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Introduction: Artificial Intelligence (AI) has emerged as a seminal force in healthcare, fundamentally transforming various aspects of medical practice and patient care. This review explores the transformative impact of AI on the treatment of cardiovascular diseases (CVDs). State of Knowledge: AI has revolutionized diagnostic accuracy, treatment precision, and patient management in the realm of cardiovascular care. It enhances diagnostic processes, enabling the early detection of CVDs through advanced imaging analysis and interpretation. Additionally, AI facilitates precision in risk stratification, identifying high-risk patient cohorts with heightened accuracy and informing personalized treatment strategies. Furthermore, AI optimizes drug selection and dosage regimens through pharmacogenomics, maximizing therapeutic efficacy while minimizing adverse drug reactions. Moreover, AI improves precision and safety during interventional procedures, guiding clinicians in real-time decision-making and enhancing procedural outcomes. Conclusions: AI is poised to revolutionize cardiovascular care, fostering innovation and improving patient outcomes.

In this paper, we propose a new Modified Laplacian Vector Median Filter (MLVMF) for real-time denoising complex images corrupted by "salt and pepper" impulsive noise. The method consists of two rounds with three steps each: the first round starts with the identification of pixels that may be contaminated by noise using a Modified Laplacian Filter. Then, corrupted pixels pass a neighborhood-based validation test. Finally, the Vector Median Filter is used to replace noisy pixels. The MLVMF uses a 5 × 5 window to observe the intensity variations around each pixel of the image with a rotation step of π/8 while the classic Laplacian filters often use rotation steps of π/2 or π/4. We see better identification of noise-corrupted pixels thanks to this rotation step refinement. Despite this advantage, a high percentage of the impulsive noise may cause two or more corrupted pixels (with the same intensity) to collide, preventing the identification of noise-corrupted pixels. A second round is then necessary using a second set of filters, still based on the Laplacian operator, but allowing focusing only on the collision phenomenon. To validate our method, MLVMF is firstly tested on standard images, with a noise percentage varying from 3% to 30%. Obtained performances in terms of processing time, as well as image restoration quality through the PSNR (Peak Signal to Noise Ratio) and the NCD (Normalized Color Difference) metrics, are compared to the performances of VMF (Vector Median Filter), VMRHF (Vector Median-Rational Hybrid Filter), and MSMF (Modified Switching Median Filter). A second test is performed on several noisy chest x-ray images used in cardiovascular disease diagnosis as well as COVID-19 diagnosis. The proposed method shows a very good quality of restoration on this type of image, particularly when the percentage of noise is high. The MLVMF provides a high PSNR value of 5.5% and a low NCD value of 18.2%. Finally, an optimized Field-Programmable Gate Array (FPGA) design is proposed to implement the proposed method for real-time processing. The proposed hardware implementation allows an execution time equal to 9 ms per 256 × 256 color image. [ABSTRACT FROM AUTHOR]

Objectives: Aldosterone-to-renin ratio (ARR) based screening is the first step in the diagnosis of primary aldosteronism (PA). However, the guideline-recommended ARR cutoff covers a wide range, from the equivalent of 1.3 to 4.9 ng·dl -1 /mIU∙l -1 . We aimed to optimize the ARR cutoff for PA screening based on the risk of cardiovascular diseases (CVD)., Methods: Longitudinally, we included hypertensive participants from the Framingham Offspring Study (FOS) who attended the sixth examination cycle and followed up until 2014. At baseline (1995-1998), we used circulating concentrations of aldosterone and renin to calculate ARR (unit: ng·dl -1 /mIU∙l -1 ) among 1,433 subjects who were free of CVD. We used spline regression to calculate the ARR threshold based on the incident CVD. We used cross-sectional data from the Chongqing Primary Aldosteronism Study (CONPASS) to explore whether the ARR cutoff selected from FOS is applicable to PA screening., Results: In FOS, CVD risk increased with an increasing ARR until a peak of ARR 1.0, followed by a plateau in CVD risk (hazard ratio 1.49, 95%CI 1.19-1.86). In CONPASS, when compared to essential hypertension with ARR < 1.0, PA with ARR ≥ 1.0 carried a higher CVD risk (odds ratio 2.24, 95%CI 1.41-3.55), while essential hypertension with ARR ≥ 1.0 had an unchanged CVD risk (1.02, 0.62-1.68). Setting ARR cutoff at 2.4 ~ 4.9, 10% ~30% of PA subjects would be unrecognized although they carried a 2.45 ~ 2.58-fold higher CVD risk than essential hypertension., Conclusions: The CVD risk-based optimal ARR cutoff is 1.0 ng·dl -1 /mIU∙l -1 for PA screening. The current guideline-recommended ARR cutoff may miss patients with PA and high CVD risk., Clinical Trial Registration: ClinicalTrials.gov (NCT03224312).

Background: The progression of central blood pressure (CBP) values and central hemodynamic parameters and its relationship with cardiovascular risk factors is quite unknown. We sought to investigate this association in a Spanish adult population without cardiovascular diseases., Methods: Prospective observational research with a 5-year follow-up. Randomly sampled 501 individuals (mean age 56 ± 14 years, 50.3% women). After 5 years, 480 individuals had a follow-up. Measurements taken using the SphygmoCor (AtCor Medical Pty Ltd., Head Office, West Ryde, Australia), following all the recommendations established in the "International task force" (Sharman JE, Avolio AP, Baulmann J, Benetos A, Blacher J, Blizzard CL, Boutouyrie P, Chen CH, Chowienczyk P, Cockcroft JR, Cruickshank JK, Ferreira I, Ghiadoni L, Hughes A, Jankowski P, Laurent S, McDonnell BJ, McEniery C, Millasseau SC, Papaioannou TG, Vlachopoulos C. Validation of non-invasive central blood pressure devices: ARTERY Society task force consensus statement on protocol standardization. Eur Heart J 2017; 38:2805-2812), giving an estimate of CBP relative to measured brachial blood pressure (type 1 device)., Results: Progressions during follow-up: central systolic blood pressure (cSBP): 4.16 ± 13.71 mm Hg; central diastolic blood pressure: 2.45 ± 11.37 mm Hg; central pulse pressure: 1.72 ± 12.43 mm Hg; pulse pressure amplification (PPA): 2.85 ± 12.20 mm Hg; ejection duration: 7.00 ± 47.87 ms; subendocardial viability ratio (SEVR): -8.04 ± 36.24%. In multiple regression analysis: cSBP positively associated with: body mass index (BMI) (β = 0.476); waist size (β = 0.159); number of cigarettes per day (β = 0.192). Inversely associated with peripheral systolic blood pressure (β = -0.282). Central diastolic blood pressure increase positively associated with number of cigarettes per day (β = 0.174). Inversely associated with peripheral diastolic blood pressure (β = -0.292). Central pulse pressure increase positively associated with BMI (β = 0.330). Inversely associated with peripheral pulse pressure (β = -0.262). Pulse pressure amplification increase positively associated with: BMI (β = 0.276); number of cigarettes per day (β = 0.281). Ejection duration progress inversely associated with basal plasma glucose (β = -0.286)., Conclusions: All measures increased except for SEVR. Progressions in CBP and PPA were positively associated with anthropometric parameters and number of cigarettes and CBP inversely associated with peripheral blood pressure, although this association was different according to sex., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Journal of Hypertension, Ltd. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: It is uncertain which lipid-related parameter is most suitable for predicting the risk of cardiometabolic disease (CMD) in individuals with hypertension., Aims: To explore which lipid-related parameter is most suitable for predicting the risk of CMD., Methods and Results: We studied 30,378 patients with hypertension who completed the 2006-2007 Kailuan health examination and followed up until December 31, 2021. In the constructed model, the utilities of lipid-related parameters for the prediction of CMD were compared using the C-index, NRI, and IDI. The best predictor (remnant cholesterol, RC) was identified and the participants were grouped according to RC quartile. Cox proportional hazard analysis was then used to evaluate the relationship between RC and the risk of CMD. During a median follow-up period of 14.7 years (IQR 5.3-15.1), 9502 (31.27 %) participants with hypertension developed CMD. The C-index, NRI, and IDI values for RC were higher than those for the other lipid parameters. After adjustment for multiple potential confounding factors, compared with the quartile (Q)1 RC group, the adjusted hazard ratios for CMD of the Q2-Q4 groups were 1.09 (1.03-1.16), 1.17 (1.11-1.24), and 1.25 (1.18-1.33) (P < 0.0001). Restrictive cubic spline analysis revealed dose-dependent relationships of lipid parameters with the risk of CMD., Conclusions: RC is superior to other lipid parameters for the prediction of the risk of CMD in individuals with hypertension. As the concentration of RC increases, the risk of CMD in such individuals also increases., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Current prediction models for mainland Europe do not include ethnicity, despite ethnic disparities in cardiovascular disease (CVD) risk. SCORE2 performance was evaluated across the largest ethnic groups in the Netherlands and ethnic backgrounds were added to the model., Methods: 11,614 participants, aged between 40 and 70 years without CVD, from the population-based multi-ethnic HELIUS study were included. Fine and Gray models were used to calculate sub-distribution hazard ratios (SHR) for South-Asian Surinamese, African Surinamese, Ghanaian, Turkish and Moroccan origin groups, representing their CVD risk relative to the Dutch group, on top of individual SCORE2 risk predictions. Model performance was evaluated by discrimination, calibration and net reclassification index (NRI)., Results: Overall, 274 fatal and non-fatal CVD events, and 146 non-cardiovascular deaths were observed during a median of 7.8 years follow-up (IQR 6.8-8.8). SHRs for CVD events were 1.86 (95 % CI 1.31-2.65) for the South-Asian Surinamese, 1.09 (95 % CI 0.76-1.56) for the African-Surinamese, 1.48 (95 % CI 0.94-2.31) for the Ghanaian, 1.63 (95 % CI 1.09-2.44) for the Turkish, and 0.67 (95 % CI 0.39-1.18) for the Moroccan origin groups. Adding ethnicity to SCORE2 yielded comparable calibration and discrimination [0.764 (95 % CI 0.735-0.792) vs. 0.769 (95 % CI 0.740-0.797)]. The NRI for adding ethnicity to SCORE2 was 0.24 (95 % CI 0.18-0.31) for events and - 0.12 (95 % CI -0.13-0.12) for non-events., Conclusions: Adding ethnicity to the SCORE2 risk prediction model in a middle-aged, multi-ethnic Dutch population did not improve overall discrimination but improved risk classification, potentially helping to address CVD disparities through timely treatment., Competing Interests: Declaration of competing interest All authors declare no conflicting interest., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Purpose: Studies consistently show abnormally high levels of lactate acid in cardiovascular disease patients, suggested that targeting lactate production may serve as potential strategies for the treatment in the future. However, observational results may be subject to residual confounding and bias., Methods: This study used the dataset from GWAS database to examine confounding in epidemiologic associations between lactate and cardiovascular diseases. A genome-wide genetic association study using Mendelian randomization (MR) was performed from December 02, 2023 to January 15, 2024 to reduce confounding and enhance causal inference. Primary analysis was conducted using inverse-variance-weighted MR. All studies included patients predominantly of European ancestry., Results: The association between lactate and cardiovascular diseases, including 60801 cases from coronary heart disease, 7018 cases from myocardial infarction, 14334 cases from coronary atherosclerosis, 60620 cases from atrial fibrillation, 54358 cases from hypertension, 71 cases from hypertrophic cardiomyopathy, 47309 cases from heart failure, 7055 cases from stroke, 7193 cases from cardioembolic ischemic stroke, 4373 cases from ischemic stroke caused by large vascular atherosclerosis, 2118 cases from pulmonary embolism, 1230 cases from peripheral artery disease, and 4620 cases from venous thromboembolism. Genetically predicted coronary atherosclerosis was associated with a higher risk of lactate level (OR = 1.950; 95% CI (0.087, 1.249); P = 0.024); this association was also evident for peripheral artery disease (OR = 1.003; 95% CI (0.000, 0.005); P = 0.021). No genetically predicted associations were noted for the other cardiovascular diseases., Conclusion: The findings of this study provide genetic evidence supporting a higher risk of lactate level only in coronary atherosclerosis and peripheral artery disease. However, no genetic association between lactate level and the other cardiovascular diseases., Competing Interests: The authors report no conflicts of interest in this work., (© 2024 Chang et al.)

