Current Cardiology Reviews最新文献

Introduction: Thoracic aortic aneurysms (TAAs) are worrisome for their propensity to dissect. Previous studies have demonstrated the potential benefits of statin use, particularly with slowing aortic aneurysm growth. The aim of this meta-analysis was to consolidate existing research to ascertain if statins effectively reduce TAA growth.

Methods: Multiple databases were searched to identify studies assessing TAA growth in patients on statins (cases) and those not on statins (controls). The primary outcome was TAA (ascending/ aortic arch) growth rate per year. Standard mean difference (SMD) and 95% confidence intervals (95% CI) were estimated with a random-effects model using the inverse-variance technique. We assigned I2>50% as an indicator of statistical heterogeneity. P-value <0.05 was considered significant. Data analysis was performed using SPSS v.25.0.

Results: Four studies comprising 757 cases (male 64%, mean age 65±14 years) and 1,696 controls (male 62%, mean age 61±18 years) were included. The baseline diameters of TAA for cases and controls were 40.35±8.75 mm and 42.39±12.60 mm, respectively. Pooled results suggested statins to be associated with slower growth of TAAs with pooled SMD -0.70 mm/year [95% CI (-1.23 - -0.16); p=0.01]. Heterogeneity statistics among 4 studies was 95%.

Conclusion: This pooled meta-analysis showed statins as associated with slower growth of TAAs. However, given the heterogeneity of the included studies in this meta-analysis, results should be interpreted with caution.

Diabetic Cardiomyopathy (DCM) is a notable consequence of diabetes mellitus, distinguished by cardiac dysfunction that occurs separately from coronary artery disease or hypertension. A recent study has revealed an intricate interaction of pathogenic processes that contribute to DCM. Important aspects involve the dysregulation of glucose metabolism, resulting in heightened oxidative stress and impaired mitochondrial function. In addition, persistent high blood sugar levels stimulate inflammatory pathways, which contribute to the development of heart fibrosis and remodelling. Additionally, changes in the way calcium is managed and the presence of insulin resistance are crucial factors in the formation and advancement of DCM. This may be due to the involvement of many molecular mechanistic pathways such as NLRP3, NF-κB, PKC, and MAPK with their downstream associated signaling pathways. Gaining a comprehensive understanding of these newly identified pathogenic pathways is crucial in order to design precise therapy approaches that can enhance the results for individuals suffering from diabetes. In addition, this review offers an in-depth review of not just pathogenic pathways and molecular mechanistic pathways but also diagnostic methods, treatment options, and clinical trials.

RAS proteins are critical in cellular signal transduction, influencing cell proliferation, differentiation, and survival. While extensively studied for their role in cancer, RAS gene mutations also contribute significantly to cardiovascular diseases, such as hypertrophic cardiomyopathy, pulmonary valve stenosis, and atrial septal defects. Despite their similar primary structures, RAS proteins exhibit distinct functions in cardiac biology: H-RAS regulates cardiomyocyte size, K-RAS governs proliferation, and N-RAS, less associated with cardiac defects, is understudied in cardiac cells. Congenital RAS mutations, collectively known as RASopathies, include syndromes, like Noonan syndrome and cardio-facio-cutaneous syndrome, which often lead to severe cardiac complications, including heart failure. Genetic testing and imaging advances have improved the diagnosis and management of these conditions. Recent research has shown promise with MEK inhibitors and other targeted therapies, offering potential improvements in managing RAS-related cardiac conditions. This review explores the role of the RAS subfamily in heart disease, highlighting key concepts and potential therapeutic targets. PubMed database was searched using keywords, such as RASopathies, RAS gene mutations, cardiac hypertrophy, cardiovascular disease, RAS/MAPK pathway, congenital heart disease, and more. Relevant literature up to June 2024 was examined and summarized, consisting of data from various clinical trials, metaanalyses, retrospective/prospective cohort studies, and current guidelines.

Introduction: Peripheral arterial disease (PAD) is a marker of significant atherosclerotic cardiovascular disease and is associated with greater healthcare burden and worse prognosis in individuals with chronic inflammatory disease (CID). We aimed to investigate temporal trends and disparities of PAD-related mortality in populations with CID from 1999-2020 across six common CIDs (i.e., chronic viral hepatitis, human immunodeficiency virus, inflammatory bowel disease, psoriasis, rheumatoid arthritis, and systemic lupus erythematosus).

