Cardiovascular Disease In Type Research Articles

The Association between Dietary Acid Load and Non-Communicable Diseases: A Cohort Study in Shahrekord

Background and aim: It has recently been suggested that acid-base imbalances may play a role in some types of cardiovascular diseases and metabolic disorders. The aim of this study is to investigate the association between dietary acid load and common non-communicable diseases (NCDs). Methods: In this cross-sectional study, 1800 participants were enrolled in a cohort study in Shahrekord. Data were collected using a Food Frequency Questionnaire (FFQ). The potential renal acid load (PRAL) was calculated using the intestinal absorption of five nutrients including protein, potassium, phosphorus, magnesium, and calcium. The association of dietary acid load with NCDs was investigated in two models. Then, the raw model was adjusted by including calorie intake and age; after adjusting the effect of the two variables, the association between dietary acid load and the studied NCDs was not statistically significant. Results: The mean age of the participants was 51.49±9.27 years, and 941 (52.27%) of them were female. Mean±SD acid load score was -6.88±23.23. The results showed that there was a significant association between dietary acid load and age (P=0.005), weight (P=0.0001), waist circumference (P=0.016), hip circumference (P=0.0001), waist-to-hip ratio (P=0.01), body mass index (P=0.004), and triglyceride (P=0.012). In the raw model, a significant association was observed between dietary acid load and hypertension (OR=0.57, 0.39-0.8). Conclusion: In this study, no significant association was observed between dietary acid load and NCDs, but the variable was associated with weight and body mass index as the most important risk factors for NCDs.

Prognostic properties of biomarkers in COVID-19 infection and concomitant chronic coronary syndromes

Background. The novel coronavirus disease 2019 (COVID-19), caused by a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become an unprecedented challenge for the health care system and has taken a leading position among infectious diseases due to the rapid spread and development of complications from various body systems. The problem of cardiac comorbidity in COVID-19 has several aspects: the impact of concomitant cardiovascular diseases on the incidence of a new viral infection, its severity and risk of mortality, as well as possible side effects of a number of drugs traditionally used to treat certain types of cardiovascular diseases. SARS-CoV-2 is not only a pneumonia pathogen, but also causes serious systemic consequences. Patients with cardiovascular diseases and risk factors for cardiovascular complications, such as hypertension and coronary heart disease, are more exposed to fatal consequences of COVID-19. In addition, a significant proportion of patients develop COVID-associated myocardial injury, which significantly increases the risk of in-hospital mortality. The purpose of the study was to investigate the prognostic role of individual biomarkers in patients with COVID-19-associated pneumonia on the background of chronic coronary syndromes. Materials and methods. This study was defined as an open-label, non-randomized, controlled, comparative one in parallel groups. 124 patients with COVID-19-associated pneumonia were selected upon admission, including 92 participants with a history of chronic coronary syndromes. Results. The study showed that elevated levels of biomarkers such as proinflammatory cytokine interleukin-6, iron-storage protein ferritin, serum angiotensin-converting enzyme-2, ketone body beta-hydroxybutyric acid, and fibrin breakdown product D-dimer may be associated with a more severe course of pneumonia caused by COVID-19 infection. Thus, these biomarkers had good prognostic value in predicting severe disease and death in patients with chronic coronary syndromes during hospitalization. Conclusions. The study confirms that an increase in the level of proinflammatory biomarkers is a predictor for the development of a severe coronavirus infection.

Early-Onset Hypertension and Sex-Specific Residual Risk for Cardiovascular Disease in Type 2 Diabetes.

To investigate whether the sex disparities in type 2 diabetes-associated cardiovascular disease (CVD) risks may be related to early-onset hypertension that could benefit from intensive blood pressure (BP) control. We analyzed intensive versus standard BP control in relation to incident CVD events in women and men with type 2 diabetes, based on their age of hypertension diagnosis. Among 3,792 adults with type 2 diabetes (49% women), multivariable-adjusted CVD risk was increased per decade earlier age at hypertension diagnosis (hazard ratio 1.11 [1.03-1.21], P = 0.006). Excess risk associated with early-diagnosed hypertension was attenuated in the presence of intensive versus standard antihypertensive therapy in women (P = 0.036) but not men (P = 0.76). Women with type 2 diabetes and early-onset hypertension may represent a higher-risk subpopulation that not only contributes to the female excess in diabetes-related CVD risk but may benefit from intensive BP control.