Background: The risk of cardiovascular disease (CVD) is increased in individuals with type 2 diabetes mellitus (T2DM), but it remains uncertain how long an elevated CVD occurrence precedes diabetes diagnosis., Objectives: The aim of this study was to investigate CVD occurrence 30 years before, and 5 years after, T2DM diagnosis compared with matched comparisons., Methods: This combined case-control and cohort study included all individuals diagnosed with T2DM in Denmark between 2010 and 2015, as well as general population comparisons matched by age and sex. CVD was defined as myocardial infarction or ischemic stroke. Conditional logistic regression was used to compute ORs for CVD prevalence in the 30-year period before T2DM diagnosis. Cox proportional hazards regression models were used to compute HRs for 5-year CVD incidence after T2DM diagnosis., Results: The study included 127,092 individuals with T2DM and 381,023 matched comparisons. In the 30-year period before T2DM diagnosis, 14,179 (11.2%) T2DM individuals and 17,871 (4.7%) comparisons experienced CVD. CVD prevalence was higher in those with T2DM than the comparisons in the entire period before T2DM diagnosis, with ORs ranging from 2.18 (95% CI: 1.91-2.48) in the earliest period (25-30 years before diagnosis) to 2.96 (95% CI: 2.85-3.08) in the latest period (<5 years before diagnosis). After T2DM diagnosis, 5-year CVD incidence was similarly increased in T2DM individuals vs comparisons (HR: 2.20; 95% CI: 2.12-2.27)., Conclusions: Individuals with T2DM had 2-fold more CVD events than matched comparisons starting 3 decades before T2DM diagnosis. This indicates that comprehensive preventive strategies may be initiated much earlier in individuals at risk of T2DM., Competing Interests: Funding Support and Author Disclosures Dr Gyldenkerne is supported by a scholarship from Aarhus University. The funding source had no influence on the study design, conduct and interpretation of the data, or the decision to submit this manuscript for publication. Dr Maeng is supported by the Borregaard Clinical Ascending Investigator Research Grant financed by the Novo Nordisk Foundation (grant NNF22OC0074083); has received lecture and/or advisory board fees from AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, and Novo Nordisk; has received research grants from Philips, Bayer, and Novo Nordisk; has received a travel grant from Novo Nordisk; has ongoing research contracts with Janssen, Novo Nordisk, and Philips; and is a minor shareholder in Eli Lilly & Company, Novo Nordisk, and Verve Therapeutics. The Department of Clinical Epidemiology, Aarhus University Hospital, receives funding for other studies from companies in the form of research grants to (and administered by) Aarhus University. Dr Olesen is supported by the Danish Cardiovascular Academy, which is funded by the Novo Nordisk Foundation (grant NNF20SA0067242) and The Danish Heart Foundation. None of these studies have any relation to the current study. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Obesity, defined by body mass index (BMI) alone, is a metabolically heterogeneous disorder with distinct cardiovascular manifestations across individuals. This study aimed to investigate the associations of a proteomic signature of BMI with risk of major subtypes of cardiovascular disease (CVD)., Methods: A total of 40 089 participants from UK Biobank, free of CVD at baseline, had complete data on proteomic data measured by the Olink assay. A BMI-proteomic score (pro-BMI score) was calculated from 67 pre-identified plasma proteins associated with BMI., Results: A higher pro-BMI score was significantly associated with higher risks of ischemic heart disease (IHD) and heart failure (HF), but not with risk of stroke. Comparing the highest with the lowest quartiles, the adjusted hazard ratio (HR) for IHD was 1.49 (95% CI, 1.32-1.67) (P-trend < 0.001), and the adjusted HR for HF was 1.52 (95% CI, 1.25-1.85) (P-trend < 0.001). Further analyses showed that the association of pro-BMI score with HF risk was largely driven by the actual BMI, whereas the association of the pro-BMI score with IHD risk was independent of actual BMI and waist-to-hip ratio (WHR). The association between pro-BMI score and IHD risk appeared to be stronger in the normal BMI group than other BMI groups (P-interaction = 0.004) and stronger in the normal WHR group than the high WHR group (P-interaction = 0.049)., Conclusions: Higher pro-BMI score is significantly associated with higher IHD risk, independent of actual BMI levels. Our findings suggest that plasma proteins hold promise as complementary markers for diagnosing obesity and may facilitate personalized interventions., (© Association for Diagnostics & Laboratory Medicine 2024.)

Chronic kidney disease and dialysis-dependent end-stage renal disease are increasing in prevalence in the United States. The costs associated with end-stage renal disease management comprise approximately 1% of the federal government's annual budget. Chronic kidney disease and end-stage renal disease cause significant derangements of the cardiac and vascular system. Pathophysiologic hallmarks include alterations of the renin-angiotensin system, chronically increased sympathetic tone, calcium and phosphate imbalance, pro-inflammatory cytokine release, and uremic toxin accumulation. This results in several pathologies specific to the cardiac and vascular systems, which will each be reviewed separately herein., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article., (Published by Elsevier Inc.)

Introduction: Cardiovascular diseases (CVDs) are disorders affecting the heart and blood vessels. Early diagnosis of CVDs and timely intervention can prevent complications, enable prompt treatment, and reduce the burden of the disease on individuals and healthcare systems. Artificial intelligence (AI) has recently been utilized to analyze electrocardiogram (ECG) data to diagnose and classify CVDs. The present systematic review aimed to explore practical AI algorithms for analyzing ECG data to identify and classify CVDs., Search Strategy: The study was conducted based on the PICO criteria and adhering to the PRISMA checklist. This review included a comprehensive search from 2020 to 2024 across the PubMed, Scopus, Web of Science, SID, and Magiran databases, as well as the Google Scholar search engine. The search utilized MESH keywords including "Diagnosis" , "cardiovascular disease" , "Artificial intelligence" and "electrocardiogram". Subsequently, two independent researchers screened the retrieved articles based on inclusion criteria., Results: A total of 90 articles were identified through the initial search. Seven articles were finally included in the study. Most studies indicated that AI technology, utilizing specific algorithms, such as Convolutional Neural Network (CNN), Grasshopper Optimisation Algorithm (GOA), ResNet-50, and Gated Recurrent Unit (GRU), can facilitate early diagnosis and classification of CVDs by analyzing raw ECG data. In conjunction with the GOA algorithm, the CNN algorithm successfully identified and classified 16 categories of CVDs, with an accuracy of 99.58%, by analyzing ECG data. In this analysis, CNN extracted visual patterns from the data, while GOA assisted in fine-tuning its internal parameters to achieve higher accuracy. The ResNet-50 algorithm, a specific type of CNN, has also diagnosed and classified 27 categories of CVDs, with an accuracy of 97.63% using the skip connections mechanism and ECG data. Furthermore, using ECG data, the GRU algorithm effectively identified four categories of CVDs, with an accuracy of 58.90%., Conclusion and Discussion: AI-based diagnosis and classification of CVD patients using ECG data holds promise for accurate and timely diagnosis and classification. Integrating AI technologies into healthcare practices can make the diagnostic process faster and easier, ultimately leading to better management of CVD patients. However, given the limitations of the studies conducted in this field, further and more diverse research is recommended.