Methods: United States (US) PAD and CID-related mortality and demographic data from 1999- 2020 were extracted from the CDC database through the multiple-cause-of-death files. Ageadjusted mortality rates (AAMR) per 1,000,000 and 95% confidence intervals were standardized to the 2000 US population. The mortality trends were analyzed using Joinpoint Regression.

Results: A total of 22,175 PAD-related deaths were recorded in the population with CID between 1999 and 2020. Mortality remained stable during the 22-year period (AAPC -0.04%, p=0.95) with a cumulative AAMR of 4.64. Mortality was highest in rural counties (AAMR 5.27), and among non-Hispanic Black populations (AAMR 7.06). Among the CID subtypes, PAD mortality was highest in populations with RA (AAMR 2.48) and lowest in populations with psoriasis (AAMR 0.11).

Conclusion: Our findings highlight the disparities of PAD mortality in patients with CID, with the Black population and rural communities disproportionately affected. Further investigation with individual- level data is warranted to identify the contributing factors for the observed disparities.

Introduction: Atherosclerosis is a chronic disease caused by the accumulation of lipids, inflammatory cells, and fibrous elements in arterial walls, leading to plaque formation and cardiovascular conditions like coronary artery disease, stroke, and peripheral arterial disease. Factors like hyperlipidemia, hypertension, smoking, and diabetes contribute to its development. Diagnosis relies on imaging and biomarkers, while management includes lifestyle modifications, pharmacotherapy, and surgical interventions. Computational biology is transforming biological knowledge into clinical practice by identifying biomarkers that can predict clinical outcomes. This involves omics data, predictive modeling, and data integration. Statistical analysis-based methods are also being developed to develop and integrate methods for screening, diagnosing, and prognosing atherosclerosis.

Methodology: The present work aimed to uncover critical genes and pathways to enhance the understanding of the mechanism of atherosclerosis. GSE23746 was analyzed to find differentially expressed genes (DEGs) using 19 control samples and 76 atherosclerotic samples.

Results: A total of 76 DEGs were identified. Analysed DEGs using Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) to generate enrichment datasets. A Protein- protein Interaction (PPI) network of DEGs was created utilizing the Search Tool for the Retrieval of Interacting Genes (STRING).

Conclusion: Ten hub genes, namely EGR1, PTGS2, TNF, NFKBIA, CXCL8, TNFAIP3, CCL3, IL1B, PTPRC, and CD83, were found to be significantly linked to atherosclerosis. Furthermore, the metabolic pathway analysis through KEGG and STRING provides potential targets for therapeutic interventions through HUB genes to diagnose the illness at an early stage, which aids in the reduction of cardiovascular risk. From risk factor profiling to the discovery of novel biomarkers, several components such as phospholipids, ANGPTL3, LCAT, and the proteinencoded OCT-1 gene, play a vital role in crucial processes. These compounds are potential therapeutic targets for early diagnosis of atherosclerotic lesions and future novel biomarkers.

Introduction: The presence of both cardiovascular disease (CVD) and depression is common, and their complex connection poses difficulties in therapy and affects patient outcomes. Thus, this study aims to examine the complex correlation between depression and cardiovascular disease (CVD), with a specific focus on potential biomarkers and innovative therapeutic approaches.

Methods: Publications were considered between 2015-2024 from standard databases like Google Scholar, PubMed-Medline, and Scopus using standard keywords, "Depression", "Cardiovascular Disease", "Biomarkers", and "Therapeutic Approaches". Recent studies have discovered several potential biomarkers linked to depression and cardiovascular disease (CVD), including neuroendocrine factors, inflammatory markers, and signs of oxidative stress. Therapeutic approaches for depression and cardiovascular disease have emerged, with a focus on tackling their connections from multiple dimensions.

Results and discussion: Emerging research suggests that depression has an impact on both the prognosis and risk of CVD. Conversely, depression can be caused by CVD, which triggers a series of events that lead to higher rates of illness and death.

Conclusion: A comprehensive understanding of the fundamental pathophysiological pathways is essential for the identification of biomarkers that can serve as diagnostic tools or therapy targets. Among these interventions, exercise and dietary adjustments have shown promising impacts on cardiovascular health and results, as well as mental health. Ultimately, the selection of diagnostic techniques and treatments hinges on comprehending the complex interplay between depression and CVD. Researchers are developing novel therapeutic techniques to enhance the cardiovascular and mental health outcomes of individuals with both depression and CVD.