Unexpected gaps in knowledge of familial hypercholesterolaemia among Dutch general practitioners.

Familial hypercholesterolaemia (FH) warrants early diagnosis to prevent premature atherosclerotic cardiovascular disease (CVD). However, underdiagnosis and undertreatment of FH persist. This study aimed to assess the knowledge and practice of FH care among general practitioners (GPs) in the Netherlands. An internationally standardised, online questionnaire was sent to Dutch GPs between February 2021 and July 2022. The survey assessed knowledge and awareness of FH, encompassing general familiarity, awareness of management guidelines, inheritance, prevalence, CVD risk, and clinical practice related to FH. Comparative analysis was performed using data on primary care physicians from Western Australia, the Asia-Pacific region and the United Kingdom. Of the 221 participating GPs, 62.4% rated their familiarity with FH as above average (score > 4 on a1-7 scale), with 91.4% considering themselves familiar with FH treatment and referral guidelines. Correct identification of the FH definition, typical lipid profile, inheritance pattern, prevalence and CVD risk was reported by 83.7%, 87.8%, 55.7%, 19.5%, and 13.6% of the respondents, respectively. Of the participants, 58.4% answered fewer than half of the 8 knowledge questions correctly. Dutch GPs reported greater FH familiarity and guideline awareness compared with their international counterparts but exhibited similar low performance on FH knowledge questions. Despite the Netherlands' relatively high FH detection rate, substantial knowledge gaps regarding FH persist among Dutch GPs, mirroring global trends. Enhanced FH education and awareness in primary care are imperative to improve FH detection and ensure adequate treatment. Targeting the global suboptimal understanding of FH might require international efforts.

Frequency and determinants of lipid management target achievement in primary prevention of cardiovascular disease in type 2 diabetes

Frequency and determinants of lipid management target achievement in primary prevention of cardiovascular disease in type 2 diabetes

Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank

Aims/hypothesisThe aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers.MethodsFrom a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts.ResultsAt false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts.Conclusions/interpretationAltered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.Graphical

Electronic cigarettes and cardiovascular disease: epidemiological and biological links.

Electronic cigarettes (e-cigarettes), as alternative nicotine delivery methods, has rapidly increased among youth and adults in recent years. However, cardiovascular safety is an important consideration regarding e-cigarettes usage. e-cigarette emissions, including nicotine, propylene glycol, flavorings, nitrosamine, and metals, might have adverse effects on cardiovascular health. A large body of epidemiological evidence has indicated that e-cigarettes are considered an independent risk factor for increased rates of cardiovascular disease occurrence and death. The incidence and mortality of various types of cardiovascular disease, such as cardiac arrhythmia, hypertension, acute coronary syndromes, and heart failure, have a modest growth in vapers (users of e-cigarettes). Although the underlying biological mechanisms have not been fully understood, studies have validated that oxidative stress, inflammation, endothelial dysfunction, atherosclerosis, hemodynamic effects, and platelet function play important roles in which e-cigarettes work in the human body. This minireview consolidates and discusses the epidemiological and biological links between e-cigarettes and various types of cardiovascular disease.

Diabetic retinopathy as an independent marker of cardiovascular disease in type 1 diabetes: Results from a nationwide longitudinal matched case-cohort study.