Aim: To identify risk factors associated with major adverse cardiovascular events (MACE) and malignancies in patients with rheumatoid arthritis (RA) using real-world data from Japan., Methods: This cohort study used the Real World Data database of medical institutions in Japan. Eligible patients (January 2013-December 2021) had ≥ 1 RA diagnosis, were aged ≥ 18 years, prescribed ≥ 1 antirheumatic drug, had no psoriasis diagnosis, and had a record postindex. Patients had no myocardial infarction/stroke ≤ 31 days (MACE cohort) or malignancy < 1 year (malignancy cohort) before index. Cohorts were determined by incidence of initial MACE or malignancy. Known/exploratory variables were selected using Cox regression models., Results: Across MACE (n = 16 012) and malignancy (n = 14 545) cohorts, most patients were female and aged ≥ 65 years. Overall, 214 MACE per 43964.7 patient-years (incidence rate 0.49 per 100 patient-years) and 315 malignancies per 40251.6 patient-years (incidence rate 0.78 per 100 patient-years) occurred. Male sex, older age (≥ 65 years), hypertension, renal disease, cerebrovascular disease, and prior X-ray examination were significantly associated with increased MACE risk. Male sex, older age (≥ 50 years), nonsteroidal anti-inflammatory drug use, emphysema, serious infection, malignancy history, and prior X-ray examination were significantly associated with increased malignancy risk. Conversely, glucocorticoid use and fracture diagnosis were significantly associated with reduced malignancy risk., Conclusion: In patients with RA in Japan, male sex, older age, and prior X-ray examination were associated with increased MACE and malignancy risk., (© 2024 The Author(s). International Journal of Rheumatic Diseases published by Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.)

Inflammatory bowel diseases (IBD) are chronic inflammatory and pathological conditions of the gastrointestinal tract, which include two main clinical subtypes: Crohn's disease (CD) and ulcerative colitis (UC). IBDs show an increase in their age-standardized global incidence rate worldwide, with no gender differences, although the age-standardized mortality rate has decreased over the years. Indeed, thanks to recent therapies with novel mechanisms of action, including those with biologics and small molecules, it has been possible to reduce the mortality rate of IBDs. However, a significant percentage of IBD patients remain refractory to these multiple advanced therapies. Therefore, another challenge of IBD research remains the development of novel therapies with novel agents or cells that could improve the quality of life and outcome of IBD patients. Furthermore, another aspect to be studied in IBDs is not only the high risk of progression not only to neoplastic transformation but also to the development of cardiovascular disease (CVD). Consequently, 25-40 % of IBD patients present with cardiovascular manifestations. Here, we propose that the altered number and functions of endothelial progenitor cells (EPCs) may represent one of the crucial mechanisms associated with incomplete/delayed healing of IBD and may offer the possibility of using them, as well as their vesicles and content, as novel biomarkers and potential candidates of cell therapy for IBD. The advantages and limitations are extensively described and discussed., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Aim: Arterial stiffness, a significant cardiovascular risk marker, is particularly important in patients with diabetes mellitus (DM). Pulse wave velocity (PWV), a non-invasive measure of arterial stiffness, has emerged as an independent predictor of cardiovascular morbidity and mortality. However, its precise prognostic value in DM patients for cardiovascular risk stratification remains unclear. To address this, a systematic review was conducted., Method: A thorough search of Ovid and Scopus databases was performed for cohort studies on PWV measurements for cardiovascular risk stratification in DM patients. Nine studies were included, examining the relationship between PWV and cardiovascular events or composite endpoints in DM patients asymptomatic of cardiovascular diseases (CVD)., Results: The review revealed that optimal PWV cutoffs to predict composite cardiovascular events ranged from 10 to 12.16 m/s (aortic PWV) and 14 to 16.72 m/s (brachial-ankle PWV). In addition, meta-analysis yielded a HR of 1.15 (95 % CI 1.07-1.24, p < 0.001, I 2  = 70 %) for aortic PWV in predicting cardiovascular events., Conclusion: The assessment of arterial stiffness via PWV shows promise as an early diagnostic marker for CVD in DM patients, aiding in improved disease management. This underscores the potential of PWV in enhancing cardiovascular risk assessment and guiding clinical decisions in this high-risk population, without invasive procedures or radiation exposure., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background and Objective: Phonocardiogram (PCG) signal analysis is a non-invasive and cost-efficient approach for diagnosing cardiovascular diseases. Existing PCG-based approaches employ signal processing and machine learning (ML) for automatic disease detection. However, machine learning techniques are known to underperform in cross-corpora arrangements. A drastic effect on disease detection performance is observed when training and testing sets come from different PCG databases with varying data acquisition settings. This study investigates the impact of data acquisition parameter variations in the PCG data across different databases and develops methods to achieve robustness against these variations., Methods: To alleviate the effect of dataset-induced variations, it employs a combination of three strategies: domain-invariant preprocessing, transfer learning, and domain-balanced variable hop fragment selection (DBVHFS). The domain-invariant preprocessing normalizes the PCG to reduce the stethoscope and environment-induced variations. The transfer learning utilizes a pre-trained model trained on diverse audio data to reduce the impact of data variability by generalizing feature representations. DBVHFS facilitates unbiased fine-tuning of the pre-trained model by balancing the training fragments across all domains, ensuring equal distribution from each class., Results: The proposed method is evaluated on six independent PhysioNet/CinC Challenge 2016 PCG databases using leave-one-dataset-out cross-validation. Results indicate that our system outperforms the existing study with a relative improvement of 5.92% in unweighted average recall and 17.71% in sensitivity., Conclusions: The methods proposed in this study address variations in PCG data originating from different sources, potentially enhancing the implementation possibility of automated cardiac screening systems in real-life scenarios., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background and Aims: In patients with NAFLD, liver fibrosis increases liver-related complications, but there is controversy about the increase in CVD. Based on a prospective cohort study, this study investigated the risk of cardiovascular disease due to liver fibrosis in patients with metabolic dysfunction-associated steatotic liver disease (MASLD)., Methods and Results: This study analyzed KCPS-II prospective cohort that tracked 104,399 people who participated in health check-ups at 18 institutions nationwide from 2004 to 2013. If the fatty liver index was 30 or higher, it was defined as SLD, and participants were classified into No-SLD, MASLD, MetALD, ALD, and Cryptogenic SLD. Liver fibrosis was defined by the FIB-4 index, and the occurrence of cardiovascular disease according to SLD classification was analyzed using Cox proportional model regression analysis. Out study included a total of 6,942 participants (6.6%) had MASLD, 6,694 (6.4%) had MetALD, 4,751 (4.6%) had ALD, and 382 (0.3%) had Cryptogenic SLD. For the cases of FIB-4 index ≥1.3, the multivariable-adjusted HR (95% CI) of cardiovascular disease was 2.27 (1.87-2-76) in MASLD, 1.67 (1.30-2.10) in MetALD, and 2.56 (1.99-3.30) in ALD, but it was 0.78 (0.19-3.10) in Cryptogenic&#95;SLD, which was not significant. The risk of cardiovascular disease according to the fibrosis stage classified by BARD also presented similar results., Conclusions: This prospective cohort study of Korean patients with newly defined MASLD, MetALD, and ALD with FIB-4 ≥ 1.3 at high risk of developing cardiovascular disease., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Cardiovascular diseases as a primary driver of global morbidity and mortality. Despite the array of therapeutic avenues in clinical practice, predominantly pharmaceutical and surgical interventions, they often fall short of fully addressing the clinical exigencies of cardiovascular patients. In recent years, nanocarriers have shown great potential in the treatment and diagnose of cardiovascular diseases. They can enhance drug targeting and bioavailability while reducing side effects. Additionally, by improving imaging and detection technologies, they enhance early diagnosis and disease monitoring capabilities. These advancements in technology offer new solutions for precision medicine in cardiovascular diseases, advancing treatment efficacy and disease management. Crafted from biomaterials, metals, or their amalgamations, these nanocarriers approximate the dimensions of biologically active molecules like proteins and DNA. Cardiovascular nanomedicine, in its infancy, has only recently burgeoned. Yet, with continual refinement in nanocarrier architecture, drug delivery mechanisms, and therapeutic outcomes, the potential of nanomedical technologies in clinical contexts becomes increasingly evident. This review aims to consolidate the strides made in nanocarrier research concerning the treatment and diagnose of cardiovascular diseases., Competing Interests: Declaration of competing interest The authors have no conflict of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The risk of sudden cardiac death (SCD) is increased during endurance competitive sports. Coronary artery disease (CAD) is the most common cause of SCD in master athletes ≥ 35 years old (MAs). To reduce the risk of SCD self-assessment of symptoms by questionnaire, and evaluation of cardiovascular risk-score, are recommended as pre-participation cardiovascular evaluation (PCVE). We aimed to examine whether PCVE predicts CVD in MAs with or without increased risk as measured by validated score instruments., We performed a single-site observational cohort study of healthy MAs based on findings at PCVE. They were allocated in two different groups: those MAs with reported symptoms on the questionnaire and/or with elevated cardiovascular risk score were allocated to a symptom group (SG), while MAs with no symptoms, nor raised risk score were defined as control group (CG). Thereafter, all were examined with extended examinations: resting-ECG, cardiorespiratory exercise testing and echocardiography., Total, 81 (18 women) MAs participated in the study. There were no differences at baseline between SG ( n  = 39) and CG ( n  = 42); sex ( p  = 0.11), age (55.0 ± 9.8 vs. 51.9 ± 11.1 years; p  = 0.18), maximal oxygen uptake (49.8 ± 7.6 vs. 51.6 ± 7.0 ml/kg/min; p  = 0.26), resting heart rate (61.4 ± 12.8 vs. 60.2 ± 11.0/min; p  = 0.66), training hours/week (7.0 ± 3.2 vs. 7.1 ± 3.1; p  = 0.88). After further examination, sixteen (20%) MAs were found with CVD: 12 in SG, 4 in CG ( p  = 0.024). The negative predictive value and specificity of the PCVE were 90% and 58%, respectively., Negative findings on PCVE by questionnaire and cardiovascular risk-score may be a strategy to exclude subjects from preparticipation screening, thus saving resources.

