels and decreased estimated glomerular filtration rate (eGFR). CVD incidence increased significantly during follow-up (p < 0.001). Although overall adherence to the MeDi improved, only 17.8% of participants achieved high adherence. Participants attending regular dietitian-led follow-up demonstrated significantly higher MDSS scores, greater adherence to the MeDi, and higher phase angle values compared with participants without regular follow-up. Conclusions: Adults with T2DM and AH demonstrated partial enhancement of MeDi adherence over three years; although the lipid profile also improved, this could not be attributed to diet and may largely reflect pharmacological treatment. These changes were accompanied by progressive muscle mass loss, declining renal function, and increased cardiovascular burden. Continuous dietitian-led follow-up was associated with superior dietary quality and better nutritional status, supporting the importance of individualized, multidisciplinary approaches integrating sustained nutritional counselling, lean mass preservation, and structured physical activity in long-term cardiometabolic care. Full article

Cardiovascular diseases (CVDs) remain the foremost cause of death globally, responsible for 19.2 million deaths and 437 million disability-adjusted life years in 2023, with prevalent cases having more than doubled since 1990. No approved therapy restores myocardium lost to infarction. The adult heart replaces cardiomyocytes at approximately 1% per year in young adults, declining to about 0.45% per year with ageing, far below what is needed to recover the more than one billion cells destroyed by a large myocardial infarction. Cell-based regenerative strategies have been investigated for more than two decades, encompassing bone marrow mononuclear cells (BM-MNCs), mesenchymal stromal cells (MSCs), cardiac progenitor cells, cardiosphere-derived cells (CDCs), skeletal myoblasts, and induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). Safety has been consistent. Efficacy has been modest and variable: the CADUCEUS trial demonstrated scar mass reduction with CDCs without proportionate ejection fraction improvement; the Phase 1/2 POSEIDON trial confirmed MSC safety in 30 patients; and the Phase 3 DREAM-HF trial, enrolling 537 patients, failed its primary endpoint (HR 1.2, p = 0.406). Mechanistic work has established that transplanted cells engraft poorly and exert their benefit principally through paracrine signalling mediated by secreted extracellular vesicles and exosomes carrying microRNAs, trophic factors, and immunomodulatory proteins. For iPSC-CMs, electrophysiological immaturity and arrhythmogenic risk in primate models remain unresolved barriers. Emerging strategies include CRISPR-engineered hypoimmune iPSC lines, bioengineered cardiac patches, injectable hydrogel scaffolds, and engineered exosome platforms. This review provides a comprehensive synthesis of preclinical and clinical evidence, examines translational barriers, and identifies the scientific and regulatory priorities required before these therapies can enter routine clinical practice. Full article

Predictive models used for the assessment of cardiovascular disease (CVD) risk must not only be highly accurate but also explainable and reliable for clinical decision-making. In this paper, we present a methodological framework for explainable machine learning and deep learning approaches to CVD risk prediction that uses clinically derived electrocardiogram (ECG) features and conventional CVD risk factors. A large synthetic dataset containing 30,000 patient cases was created according to a clinically validated distribution to provide reproducible and privacy-preserving benchmarking. A series of interpretability tests were performed on multiple models of machine learning and deep learning categories within a unified experimental setup. Out of the tested models, XGBoost and BiLSTM provided the highest discrimination capabilities in the machine learning and deep learning categories, respectively. Explaining the predictions via the SHapley Additive explanations (SHAP) approach, calibration of probability estimations, uncertainty quantification, and ablation studies were applied to assess the explainability, reliability, and robustness of the models. We show that the presented framework allows for the production of consistent and interpretable predictions along with the evaluation of the models’ explainability and predictive reliability. Instead of focusing on the single-feature importance, this paper presents a reproducible methodological framework for the explainable modeling of CVD risk. Full article