To investigate diabetic retinopathy (DR) as a potential marker of cardiovascular disease (CVD) in adults with type 1 diabetes attending the Danish DR-screening programme and non-diabetes adults. In this registry-based matched case-cohort study, we identified 16 547 adults with type 1 diabetes, who were registered in the Danish Registry of Diabetic Retinopathy (DiaBase). Each case was age- and sex-matched by five non-diabetes individuals (n = 82 399), and odds ratios (ORs) and hazard ratios (HRs) were estimated for incident and upcoming CVD in multivariable models. Adults with type 1 diabetes (median age 44.5 years, 57.6% male) were more likely to have prevalent CVD (OR 1.29; 95% CI, 1.20-1.38) and to develop CVD within 5 years (HR 1.19; 95% CI, 1.08-1.30) as compared to non-diabetes control. However, adults without DR were less likely to develop CVD (HR 0.84; 95% CI, 0.72-0.97) compared to the reference population. For adults with type 1 diabetes, there was an increasing risk for incident CVD for increasing levels of DR (HR 1.33, 1.95, 1.71 and 2.39 for DR-levels 1-4, respectively). Patients with CVD at the time of the first screening had a higher risk to develop DR during follow-up (HR 1.23; 95% CI, 1.02-1.49). In a nationwide matched case-cohort study adjusted for potential confounders, DR was identified as an independent marker of prevalent and incident CVD in type 1 diabetes with increasing risk demonstrated for higher levels of DR. Likewise, CVD also independently predicted the risk of incident DR.

Green tea consumption and incidence of cardiovascular disease in type 2 diabetic patients with overweight/obesity: a community-based cohort study

BackgroundGreen tea has been reported to be potentially protective against the development of cardiovascular disease (CVD). This study aimed to investigate the association between green tea consumption and incident CVD in type 2 diabetes (T2D) patients with overweight/obesity.MethodsA total of 4756 Chinese overweight/obese T2D patients were recruited and followed up for 6.27 years. Information on green tea consumption was collected at baseline using interviewer-administered questionnaires. Hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CVD according to green tea consumption were estimated using the Cox proportional hazards model.ResultsCompared with non-habitual consumers, participants who consumed > 5 g/day of green tea leaves reduced the risk of CVD by 29% (95%CI: 0.55–0.92), stroke by 30% (95%CI: 0.51–0.95) and coronary heart disease (CHD) by 40% (95%CI: 0.40–0.89). Similarly, participants who consumed green tea for ≥ 40 years reduced the risk of CVD by 31% (95%CI: 0.54–0.88), stroke by 33% (95%CI: 0.50–0.90) and CHD by 39% (95%CI: 0.42–0.88). Among participants with < 5-year history of T2D, > 5 g/day of tea leaves and > 40 years of tea consumption were associated with 59% (95%CI: 0.23–0.72) and 57% (95%CI: 0.26–0.74) reduced risk of stroke, respectively. However, among participants with ≥ 5-year history of T2D, > 5 g/day of tea leaves and > 40 years of tea consumption were associated with a 50% (95%CI: 0.30–0.82) and 46% (95%CI: 0.35–0.85) reduced risk of CHD, respectively.ConclusionsGreen tea consumption is associated with reduced risk of CVD, stroke, and CHD in overweight/obese T2D patients.

The Determination of Diabetes Utilities, Costs, and Effects Model: A Cost-Utility Tool Using Patient-Level Microsimulation to Evaluate Sensor-Based Glucose Monitoring Systems in Type 1 and Type 2 Diabetes: Comparative Validation

ObjectivesTo assess the accuracy and validity of the Determination of Diabetes Utilities, Costs, and Effects (DEDUCE) model, a Microsoft-Excel-based tool for evaluating diabetes interventions for type 1 and type 2 diabetes. MethodsThe DEDUCE model is a patient-level microsimulation, with complications predicted based on the Sheffield and Risk Equations for Complications Of type 2 diabetes models for type 1 and type 2 diabetes, respectively. For this tool to be useful, it must be validated to ensure that its complication predictions are accurate. Internal, external, and cross-validation was assessed by populating the DEDUCE model with the baseline characteristics and treatment effects reported in clinical trials used in the Fourth, Fifth, and Ninth Mount Hood Diabetes Challenges. Results from the DEDUCE model were evaluated against clinical results and previously validated models via mean absolute percentage error or percentage error. ResultsThe DEDUCE model performed favorably, predicting key outcomes, including cardiovascular disease in type 1 diabetes and all-cause mortality in type 2 diabetes. The model performed well against other models. In the Mount Hood 9 Challenge comparison, error was below the mean reported from comparator models for several outcomes, particularly for hazard ratios. ConclusionsThe DEDUCE model predicts diabetes-related complications from trials and studies well when compared with previously validated models. The model may serve as a useful tool for evaluating the cost-effectiveness of diabetes technologies.