Background and Aims: Uric acid has been positively associated with the risk of developing heart failure in the general population. Nevertheless, it remains unclear whether hyperuricemia is an independent risk factor for heart failure and further contributes to the risk of heart failure among the already at-risk cardiovascular disease (CVD) population. This study aimed to evaluate the association between uric acid and incident heart failure in individuals with established CVD., Methods and Results: Included were 18,438 adults with established CVD but free of heart failure at baseline, from the Kailuan Study. Incident heart failure cases were ascertained by medical records. Cause-specific Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) of heart failure according to uric acid tertiles. Over a median follow-up of 6.1 years, we identified 1215 incident heart failure cases. Higher uric acid was associated with a higher risk of incident heart failure, with adjusted HR for the last vs. first tertile of 1.50 (95%CI:1.30-1.73). Higher uric acid concentrations were associated with an increased risk of heart failure in individuals with coronary heart disease, atrial fibrillation, and ischemic stroke, but not in those with hemorrhagic stroke. Moreover, the observed association between uric acid and heart failure risk was more pronounced in individuals diagnosed with heart failure with reduced ejection fraction subtype compared with heart failure with preserved ejection fraction., Conclusions: In individuals with CVD, uric acid was positively associated with the risk of heart failure, in a dose-response manner., Competing Interests: Declaration of competing Interest None reported., (Copyright © 2024 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Background and Aim: During the last few years, the Seven Countries Study of Cardiovascular Diseases (SCS) produced some new analyses dealing with the relationships of a dietary score, the pool of dietary fatty acids and serum cholesterol with major types of cardiovascular disease (CVD) mortality in 10 cohorts of 6 countries made of middle-aged men followed-up for 60 years until extinction. This sparse evidence is condensed here to provide a coherent view., Methods and Results: The Mediterranean Adequacy Index (MAI, a dietary score whose high levels depict the characteristics of the Mediterranean Diet), was highly and significantly associated in an inverse way, at country levels, with the Atherogenicity (ATI) and the Thrombogenicity (THI) indexes that included a series of dietary fatty acids. These indexes were highly and significantly associated in a direct way with country baseline serum cholesterol levels. Countries with high serum cholesterol had largely higher death rates from coronary heart disease (CHD) and lower rates from other heart diseases of uncertain etiology and stroke. The reverse was observed in countries with low serum cholesterol., Conclusion: The chain of diet, dietary fatty acids and serum cholesterol seems to be responsible in various ways for the different distribution of major CVD mortality subtypes in extincted cohorts., Competing Interests: Declaration of competing interest The authors report no relationships that could be construed as a conflict of interest. The authors certify that they complied with the Principles of Ethical Publishing Rules., (Copyright © 2024 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. All rights reserved.)

Traditionally, machine learning-based clinical prediction models have been trained and evaluated on patient data from a single source, such as a hospital. Cross-validation methods can be used to estimate the accuracy of such models on new patients originating from the same source, by repeated random splitting of the data. However, such estimates tend to be highly overoptimistic when compared to accuracy obtained from deploying models to sources not represented in the dataset, such as a new hospital. The increasing availability of multi-source medical datasets provides new opportunities for obtaining more comprehensive and realistic evaluations of expected accuracy through source-level cross-validation designs. In this study, we present a systematic empirical evaluation of standard K-fold cross-validation and leave-source-out cross-validation methods in a multi-source setting. We consider the task of electrocardiogram based cardiovascular disease classification, combining and harmonizing the openly available PhysioNet/CinC Challenge 2021 and the Shandong Provincial Hospital datasets for our study. Our results show that K-fold cross-validation, both on single-source and multi-source data, systemically overestimates prediction performance when the end goal is to generalize to new sources. Leave-source-out cross-validation provides more reliable performance estimates, having close to zero bias though larger variability. The evaluation highlights the dangers of obtaining misleading cross-validation results on medical data and demonstrates how these issues can be mitigated when having access to multi-source data., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Using a systematic meta-analysis, we investigated if patients with type 2 diabetes (T2D) and with varying baseline blood pressure (BP) differ in the cardiorenal benefits received from sodium-glucose co-transporter 2 inhibitors (SGLT-2is) and glucagon-like peptide 1 receptor agonists (GLP-1RAs). Design: Randomized, placebo-controlled, cardiovascular outcome trials (CVOTs) of SGLT-2is and GLP-1RAs were identified from MEDLINE, Embase, and the Cochrane Library up to April 2024. Hazard ratios (HRs) with 95% CIs were pooled. The differential treatment effect by baseline BP category within each trial was estimated as the ratio of the HR (RHR) and pooled. Results: Seventeen publications based on 9 unique CVOTs (4 SGLT-2is and 5 GLP-1RAs) were eligible. In participants with normal baseline BP, comparing SGLT-2is with placebo, the HRs (95% CIs) were 0.88 (0.79-0.97) for major adverse cardiovascular events (MACE), 0.73 (0.59-0.91) for heart failure (HF) hospitalization, 0.78 (0.65-0.94) for composite CVD death/HF hospitalization, and 0.55 (0.41-0.73) for composite renal outcome. The corresponding estimates for participants with higher baseline BP were 0.88 (0.81-0.96), 0.67 (0.57-0.79), 0.73 (0.65-0.82), and 0.61 (0.48-0.77), respectively. In participants with normal baseline BP, GLP-RAs had no strong effect on MACE, stroke and nephropathy, but reduced stroke and nephropathy risk in those with higher baseline BP. Estimated RHRs showed no statistical evidence that baseline BP modified the cardiorenal benefits of SGLT-2is and GLP-1RAs. Conclusions: In patients with T2D, the cardiorenal benefits of treatment with SGLT2-Is and GLP1-RAs were similar in patients with normal baseline BP compared to those with a higher baseline BP.

Background and Objective: Electrocardiogram (ECG) is one of the most important diagnostic tools for cardiovascular diseases (CVDs). Recent studies show that deep learning models can be trained using labeled ECGs to achieve automatic detection of CVDs, assisting cardiologists in diagnosis. However, the deep learning models heavily rely on labels in training, while manual labeling is costly and time-consuming. This paper proposes a new self-supervised learning (SSL) method for multilead ECGs: bootstrap each lead's latent (BELL) to reduce the reliance and boost model performance in various tasks, especially when training data are insufficient., Method: BELL is a variant of the well-known bootstrap your own latent (BYOL). The BELL aims to learn prior knowledge from unlabeled ECGs by pretraining, benefitting downstream tasks. It leverages the characteristics of multilead ECGs. First, BELL uses the multiple-branch skeleton, which is more effective in processing multilead ECGs. Moreover, it proposes intra-lead and inter-lead mean square error (MSE) to guide pretraining, and their fusion can result in better performances. Additionally, BELL inherits the main advantage of the BYOL: No negative pair is used in pretraining, making it more efficient., Results: In most cases, BELL surpasses previous works in the experiments. More importantly, the pretraining improves model performances by 0.69% ∼ 8.89% in downstream tasks when only 10% of training data are available. Furthermore, BELL shows excellent adaptability to uncurated ECG data from a real-world hospital. Only slight performance degradation occurs (<1% in most cases) when using these data., Conclusion: The results suggest that the BELL can alleviate the reliance on manual ECG labels from cardiologists, a critical bottleneck of the current deep learning-based models. In this way, the BELL can also help deep learning extend its application on automatic ECG analysis, reducing the cardiologists' burden in real-world diagnosis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Aims: The utilization of sulfonylurea (SU) for the management of Type 2 Diabetes Mellitus (T2DM) has witnessed a decline, attributed to the rising popularity of alternative medications and uncertainties surrounding the cardiovascular risk profile of SUs. This study aimed to investigate the potential association between SU intake and the incidence of cardiovascular events in patients with T2DM., Methods: A retrospective cohort study, based on a general practice (GP) registry, was designed, encompassing patients diagnosed with T2DM between 2005 and 2014.Follow-up persisted until the occurrence of a cardiovascular event, loss to follow-up, or until December 31, 2022. Comparative analyses were conducted between patients, receiving SU treatment and those without RESULTS: Data from a cohort comprising 5589 patients revealed that 13 % and 13.1 % of individuals in the comparator group and the SU group, respectively, experienced a cardiovascular event. However, no statistically significant elevation in the risk of cardiovascular events was observed after SU usage. Furthermore, the glycated haemoglobin (HbA1c) levels were significantly higher in the SU group (7.0 % vs. 6.4 %, p < 0.001)., Conclusions: The findings from this study indicate that the use of sulfonylureas SUs is not associated with a statistically significant increase in the risk of cardiovascular events among patients with type T2DM. These results contribute to the ongoing discourse on the safety and efficacy of SU therapy in diabetes management., Competing Interests: Conflict of Interest There were no conflicts of interest for this study., (Copyright © 2024 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)