Cardiovascular disease (CVD) is the result of a complex interaction between genetic, lifestyle, and environmental factors, which may vary over the course of life. Traditional risk factors do not explain all patients’ risks; thus, the research of additional biomarkers to refine cardiovascular risk prediction has attracted considerable interest in recent years. Genetic factors, as well as air pollution exposure, among nontraditional factors, have been found to be critical determinants of CV risk. Accordingly, this narrative review aims to provide a comprehensive summary of the literature (PubMed) on the combined effects of air pollution and genetic susceptibility on CVD risk. Although different limitations and pitfalls are still to be solved, available evidence suggests that genetic variants (especially genes related to detoxification and inflammation) are involved in the association between air pollution exposure and CV adverse events. Thus, this research area could provide further knowledge of the etiology of CVD, offering new tools for targeted prevention and treatment of more susceptible subjects from a more personalized medicine point of view. Full article

Cardiovascular disease (CVD) remains the leading global cause of morbidity and mortality. While low-dose aspirin is well established for secondary prevention, its role in primary prevention is controversial because modest benefits in cardiovascular benefits must be balanced against increased bleeding risk, as highlighted by recent large trials. Current guidelines recommend restricting aspirin use to individuals at higher cardiovascular risk without elevated bleeding risk, yet significant heterogeneity persists in defining these thresholds. Evidence from randomized trials, guidelines, cohort and modeling analyses, and post hoc or observational subgroup studies suggests that selected patients with advanced subclinical atherosclerosis or specific high-risk markers may have a more favorable risk–benefit profile, although the certainty and directness of evidence vary across subgroups. This narrative review and pragmatic clinical guide presents an illustrative tiered framework based on clinical, imaging, and biomarker markers—such as coronary artery calcium score, carotid plaque score, and lipoprotein(a)—to support individualized discussion of preventive aspirin therapy. The framework is not a validated risk calculator or standalone treatment algorithm, and decisions should balance absolute cardiovascular risk, major bleeding risk, evidence certainty, and patient preferences. Full article

Background: Epidemiological evidence suggests that green leafy vegetables (GLV) may reduce the risk of cardiovascular disease (CVD). However, the relationship remains incompletely understood due to inconsistencies between findings from observational studies and randomized controlled trials (RCTs). Therefore, a comprehensive synthesis of evidence across study designs is warranted. This systematic review and meta-analysis aimed to evaluate the association between GLV consumption and CVD risk, as well as related cardiovascular risk factors, including blood pressure (BP) and endothelial function, based on evidence from observational studies and RCTs. Methods: Systematic searches of PubMed, EMBASE, APA PsycInfo, and Ovid databases were conducted through 30 October 2024. Risk of bias was assessed using the ROBINS-E tool for observational studies and the RoB 2 tool for RCTs. Pooled relative risks (RRs) with 95% confidence intervals (CIs) were calculated for observational studies, whereas mean differences (MDs) were used for RCT outcomes. Random-effects meta-analyses were performed, and heterogeneity was evaluated using Cochran’s Q and I² statistics. Results: Higher GLV consumption was significantly associated with a reduced risk of CVD in observational studies (RR: 0.89; 95% CI: 0.82–0.97; p < 0.01; I² = 80%; Q = 55.88) and lower CVD mortality (RR: 0.79; 95% CI: 0.62–0.97; p < 0.01; I² = 80%; Q = 4.93). However, pooled analysis of seven RCTs showed no significant improvement in vascular function following GLV intake (MD: −0.37; 95% CI: −1.90 to 1.16; p = 0.64; I² = 88%; Q = 18.59). No significant associations were observed between GLV consumption and hypertension risk in observational studies, nor were significant effects found on systolic or diastolic BP in RCTs. Conclusions: Higher GLV consumption may be associated with a lower risk of CVD in observational studies. However, evidence from RCTs remains limited and inconclusive. Further well-designed clinical trials are needed to confirm these associations, establish dose–response relationships, and elucidate the mechanisms underlying the cardioprotective effects of GLVs to support evidence-based dietary recommendations. Full article