The Burden of Dyslipidemia and Determinant Factors Among Type 2 Diabetes Mellitus Patients at Hawassa University Comprehensive Specialized Hospital, Hawassa, Ethiopia.

Diabetes is a global health challenge with escalating prevalence rates. Cardiovascular complications represent the leading cause of mortality among individuals with diabetes. Notably, dyslipidemia stands as a prominent risk factor for cardiovascular disease in Type 2 diabetes mellitus (T2DM) patients. Timely detection and management of dyslipidemia in these patients hold the potential to deter its progression and substantially reduce the risk of cardiovascular-related morbidity and mortality.This study was aimed at assessing the burden of dyslipidemia and determinant factors among T2DM patients who were being followed at the Endocrinology clinic of Hawassa University Comprehensive Specialized Hospital (HUCSH). An Institutional- based retrospective cross-sectional study was conducted, and samples of 228 patients were selected using a systematic random sampling technique. Data were collected through structured face-to-face interviews using a questionnaire. Bivariate logistic analysis was utilized, and variables with a p-value < 0.25 in this analysis were considered candidates for multivariate logistic analysis. Multivariate logistic regression was employed to identify factors associated with the prevalence of dyslipidemia, with a significance threshold set at p < 0.05. The research revealed an overall prevalence of dyslipidemia among the study participants at 75.9%. The specific manifestations of dyslipidemia were observed as follows: hypertriglyceridemia in 43%, hypercholesterolemia in 25%, elevated low-density lipoprotein in 59.2%, and reduced high-density lipoprotein in 33.3% of the study participants. Factors significantly associated with dyslipidemia included longer diabetes duration, poor physical activity, elevated HbA1C, and obesity. This study underscores a notably high prevalence of dyslipidemia among T2DM patients. The findings highlight the advocate for clinicians to prioritize routine screening, and effective treatment concerning dyslipidemia and its associated risk factors among individuals with T2DM. It is worth mentioning that this study was conducted in a specific hospital setting and limited time, and hence the findings, and generalizability to other healthcare facilities should be taken cautiously.

Expression levels and clinical significance of ferroptosis-related genes in patients with myocardial infarction

Myocardial infarction (MI) is the most serious type of cardiovascular disease and the leading cause of cardiac death.Ferroptosis is one of the newly discovered programmed cell death modes in MI, but its mechanism of action in MI has not been clarified.In this study, we analyzed the expression changes of ferroptosis-related genes in MI and explored the potential mechanisms of ferroptosis-related functions in myocardial infarction. Public data sets GSE19339, GSE97320 and GSE141512 were retrieved from the Gene Expression Omnibus (GEO) Datasets public database. After data preprocessing, differentially expressed genes were screened, and differentially expressed ferroptosis-related genes associated with myocardial infarction were obtained. The biological function and signaling pathway enrichment analysis were performed to establish the PPI interaction network specific to heart tissue, and the differential diagnosis significance of differentially expressed ferroptosis-related genes associated with myocardial infarction was analyzed by ROC curve and decision tree model.A total of 317 genes showed significant changes in expression levels in patients with myocardial infarction, including 205 down-regulated genes and 112 up-regulated genes.Gene Ontology (GO) enrichment analysis and functional classification of Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways showed that these genes were mainly involved in signaling pathways or biological functions related to inflammation and apoptosis.Five differentially expressed ferroptosis-related genes (SLC2A3, EPAS1, HMOX1, ATM, FANCD2) were obtained, all of which played key biological functions in cardiac tissue function. SLC2A3, EPAS1, HMOX1, ATM and FANCD2 genes all had good diagnostic value for myocardial infarction (P < 0.05). The increase of SLC2A3, EPAS1 and HMOX1 are risk factors for myocardial infarction, while ATM and FANCD2 are protective factors.Decision tree analysis showed that SLC2A3, HMOX1, ATM, FANCD2 gene had higher net yield in diagnosing myocardial infarction. In summary, the mechanism of ferroptosis is involved in the occurrence and progression of myocardial infarction. In this study, five differentially expressed ferroptosis-related genes associated with myocardial infarction were retrieved, which may be good biomarkers of ferroptosis after MI.These findings also suggest that the differential expression of ferroptosis-related genes associated with myocardial infarction has significant diagnostic significance for myocardial infarction.