Purpose of Review: Elevated lipoprotein(a) [Lp(a)] is a prevalent, independent, genetic risk factor for cardiovascular disease. Though crucial for adequate risk assessment, detection of individuals at increased risk because of elevated Lp(a) is severely lacking in practice. In this light, several consensus statements have recommended familial cascade screening strategies to increase detection of elevated Lp(a). This review aims to synthesize findings from recent research into the effectiveness of cascade screening for elevated Lp(a)., Recent Findings: Cascade screening is an effective method for identifying individuals with elevated Lp(a) and is superior to opportunistic screening. Cascade screening identifies approximately one new case of elevated Lp(a) ≥ 125 nmol/L for every two first-degree relatives screened. The number needed to screen (NNS) ranged from 1.3 to 2.9, depending on Lp(a) threshold values and selected population., Summary: Cascade screening appears to be a promising strategy for identifying individuals with elevated Lp(a). However, several challenges persist regarding the implementation of this strategy in clinical practice. Deciding on threshold values for initiating cascade screening, considering the implications of ethnicity-related variability of Lp(a) levels, and further research into the clinical relevance of cascade screening are crucial steps. Understanding these factors will be essential for optimizing cascade screening protocols and enhancing its effectiveness in clinical practice., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background and Objective: Electrocardiogram (ECG) analysis is crucial in diagnosing cardiovascular diseases (CVDs). It is important to consider both temporal and spatial features in ECG analysis to improve automated CVDs diagnosis. Significant progress has been made in automated CVDs diagnosis based on ECG with the continuous development of deep learning. Current most researches often treat 12-lead ECG signals as synchronous sequences in Euclidean space, focusing primarily on extracting temporal features while overlooking the spatial relationships among the 12-lead. However, the spatial distribution of 12-lead ECG electrodes can be more naturally represented using non-Euclidean data structures, which makes the relationships among leads more consistent with their intrinsic characteristics., Methods: This study proposes an innovative method, Convolutional Residual Graph Neural Network (Conv-RGNN), for ECG classification. The first step is to segment the 12-lead ECG into twelve single-lead ECG, which are then mapped to nodes in a graph that captures the relationships between the different leads through spatial connections, resulting in the 12-lead ECG graph. The graph is then used as input for Conv-RGNN. A convolutional neural network with a position attention mechanism is used to extract temporal sequence information and selectively integrate contextual information to enhance semantic features at different positions. The spatial features of the 12-lead ECG graph are extracted using the residual graph neural network., Results: The experimental results indicate that Conv-RGNN is highly competitive in two multi-label datasets and one single-label dataset, demonstrating exceptional parameter efficiency, inference speed, model performance, and robustness., Conclusion: The Conv-RGNN proposed in this paper offer a promising and feasible approach for intelligent diagnosis in resource-constrained environments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Cell-derived extracellular vesicles (EVs) have emerged as a promising non-invasive liquid biopsy technique due to their accessibility and their ability to encapsulate and transport diverse biomolecules. EVs have garnered substantial research interest, notably in cardiovascular diseases (CVDs), where their roles in pathophysiology and as diagnostic and prognostic biomarkers are increasingly recognized. This review provides a comprehensive overview of EVs, starting with their origins, followed by the techniques used for their isolation and characterization. We explore the diverse cargo of EVs, including nucleic acids, proteins, lipids, and metabolites, highlighting their roles in intercellular communication and as potential biomarkers. We then delve into the application of genomics, transcriptomics, proteomics, and metabolomics in the analysis of EVs, particularly within the context of CVDs. Finally, we discuss how integrated multi-omics approaches are unveiling novel biomarkers, offering fresh insights into the diagnosis and prognosis of CVDs. This review underscores the growing importance of EVs in clinical diagnostics and the potential of multi-omics to propel future advancements in CVD biomarker discovery., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In 2020, the NIH and FDA issued guidance documents that laid the foundation for human subject research during an unprecedented pandemic. To bridge these general considerations to actual applications in cardiovascular interventional device trials, the PAndemic Impact on INTErventional device ReSearch (PAIINTERS) Working Group was formed in early 2021 under the Predictable And Sustainable Implementation Of National CardioVascular Registries (PASSION CV Registries). The PAIINTER's Part I report, published by Rymer et al. [5], provided a comprehensive overview of the operational impact on interventional studies during the first year of the Pandemic. PAIINTERS Part II focused on potential statistical issues related to bias, variability, missing data, and study power when interventional studies may start and end in different pandemic phases. Importantly, the paper also offers practical mitigation strategies to adjust or minimize the impact for both SATs and RCTs, providing a valuable resource for researchers and professionals involved in cardiovascular clinical trials., Competing Interests: Declaration of competing interest The authors of this publication include representatives employed by Boston Scientific, Abbott Cardiovascular, Edwards Lifesciences, FDA, Medtronic, Columbia University, Yale University, and Duke University., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Older adults with intellectual disabilities (ID) have a high risk of cardiovascular diseases (CVD). At the same time, challenging diagnostic work-up increases the likelihood of underdiagnosis of CVD in this population. To limit this underdiagnosis, it would be beneficial to use objective measures such as the electrocardiogram (ECG). However, little is known about the feasibility of ECG recording and the prevalence of ECG abnormalities in this population. Therefore, the aims of this study were to investigate the feasibility of resting ECG recording, to study the prevalence of ECG abnormalities, and to compare the frequency of ECG abnormalities with medical records in older adults with ID., Method: A cross-sectional study was performed within a cohort of older adults (≥60 years) with ID as part of the Healthy Ageing and Intellectual Disabilities (HA-ID) study. A resting 12-lead ECG was attempted, and the ECG recording was considered feasible if the recording could be made and if the ECG could be interpreted by a cardiologist and the Modular ECG Analysis System (MEANS). ECGs were assessed for the presence of ECG abnormalities and medical record review was performed. If the cardiologist or MEANS concluded that there was evidence of myocardial infarction, atrial fibrillation or QTc prolongation on the ECG in the absence of this ECG diagnosis in the participant's medical record, this was classified as a previously undiagnosed ECG diagnosis., Results: ECG recording was feasible in 134 of the 200 participants (67.0%). Of these 134 participants (70.6 ± 5.8 years; 52.2% female), 103 (76.9%) had one or more ECG abnormality, with the most prevalent being prolonged P-wave duration (27.6%), QTc prolongation (18.7%), minor T-wave abnormalities (17.9%), first degree atrioventricular block (12.7%) and myocardial infarction (6.7%). Eight out of 9 (88.9%) myocardial infarctions and all cases of (significant) QTc prolongation (100%) were previously undiagnosed., Conclusions: This study showed that ECG recording is feasible in the majority of older adults with ID and revealed a substantial underdiagnosis of ECG abnormalities. These results stress the importance of ECG recording and warrant further research into the yield of opportunistic ECG screening in older adults with ID., (© 2024 The Author(s). Journal of Intellectual Disability Research published by John Wiley & Sons and MENCAP.)

Rapid and accurate identification of cardiovascular diseases (CVDs) are crucial for timely medical interventions and improved patient outcomes. Fibrinogen (Fib) has emerged as a valuable biomarker for CVDs, playing a significant role in their early detection. Elevated levels of Fib are associated with an increased risk of developing CVD, highlighting its importance for more precise diagnosis and effective treatment strategies. In recent years, significant advancements have been made in developing biosensor-based approaches for detecting Fib, offering high sensitivity and specificity. This review aims to explore the impact of Fib on cardiovascular conditions, assess the current advancements, and discuss the future potential of biosensors in Fib research for diagnosing cardiovascular disorders. Furthermore, we evaluate various biosensor techniques, including optical, electrochemical, electronic, and gravimetric methods, in terms of their utility for measuring Fib in clinical samples such as serum, plasma, whole blood, and other body fluids. A comparative analysis of these techniques is conducted based on their performance characteristics. By providing a comprehensive overview of the relationship between Fib and cardiovascular ailments, this review aims to clarify the advancements in biosensor technology for Fib detection. The comparison of different biosensor techniques will aid researchers and clinicians in selecting the most suitable approach for their specific diagnostic needs. Ultimately, integrating biosensors into clinical practice has the potential to revolutionize the detection and management of CVDs, leading to improved patient care and outcomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Aims: Skin perfusion pressure (SPP) and ankle-brachial index (ABI) are useful in screening for peripheral arterial disease in patients undergoing hemodialysis (HD). We compared the prognostic abilities of the SPP and ABI in predicting the composite outcomes of mortality and atherosclerotic vascular events., Methods: This single-center prospective cohort study enrolled 258 patients undergoing HD. The patients with SPP and ABI measurements were divided into tertiles. Log-rank tests, Cox regression analyses, and discrimination parameters were used for comparisons., Results: Over a median follow-up period of 3.7 (1.4-5.0) years, 119 composite events were recorded. The incidence rates of composite events were 27.5, 13.3, and 9.1 per 100 person years, respectively, across the SPP tertiles (log-rank: p＜0.001), and 23.2, 13.2, and 11.6 per 100 person years across the ABI tertiles (p=0.003). With the 3rd tertiles as references, the 1st tertiles of the SPP and ABI were significantly associated with the composite outcome (adjusted hazard ratio [aHR]: 2.58, 95% confidence interval [CI]: 1.57-4.23 and aHR: 1.70, 95% CI: 1.06-2.73, respectively). Adding the tertiles of the SPP to a predictive model with established risk factors significantly improved the model performance. This improvement was larger than that of the ABI in terms of net reclassification (0.330 vs. 0.275) and integrated discrimination (0.045 vs. 0.012). Furthermore, in patients with a normal ABI, the 1st SPP tertile (＜71 mmHg) was significantly associated with the outcome (aHR, 1.97; 95% CI, 1.13-3.41) when compared to the 3rd tertile., Conclusions: Even patients with a normal ABI have a poor prognosis if their SPP levels are low. SPP outperformed ABI in predicting mortality and cardiovascular outcomes in HD patients.

Aims: The objective of this research is to develop an effective cardiovascular disease prediction framework using machine learning techniques and to achieve high accuracy for the prediction of cardiovascular disease., Methods: In this paper, we have utilized machine learning algorithms to predict cardiovascular disease on the basis of symptoms such as chest pain, age and blood pressure. This study incorporated five distinct datasets: Heart UCI, Stroke, Heart Statlog, Framingham and Coronary Heart dataset obtained from online sources. For the implementation of the framework, RapidMiner tool was used. The three-step approach includes pre-processing of the dataset, applying feature selection method on pre-processed dataset and then applying classification methods for prediction of results. We addressed missing values by replacing them with mean, and class imbalance was handled using sample bootstrapping. Various machine learning classifiers were applied out of which random forest with AdaBoost dataset using 10-fold cross-validation provided the high accuracy., Results: The proposed model provides the highest accuracy of 99.48% on Heart Statlog, 93.90% on Heart UCI, 96.25% on Stroke dataset, 86% on Framingham dataset and 78.36% on Coronary heart disease dataset, respectively., Conclusions: In conclusion, the results of the study have shown remarkable potential of the proposed framework. By handling imbalance and missing values, a significantly accurate framework has been established that could effectively contribute to the prediction of cardiovascular disease at early stages., (© 2024 The Author(s). ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Background: The prognosis of individuals with and without an established heart failure (HF) diagnosis and similarly elevated N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels is not well-known., Methods and Results: CANVAS (Canagliflozin Cardiovascular Assessment Study) trial participants were stratified according to baseline NT-proBNP quartiles and history of HF at baseline. Adjusted event rates per 1000 patient-years of follow-up for hospitalizations for HF, cardiovascular mortality, and kidney events were assessed, and hazard ratios (HR) were calculated using Cox proportional hazard models. Of the 3507 participants with available NT-proBNP concentrations, 471 (13.4%) had history of HF. The incidence rate per 1000 patient-years for hospitalizations for HF increased across the NT-proBNP quartiles in patients with (0, 2.8, 13.4, and 40.1; P < .001) and without (1.8, 3.1, 6.0, and 19.1; P < .001) HF, with a significantly higher risk in patients with HF compared with those without (with HF, quartile 3 HR 9.28 [interquartile range (IQR) 1.15-75.05]; P = .04; without HF, quartile 4 HR 4.86 [95% CI, 2.08-11.35]; P < .001). A similar higher risk for kidney events was seen in HF patients (with HF, quartile 4 HR 6.94 [95% CI, 2.66-18.08]; P = .001; without HF, quartile 4 HR 4.85 [95% CI, 3.02-7.80]; P = .001). Similar trends were seen for cardiovascular mortality., Conclusions: Among patients with type 2 diabetes and cardiovascular risk, an elevated NT-proBNP level was associated with worse HF and kidney outcomes in general, regardless of history of HF; however, the presence of a clinical diagnosis of HF at baseline was associated with an incrementally higher risk, particularly in higher NT-proBNP quartiles., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: The triglyceride glucose (TyG) index is a dependable indicator of insulin resistance (IR), serves as a valuable biomarker for identifying obstructive sleep apnea (OSA) and predicting its comorbidities. Both OSA and the TyG index are significantly related to the incidence and development of cardiovascular disease (CVD). We focus on investigating the relationship between the TyG index and the incidence of CVD risk in OSA., Methods: The TyG index, homeostatic model assessment of IR (HOMA-IR) index, and polysomnography were assessed in 191 participants with OSA and without pre-existing CVD. To estimate the lifetime CVD risk, we employed the 'Prediction for Atherosclerotic CVD Risk in China' equation. The TyG index's association with CVD risk was scrutinized using multivariable logistic regression models, contrasting it with the HOMA-IR index. We compared the predictive power for high lifetime CVD risk of the TyG index and the HOMA-IR index using receiver-operating characteristic (ROC) curve analysis., Results: A total of 89 participants had high lifetime CVD risk. In fully adjusted model and additionally adjusted for HOMA-IR index, participants situated within the fifth quantile of the TyG index exhibited an increased lifetime CVD risk, with OR of 4.32 (95% CI, 1.19-15.67). The TyG index demonstrated significant predictive power for high lifetime CVD risk across varying severities of OSA and outperformed the HOMA-IR index, as evidenced by a larger area under the ROC curve., Conclusion: The TyG index, independent of the HOMA-IR index and obesity, was linked to an increased lifetime CVD risk. In predicting cardiovascular outcomes, the TyG index could potentially outperform the HOMA-IR index among individuals with OSA., Competing Interests: Declarations. Ethics approval: This study protocol was approved by the ethics committees of PUMCH (JS-3573), and informed consent for involvement in the study was obtained from each participant. Conflict of interest: The authors declare that they have no competing interests., (© 2024. The Author(s).)

Background: The inverse relationship between serum Klotho levels and systemic inflammation, particularly C-reactive protein (CRP), has been suggested in limited studies. However, the association within a large and diverse population remains underexplored., Methods: We conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) to investigate the association between serum Klotho levels and CRP among a nationally representative sample of the US population. Multiple linear regression analyses were performed to assess this relationship while adjusting for relevant covariates. Stratified analysis with interaction, restricted cubic splines (RCS) were employed to support the research objectives., Results: A total of 5901 participants had a mean age of 57.9 ± 11.0 years, with 49.4% of them being male and 50.6% of them being female. A negative association between serum Klotho and CRP was revealed in the fully adjusted model (β -0.26; 95% CI -0.41∼-0.11). When serum Klotho was taken as quartiles with Q1 as reference, the adjusted β that were lowest in Q4 were - 0.1 (95% CI -0.16∼-0.04, p-value = 0.002) in model 4, respectively. These statistics were robust in stratified analyses., Conclusion: While our study demonstrates an inverse association between serum Klotho levels and CRP, suggesting a potential cardioprotective role of Klotho, it is important to note that our cross-sectional design does not permit the establishment of causality. Therefore, we cannot definitively conclude that increasing Klotho levels will directly reduce cardiovascular risk. Our findings do, however, highlight the need for further research to explore the potential of Klotho as a therapeutic target for cardiovascular health., Competing Interests: Declarations. Ethics approval and consent to participate: The NCHS Research Ethics Review Board approved the NHANES study protocol, and participants provided written informed consent at enrollment (the website is https://www.cdc.gov/nchs/nhanes/irba98.htm ). Ethical approval and consent were not required as this study was based on publicly available de-identified data. Consent for publication: not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

This narrative review describes the impetus for health screening for non-communicable diseases in dental settings and highlights important considerations for evaluating such interventions. Real world cases are presented that showcase health screening interventions implemented in the UK. Non-communicable diseases including diabetes and cardiovascular disease are a global public health challenge. They are largely preventable by implementing lifestyle changes such as healthy eating and participation in physical activity, regular health screening for disease prevention, and/or early initiation of treatment. Hypertension case finding and control is one of the key five areas of focus for adult health, and oral health and diabetes are two of five key clinical areas for children and young people where efforts should be focused to intervene, improve outcomes and reduce inequalities. Links between oral and chronic diseases have been discussed in recent years. Therefore, screening for diabetes and cardiovascular disease has become of greater relevance to the dental profession. There is emerging evidence indicating that screening for the risk factors of cardiovascular diseases and diabetes in dental settings shows promise for improving health outcomes and may offer a cost-effective preventive approach for the detection of diabetes. Real-world services implementing health screening in dental settings have highlighted possibilities for the future and highlight the potential for the role of the dental team in detecting chronic diseases., (Copyright© 2024 Dennis Barber Ltd.)