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis.

Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Zhishi Xiebai Guizhi Decoction for coronary heart disease: A systematic review and meta-analysis.

Coronary heart disease (CHD) is a type of cardiovascular disease (CVD) caused by coronary atherosclerosis. It is a main cause of medical burden and cardiovascular related death. Zhishi Xiebai Guizhi Decoction (ZXGD) is a representative prescription of traditional Chinese medicine (TCM) in the treatment of CHD, but there is poor systemically evidence-based appraisal. To evaluate the efficacy and safety of ZXGD for CHD. Eight databases were retrieved for randomized controlled trials (RCTs). Data was extracted independently by 2 reviewers. The quality of the included studies was assessed by Cochrane Collaboration risk of bias tool. Clinical efficacy, blood lipid, vascular endothelial function, inflammatory factor and homocysteine (Hcy) were prespecified outcome measures. Twenty-four studies (2272 patients) were included. Meta-analysis showed that compared with conventional western medicine (WM) alone, ZXGD was associated with a greater symptom improvement rate with a relative risk (RR) of 1.21 [95% CI (1.16, 1.26), P < .00001] and a greater electrocardiogram (ECG) improvement rate with a RR of 1.27 [95% CI (1.16, 1.40), P < .00001]. In terms of blood lipid, ZXGD reduced total cholesterol (TC) with a mean difference (MD) of -1.15 [95%CI (-1.75, -0.55), P = .0002] and triglyceride (TG) [MD = -0.72, 95%CI (-0.99, -0.45), P < .00001], reduced low-density lipoprotein cholesterol (LDL-C) [MD = -0.93, 95% CI (-1.17, -0.69), P < .00001], and increased high-density lipoprotein cholesterol (HDL-C) [MD = 0.31, 95%CI (0.20, 0.42), P < .00001]. In terms of vascular endothelial function, ZXGD decreased the level of endothelin-1 (ET-1) [MD = -7.81, 95%CI (-9.51, -6.10), P < .00001], and increased nitric oxide (NO) [MD = 8.90, 95%CI (7.86, 9.93), P < .00001]. ZXGD also reduced high-sensitivity C-reactive protein (hs-CRP) [MD = -1.73, 95% CI (-2.63, -0.83), P < .00001] and Hcy [MD = -2.03, 95%CI (-2.78, -1.28), P < .00001]. No significant differences were found in adverse event rate between the 2 groups with a RR of 0.77 [95% CI (0.44, 1.34), P = .36]. ZXGD is effective and safe in the treatment of CHD. However, more rigorous and high-quality RCTs are needed to verify the conclusion.

Knowledge domain and emerging trends of autophagy in cardiovascular research: A bibliometric analysis.

Autophagy is essential for the homeostasis and function of the cardiovascular system. Citespace is a visual analysis software developed in the context of scientometrics and data visualization. The purpose of this study is to use Citespace software to conduct bibliometric and visual analysis of the research on autophagy in cardiovascular diseases, identify the current status, hot spots and trends in this field, help researchers clarify the future research focus and direction of autophagy in cardiovascular diseases, and provide more positive and broader ideas for the treatment and drug development of cardiovascular diseases. In the Web of Science Core Collection database to download the data from 2004 to 2022 regarding autophagy in cardiovascular research. CitespaceV was used to collect the research status, hotspots and development trends for visual analysis. The 3568 articles were published by 547 authors from 397 institutions in 75 countries. From 2004 to 2021, the annual publications increased over time. The top 3 productive nations were China, the United States, and Germany. The leading institution was China's Fudan University. The most cited paper is Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition). The research hotpots include monitoring methods for autophagy activity, changes in autophagy levels in different types of cardiovascular diseases, autophagy signal transduction mechanism in cardiovascular diseases, etc. Bibliometric analysis provided valuable information for autophagy research in cardiovascular disease, which is full of opportunities and challenges. The research of autophagy in the field of cardiovascular diseases is still worthy of in-depth exploration. A challenge with autophagy-targeted therapies is their dichotomy in which the goal is to target maladaptive autophagy while maintaining a baseline level of cell survival to optimize a beneficial outcome. It is necessary for scientists to develop new methods to evaluate the level of autophagy from basic application to human body and reveal the signaling mechanism of autophagy in different types of cardiovascular diseases.