Background: Respiratory viruses are linked to cardiovascular complications. We aim to compare cardiovascular complications due to COVID-19, influenza and RSV., Methods: We analyzed cross-sectional data from hospitalized children and young adults (≤ 20 years) from 2020 and 2021 using National Inpatient Sample (NIS). We included individuals hospitalized for COVID-19, RSV, and influenza, and weighted data were used to compare cardiovascular complications., Results: Of 212,655 respiratory virus admissions, 85,055 were from COVID-19, 103,185 were from RSV, and 24,415 were from influenza. Myocarditis was higher in COVID-19 [0.9%, n = 740] as compared to influenza [0.2%, n = 55] and RSV [0.1%, n = 65]. In the adjusted logistic regression, the odds of myocarditis was 61% lower in influenza [aOR = 0.39 (0.20-0.76), P = 0.006], and 85% lower in RSV [aOR = 0.15 (0.07-0.34) P < 0.001] as compared to COVID-19. Bradyarrhythmias/heart block was higher in COVID-19 [0.8%, n = 690] versus influenza [0.5%, n = 110] and RSV [0.2%, n = 205]. After adjusting for confounders for bradyarrhythmias/heart block, compared to COVID-19, the odds were 49% lower in RSV [aOR = 0.51 (0.33-0.80), P = 0.004] but no statistically significant difference in influenza [aOR = 0.79 (0.48-1.31), P = 0.374] was seen. Tachyarrhythmias, sudden cardiac arrest, and in-hospital mortality showed no differences after adjusting for covariates., Conclusion: Individuals with COVID-19 infection are more likely to develop cardiovascular complications compared to influenza and RSV, highlighting the need for higher index of suspicion and prompt treatment, as well as steps to limit infection and transmission of this virus in children., Competing Interests: Declarations. Ethics approval and consent to participate: Approval from an institutional review board and informed consent were not required for this study, as it adheres to the regulations set forth in 45 CFR §46, which exempts certain research involving publicly available or de-identified data from these requirements. As this study utilized publicly available de-identified data, it received expedited review approval from the University of California San Francisco, Fresno Community Medical Regional Center. IRB No: 2023024. The need for informed consent to participate was waived by the ethics committee of University of California San Francisco, Fresno Community Medical Regional Center. IRB No: 2023024. The authors listed in this manuscript are not employed by any government agency whose primary role is not research or education. Moreover, none of the authors are presenting this manuscript as an official representative or on behalf of the government. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Aims: The purpose of this prospective cohort study was to examine the association of Life Essential 8 (LE8), the recently updated algorithm for quantifying cardiovascular health (CVH) by the American Heart Association (AHA), with the risk of mortality in Chronic Obstructive Pulmonary Disease (COPD) patients., Methods: Data from the National Health and Nutrition Examination Survey (NHANES) 2007-2012 and the National Death Index mortality data up to December 31, 2019, were included in this cohort analysis. To characterize the relationship between LE8 and CVD and all-cause mortality as well as assess any potential nonlinear relationships, the limited cubic spline mixed with the Cox proportional hazards model was used., Results: The final analysis included 785 subjects. The weighted mean age of the study population was 59 years, and 479 were male. In the overall population, every 10-point increase in the LE8 score was individuals with associated with reduced risks of 4% for CVD mortality; moderate CVH had a 23% lower risk of COPD, while high CVH was linked to a 40% lower risk compared to low CVH. Among the COPD individuals, every 10-point increase in the LE8 score was associated with reduced risks of 4% for all-cause mortality,8% for CLRD mortality, and 12% for cancer mortality., Conclusion: This study demonstrates that low levels of LE8 were associated with increased risks of all-cause and cause-specific mortality in COPD individuals., Competing Interests: The authors declare that they have no competing interests., (© 2024 Sun et al.)

Systemic lupus erythematosus (SLE) poses a diagnostic challenge due to its heterogeneity. This study examines the cardiac complications of SLE comprehensively, covering pericarditis, myocarditis, pleural effusion, valvular disease, atherosclerosis, and cardiac arrhythmias. Nearly one-third of SLE-related deaths are attributed to cardiovascular diseases, necessitating a deeper understanding of cardiac pathophysiology. The impact of SLE on the cardiovascular system manifests in various ways, including recurrent and resistant pericarditis, severe myocarditis, and pleural effusion. Valvular diseases, atherosclerosis, and cardiac arrhythmias are prevalent, with immune complex deposition playing a role in atherosclerosis. Diagnostic criteria involve clinical features, laboratory findings, and autoantibodies, emphasizing the need for early diagnosis and a multidisciplinary diagnostic approach. The review explores pharmacological and non-pharmacological modalities for managing cardiac manifestations in SLE. Recommendations include NSAIDs, colchicine, and proton pump inhibitors for acute pericarditis, while selective immunosuppressive therapy is emerging for myocarditis. Valvular diseases require individualized treatment approaches, and careful corticosteroid management is crucial to avoid increased cardiovascular events. Anti-malarial therapy, particularly hydroxychloroquine, shows promise in mitigating cardiovascular risk factors. Non-pharmacological modifications, such as diet, exercise, and smoke cessation, significantly contribute to cardiovascular health in SLE patients. Adjuvant therapies involving glutathione and glutathione peroxidase focus on redox balance, offering potential interventions. This integrated approach combines diagnostic insights with diverse treatment modalities, providing a holistic strategy for managing cardiac complications in SLE. Ongoing research is essential to refine these strategies and optimize individualized treatment plans for improved patient outcomes., (© 2024 the author(s), published by De Gruyter.)

Purpose: The aim of this research was to investigate the relationship between socio-economic inequalities and fatal and non-fatal cardiovascular events., Methods: A systematic review of recently published cohort studies and a meta-analysis of relative risk (RR) of low compared with high socio-economic status (SES) in relation to cardiovascular incidence and mortality was conducted. Supplementary evaluations were conducted considering different proxies of SES in relation to different types of cardiovascular disease (CVD)., Results: We identified 17 studies including approximately 26.5 million of participants with more than 900,000 CVD events. We estimated a 50% increased CVD risk for low SES with respect to high SES (RR = 1.49 [95% confidence interval: 1.26, 1.78]). For sex-specific risk, we estimated a 79% increased CVD risk for women of low SES (RR = 1.79 [1.30, 2.46]). In men, the same investigation found a 45% increased CVD risk (RR = 1.45 [1.09, 1.92]). We reported that low education (RR = 1.56 [1.27, 1.91]), increased CVD risk the most, more than low income (RR = 1.38 [1.12, 1.70])., Conclusion: Although not statistically significant, women of low SES were at higher CVD risk than men. CVD risk was more relevant to educational inequality than economic inequality., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Background: Globally, cardiovascular disease (CVD) constitutes the primary cause of death, with insulin resistance (IR), measured by the triglyceride-glucose (TyG) index, and visceral obesity, reflected by the Chinese Visceral Adiposity Index (CVAI), as key contributors. However, the relationship between the TyG index and CVAI regarding CVD risk remains insufficiently understood. This research investigates the interactive impact of the TyG index and CVAI on the risk of cardiovascular disease., Methods: We analyzed data from 8,358 participants from the China Health and Retirement Longitudinal Study (CHARLS) over a 9-year follow-up period. Participants were classified into four groups based on median TyG index (8.59) and CVAI values (101.26), and baseline characteristics were summarized. Missing data were addressed using multiple imputation by chained equations (MICE). Cox proportional hazards models assessed associations between TyG index, CVAI, CVD, coronary heart disease (CHD), and stroke risks, with Kaplan-Meier analysis used for cumulative hazard. Interaction effects were evaluated using both multiplicative and additive measures. Subgroup analyses by age, gender, and clinical conditions were conducted to explore interaction effects across different populations. Sensitivity analyses re-tested models, excluding the covariates BMI and diabetes, using tertiles for classification, and re-evaluating imputed data., Results: Over the 9-year follow-up, 1,240 participants (14.8%) developed CVD, including 896 cases of CHD and 475 strokes. Kaplan-Meier curves indicated that participants with low TyG index but high CVAI had the highest cumulative hazard of CVD. Cox regression showed that this group had the highest CVD risk (HR = 1.87, 95% CI: 1.57-2.24), followed by those with both high TyG index and high CVAI (HR = 1.75, 95% CI: 1.49-2.06). Interaction analysis revealed a negative interaction effect between high TyG and high CVAI on CVD and CHD risks, with no significant effect on stroke. Subgroup and sensitivity analyses further confirmed these findings, showing consistent results across demographic groups and under various analytical conditions., Conclusion: This study suggests that the interaction between IR (TyG index) and visceral fat accumulation (CVAI) plays a complex role in CVD risk, with a potential antagonistic effect observed between high TyG and high CVAI on CVD events. These findings highlight the importance of considering both IR and visceral adiposity in CVD risk assessments to improve the identification of high-risk individuals., Competing Interests: Declarations. Ethics approval and consent to participate: This study was approved by the Ethics Review Committee of Peking University (IRB00001052-11015), and written informed consent was obtained from all participants. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

To examine the relationship between age at diagnosis of type 2 diabetes (T2DM) with cardiovascular and all-cause mortality in the U.S. population. Data was used from NHANES 1999 ~ 2018, which were screened to include a total of 8,654 participants with a diagnosis of diabetes for the study. We estimated the association between age at diagnosis and cardiovascular and all-cause mortality using weighted multivariate Cox regression analyses. Subgroup analyses and sensitivity analyses were performed to ensure the robustness of the data analysis. The number of participants diagnosed with diabetes at ages < 40, between 40 and 59, and > 60 are 1,492, 3,970, and 3,192, respectively, with median ages of 44.04, 57.59, and 72.24. Among patients diagnosed with T2DM, the relative risk of all-cause mortality increased with younger age at diagnosis: compared to patients with late-onset diabetes (age at type 2 diabetes diagnosis ≥ 60), the hazard ratio for all-cause mortality was 2.72 (95% CI 1.83-4.05) in those with early-onset diabetes (age at type 2 diabetes diagnosis < 40). Similarly, the risk of cardiovascular disease death was observed to be a higher relative risk with younger age at diagnosis. Exposure-effect analysis indicated that younger age at diagnosis is associated with higher risk of all-cause mortality. Subgroup analysis found that the association between age at diagnosis and cardiovascular and all-cause mortality was stronger in the current smokers and hypertensive population. The results of this study suggest that younger age at diagnosis of T2DM is associated with higher risk of death in patients. Younger patients diagnosed with T2DM had a higher risk of cardiovascular and all-cause mortality. These findings strengthen the understanding of the risk of death from T2DM and emphasize the importance of early prevention of diabetes., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethics statement: This study was reviewed and approved by the National Center for Health Statistics Research Ethics Review Board, and written informed consent was obtained from all NHANES participants., (© 2024. The Author(s).)

Background: Insulin resistance coexist with many metabolic disorders, whether these disorders were promotors or pathway-factors for the association of insulin resistance and cardiovascular disease (CVD) remained unclear. We aimed to investigate the pathways related to elevated the triglyceride-glucose (TyG) index and pathways through elevated TyG index to the occurrence of CVD in Chinese adults., Methods: A total of 96,506 participants were enrolled from the Kailuan study. Bayesian network model with the max-min hill climbing algorithm and maximum likelihood estimation was applied to identify factors and pathways related to the TyG index, and quantitatively infer the impact of associated factors on elevated TyG index and the occurrence of CVD by computing conditional probabilities., Results: A final Bayesian network was constructed with 14 nodes and 25 arcs, creating 28 pathways related to elevated TyG index and 8 pathways from elevated TyG index to CVD. Elevated TyG index was causally associated with CVD, the condition probability was 11.9%. Pathways to elevated TyG index were mainly through unhealthy lifestyles and the subsequent increase in lipid profiles, especially smoking and low-density lipoprotein cholesterol. The most important pathway from elevated TyG index to CVD was through overweight/obesity, hypertension, and chronic kidney disease, with a condition probability of 18.5%. The maximum relative change rate related to elevated TyG index was observed for overweight/obesity (64.3%)., Conclusions: Elevated TyG index was causally associated with the risk of CVD, a combined control of lifestyles and metabolic factors may contribute to the reduction of TyG index and the prevention of CVD., Competing Interests: Declarations. Ethics approval and consent to participate: The study was performed according to the guidelines of the Helsinki Declaration and was approved by the Ethics Committee of Kailuan General Hospital (approval number: 2006-05). All participants were agreed to take part in the study and provided informed written consent. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. Disclosure: None., (© 2024. The Author(s).)

Objectives: This study aimed to investigate the impact of hepatic steatosis on cardiometabolic outcomes in young adults with prediabetes., Methods: A nationwide cohort study was conducted with 896,585 young adults under 40 years old without diabetes or previous history of cardiovascular disease. Hepatic steatosis was identified using a fatty liver index of ≥ 60. The outcomes of this study were incident diabetes (DM) and composite major adverse cardiovascular events (MACE), including myocardial infarction, stroke, or cardiovascular death., Results: During a median follow-up of 11.8 years, 27,437 (3.1%) incident DM cases and 6,584 (0.7%) MACE cases were recorded. Young adults with prediabetes had a significantly higher risk of incident DM (hazard ratio [HR]: 2.81; 95% confidence interval [CI]: 2.74-2.88; P-value: <0.001) and composite MACE risk (HR: 1.10; 95% CI: 1.03-1.17; P-value: 0.003) compared to individuals with normoglycemia, after adjusting for relevant covariates. Stratification based on hepatic steatosis showed that the combination of prediabetes and hepatic steatosis posed the highest risk for these outcomes, after adjusting for relevant covariates. For incident DM, the HRs (95% CI; P-value) were: 3.15 (3.05-3.26; <0.001) for prediabetes without hepatic steatosis, 2.89 (2.78-3.01; <0.001) for normoglycemia with hepatic steatosis, and 6.60 (6.33-6.87; <0.001) for prediabetes with hepatic steatosis. For composite MACE, the HRs (95% CI; P-value) were 1.05 (0.97-1.13; 0.235) for prediabetes without hepatic steatosis, 1.39 (1.27-1.51; <0.001) for normoglycemia with hepatic steatosis, and 1.60 (1.44-1.78; <0.001) for prediabetes with hepatic steatosis., Conclusions: Prediabetes and hepatic steatosis additively increased the risk of cardiometabolic outcomes in young adults. These findings hold significance for physicians as they provide insights into assessing high-risk individuals among young adults with prediabetes., Competing Interests: Declarations. Ethics approval and consent to participate: The study protocol adhered the ethical guidelines of the Declaration of Helsinki and received approval from the Institutional Review Board of Chonnam National University Hwasun Hospital (CNUHH-2022-109). Informed consent was waived due to participants deidentification. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Background: Despite widespread use of high-intensity statin monotherapy, achieving target LDL-C levels and reducing cardiovascular events in patients with or at high risk of developing ASCVD remains challenging. Our study measured the effects of low/moderate-intensity statins and ezetimibe combination therapy compared to high-dose statin monotherapy on major adverse cardiovascular events (MACEs) and coronary atherosclerotic plaque reduction., Methods: We searched PubMed, Scopus, Web of Science, and Cochrane CENTRAL register of trials for studies comparing the combination therapy to high-intensity statin monotherapy in terms of MACEs and coronary atherosclerotic plaque reduction. The primary outcome was a composite of cardiovascular death or major cardiovascular events (MI, HF, Revascularization, or non-fatal stroke). Other outcomes included other MACEs, lipid-lowering efficacy, and safety outcomes. A protocol was registered to PROSPERO under registration number [CRD42024545807]., Results: 15 studies encompassing 251,450 participants were included in our meta-analysis. In our pooled analysis of observational studies, combination therapy was associated with lower rates of the primary composite outcome (HR = 0.76, CI 95% [0.73, 0.80]), cardiovascular death (HR = 0.80, CI 95% [0.74, 0.88]), all-cause death (HR = 0.84, CI 95% [0.78, 0.91]), and non-fatal stroke (HR = 0.81, CI 95% [0.75, 0.87]). However, the pooled analysis of RCTs did not demonstrate a statistically significant difference between both arms concerning clinical endpoints. Combination therapy had a higher number of patients with LDL-C < 70 mg/dL (RR = 1.27, CI 95% [1.21, 1.34]), significantly lowered LDL-C (MD = -7.95, CI 95% [-10.02, -5.89]) and TC (MD = -26.77, CI 95% [-27.64, -25.89]) in the pooled analysis of RCTs. In terms of safety, the combination therapy lowered muscle-related adverse events (RR = 0.52, CI 95% [0.32, 0.85]) and number of patients with liver enzyme elevation (RR = 0.51, CI 95% [0.29, 0.89]) in the pooled analysis of RCTs and was associated with lower rates of new-onset diabetes (HR = 0.80, CI 95% [0.74, 0.87]) in the pooled analysis of observational studies., Conclusion: Evidence from RCTs indicates that low/moderate statin therapy in combination with ezetimibe has a superior lipid-lowering effect and reduces side effects compared to high-dose statins. Observational studies suggest improved clinical outcomes but need to be corroborated by large, outcomes-powered RCTs over longer follow-up periods., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Purpose of Review:  Ceramides are lipid species that play several physiological roles in the body, including stress response, inflammation, and apoptosis, and their involvement in lipid metabolism and energy production makes them crucial in the pathophysiology of heart failure (HF)., Recent Findings:  Several species of ceramides and ceramide signatures have recently been investigated as possible biomarkers of cardiovascular disease (CVD), and risk scores have demonstrated prognostic value in stratifying patients by risk and possibly predicting adverse cardiac events. With growing interest in targeting metabolic dysfunction, understanding the role of ceramides in CVD also opens the possibility of novel therapeutics that target ceramide metabolism to improve cardiac function and cardiac outcomes in patients.  Understanding the role of ceramides in CVD opens the possibility of novel diagnostics and theragnostic targeting ceramide metabolism to improve cardiac function and cardiac outcomes in patients with heart failure., Competing Interests: Declarations Competing Interests Dr. Tang has served as consultant for Sequana Medical, Cardiol Therapeutics, Genomics plc, Zehna Therapeutics, WhiteSwell, Boston Scientific, CardiaTec Biosciences, Bristol Myers Squibb, Alleviant Medical, Alexion Pharmaceuticals, Salubris Biotherapeutics, BioCardia, and has received honorarium from Springer, Belvoir Media Group, and American Board of Internal Medicine. All other authors have no relationships to disclose., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)