Mediterranean diet for cardiovascular disease: an evidence mapping study.

This study aimed to evaluate the methodological quality of existing meta-analyses (MA) and the quality of evidence for outcome indicators to provide an updated overview of the evidence concerning the therapeutic efficacy of the Mediterranean diet (MD) for various types of CVD. We conducted comprehensive searches of PubMed, Cochrane Library, and Embase databases. The quality of the MA was assessed using the A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) checklist, while the Grading of Recommendations Assessment, Development and Evaluation (GRADE) evidence evaluation system was employed to evaluate the quality of evidence for significant outcomes. The CVD remains a significant contributor to global mortality. Multiple MA have consistently demonstrated the efficacy of medical interventions in managing CVD. However, due to variations in the scope, quality and outcomes of these reviews, definitive conclusions are yet to be established. This study included five randomized trials and twelve non-randomized studies, with a combined participant population of 716 318. The AMSTAR 2 checklist revealed that 54·55 % of the studies demonstrated high quality, while 9·09 % exhibited low quality, and 36·36 % were deemed critically low quality. Additionally, there was moderate evidence supporting a positive correlation between MD and CHD/acute myocardial infarction, stroke, heart failure, cardiovascular events, coronary events and major adverse cardiovascular events. This study indicates that although recognizing the potential efficacy of MD in managing CVD, the quality of the methodology and the evidence for the outcome indicators remain unsatisfactory.

Early-stage heart failure disease prediction with deep learning approach

Cardiovascular diseases rank the highest among diseases in terms of mortality rate and cause millions of deaths every year. Heart failure is a type of cardiovascular disease and its early diagnosis is extremely important for its prevention. It may be vitally important to understand to what extent which body values, characteristics and factors (age, gender, blood pressure, sugar, etc.) affect this disease and to predict whether the individual will have a possible heart attack in the future. In this study, firstly, the correlation level of the relevant body values with the disease is extracted and in the second stage, a method that predicts heart attack with DNN (Deep Neural Network) and CNN (Convolutional Neural Network) deep learning models is proposed. In the study, 918 observations obtained from the kaggle site were used. Firstly, missing data, categorical data, non-numerical features were checked. Then, outliers were cleaned and the relationship of the features in the dataset with the disease state was revealed by feature engineering operations on the data. Finally, deep neural network models were built and the model was trained and hyperparameter adjustment was performed with GridSearhCV to achieve the highest success rate. As a result of the study, Accuracy, Precision, Recall and F1-Score values were found as 0.9375, 0.9629, 0.9176, 0.9397 for DNN and 0.9312, 0.9512, 0.9176, 0.9340 for CNN respectively. The AUC value calculated from the ROC curve was found to be equal to 0.96 in both deep learning models.

Sodium intake and the risk of various types of cardiovascular diseases: a Mendelian randomization study.

The existing literature on the link between sodium intake and cardiovascular disease (CVD) largely consists of observational studies that have yielded inconsistent conclusions. In this study, our objective is to assess the causal relationship between sodium intake and 50 CVDs using two-sample Mendelian randomization (MR) analysis. MR analyses were performed to investigate the associations between urinary sodium/creatinine ratio (UNa/UCr), an indicator of sodium intake, and 50 CVDs. The genome-wide association study (GWAS) for UNa/UCr was from the UK Biobank (UKBB), and the GWASs for CVDs were from FinnGen. A false discovery rate (FDR) threshold of 5% was applied for multiple comparison correction. The inverse-variance weighted method indicated that the genetically predicted UNa/UCr was significantly associated with 7 of 50 CVDs, including "Coronary atherosclerosis" (OR = 2.01; 95% CI: 1.37, 2.95), "Diseases of arteries, arterioles and capillaries" (OR = 1.88; 95% CI: 1.20, 2.94), "Hard cardiovascular diseases" (OR = 1.71; 95% CI: 1.24, 2.35), "Ischemic heart diseases" (OR = 2.06; 95% CI: 1.46, 2.93), "Major coronary heart disease event" (OR = 1.99; 95% CI: 1.36, 2.91), "Myocardial infarction" (OR = 2.03; 95% CI: 1.29, 3.19), and "Peripheral artery disease" (OR = 2.50; 95% CI: 1.35, 4.63). Similar results were obtained with the MR-Egger and weighted median methods. No significant heterogeneity or horizontal pleiotropy was found in this analysis. Our study has uncovered a significant positive causal relationship between UNa/UCr and various CVDs. These results offer a new theoretical foundation for advocating the restriction of sodium intake as a preventive measure against CVD.

Dynamic control of contractile resistance to iPSC-derived micro-heart muscle arrays.

Many types of cardiovascular disease are linked to the mechanical forces placed on the heart. However, our understanding of how mechanical forces exactly affect the cellular biology of the heart remains incomplete. In vitro models based on cardiomyocytes derived from human induced pluripotent stem cells (iPSC-CM) enable researchers to develop medium to high-throughput systems to study cardiac mechanobiology at the cellular level. Previous models have been developed to enable the study of mechanical forces, such as cardiac afterload. However, most of these models require exogenous extracellular matrix (ECM) to form cardiac tissues. Recently, a system was developed to simulate changes in afterload by grafting ECM-free micro-heart muscle arrays to elastomeric substrates of discrete stiffnesses. In the present study, we extended this system by combining the elastomer-grafted tissue arrays with a magnetorheological elastomeric substrate. This system allows iPSC-CM based micro-heart muscle arrays to experience dynamic changes in contractile resistance to mimic dynamically altered afterload. Acute changes in substrate stiffness led to acute changes in the calcium dynamics and contractile forces, illustrating the system's ability to dynamically elicit changes in tissue mechanics by dynamically changing contractile resistance.

Abstract 18179: Metabolic Biomarker Signatures for Incident Heart Failure Hospitalisation Compared to Different Types of Cardiovascular Events: Evidence From NMR Metabolomics in 250,000 Individuals

Introduction: Metabolomic biomarker profiling by Nuclear Magnetic Resonance (NMR) is a powerful technique to examine molecular signatures for heart failure risk and clarify pathological differences to cardiovascular outcomes. Hypothesis: Blood lipids and metabolite biomarkers may differ in how they relate to prediction of heart failure vs coronary and stroke outcomes. Methods: We measured detailed plasma lipids and metabolites by NMR metabolomics in ~250,000 individuals from UK Biobank. We assessed shared and discordant biomarkers for heart failure hospitalisation in relation to myocardial infarction, ischemic stroke, peripheral artery disease, cardiac arrest and cardiovascular death. During 10 years of follow-up, 7.800 incident heart failure hospitalisation events occurred and 5-10.000 incident events for cardiovascular outcomes. Results: The overall pattern of biomarker associations differed for heart failure compared to for example, myocardial infarction, with biomarkers of LDL metabolism and apolipoprotein being especially discordant (Figure). In contrast, biomarkers of chronic inflammation and circulating fatty acids were concordant for the risk of heart failure and myocardial infarction. There were also prominent differences in the metabolic biomarker signatures for the risk of different types of cardiovascular diseases, such as between chronic ischemic heart disease, and different types of stroke. The biomarker association magnitudes were strongest for cardiovascular mortality and especially strong for short time to event onset. Conclusions: Heart failure and different cardiovascular endpoints have partly different metabolic biomarkers signatures. These may represent pathophysiological differences and have relevance for cardiovascular risk prediction, especially if using the five-point major adverse cardiovascular event definition.