Cardiovascular disease is the leading cause of pregnancy-related mortality, with pregnancy-related cardiovascular issues extending into the postpartum period. Recent studies suggest hyperandrogenism alters sex hormone levels, contributing to gestational cardiovascular disease CVD. Most of the factors behind the onset of CVD in postpartum women remain unknown. Animal studies mimic adverse pregnancy outcomes to explore molecular causes of severe prenatal cardiac events and their role in postpartum cardiovascular disease development. This review will be focused on summarising human and animal research that shows how undesirable pregnancy outcomes, such as obesity in the mother and gestational diabetes (GD), have an impact on postpartum cardiovascular disease and prenatal cardiometabolic dysfunction. We will highlight the adverse effects of gestational hyperandrogenism as a potential biomarker for cardiovascular dysfunction in pregnant women and new mothers. Investigative cardiovascular (CV) risk variables in the early postpartum phase following pregnancy that were impacted by GD was the aim of this study. Current research strongly implies that women with GDM have a higher risk of developing CVD. Finding appropriate, reliable indicators of CVD and specific treatment modalities that can control obesity, diabetes, and metabolic syndrome are critical to reducing the burden of CVD on impacted women. GD and hypertensive disorders are two pregnancy- related illnesses that raise the risk of CVD in the long run. Despite a lack of awareness, early screening, lifelong monitoring, and continuous research to enhance detection and prevention are essential.

Cardiovascular disease (CVD) Continues to be the leading cause of mortality worldwide, underscoring the critical need for effective prevention and management strategies. The ability to predict cardiovascular risk accurately and cost-effectively is central to improving patient outcomes and reducing the global burden of CVD. While useful, traditional tools used for risk assessment are often limited in their scope and fail to adequately account for atypical presentations and complex patient profiles. These limitations highlight the necessity for more advanced approaches, particularly integrating artificial intelligence (AI) into cardiovascular risk prediction. Our review explores the transformative role of AI in enhancing the accuracy, efficiency, and accessibility of cardiovascular risk prediction models. The implementation of AI-driven risk assessment tools has shown promising results, not only in improving CVD mortality rates but also in enhancing quality of life (QOL) markers and reducing healthcare costs. Machine learning (ML) algorithms predicted 2-year survival rates after MI with improved accuracy compared to traditional models. Deep learning (DL) forecasted hypertension risk with a 91.7% accuracy based on electronic health records. Furthermore, AI-driven ECG (Electrocardiography) analysis has demonstrated high precision in identifying left ventricular systolic dysfunction, even with noisy single-lead data from wearable devices. These tools enable more personalized treatment strategies, foster greater patient engagement, and support informed decision-making by healthcare providers. Unfortunately, the widespread adoption of AI in CVD risk assessment remains a challenge, largely due to a lack of education and acceptance among healthcare professionals. To overcome these barriers, it is crucial to promote broader education on the benefits and applications of AI in cardiovascular risk prediction. By fostering a greater understanding and acceptance of these technologies, we can accelerate their integration into clinical practice, ultimately aiming to mitigate the global impact of CVD.

Current arrhythmia therapies such as ion channel blockers, catheter ablation, or implantable cardioverter defibrillators have limitations and side effects, and given the proarrhythmic risk associated with conventional, ion channel-targeted anti-arrhythmic drug therapies, a new approach to arrhythmias may be warranted. Measuring and adjusting the level of specific ions that impact heart rhythm can be a simple and low-complication strategy for preventing or treating specific arrhythmias. In addition, new medicines targeting these ions may effectively treat arrhythmias. Numerous studies have shown that intracellular and extracellular zinc concentrations impact the heart's electrical activity. Zinc has been observed to affect cardiac rhythm through a range of mechanisms. These mechanisms encompass the modulation of sodium, calcium, and potassium ion channels, as well as the influence on beta-adrenergic receptors and the enzyme adenylate cyclase. Moreover, zinc can either counteract or induce oxidative stress, hinder calmodulin or the enzyme Ca (²⁺)/calmodulin-dependent protein kinase II (CaMKII), regulate cellular ATP levels, affect the processes of aging and autophagy, influence calcium ryanodine receptors, and control cellular inflammation. Additionally, zinc has been implicated in the modulation of circadian rhythm. In all the aforementioned cases, the effect of zinc on heart rhythm is largely influenced by its intracellular and extracellular concentrations. Optimal zinc levels are essential for maintaining a normal heart rhythm, while imbalances-whether deficiencies or excesses-can disrupt electrical activity and contribute to arrhythmias.

Background: Acute Heart Failure (HF) is related to a significant hospital mortality rate and functional impairment in many patients. However, there is still a lack of studies that support the use of Beta-blockers (BB) in the management of decompensated HF.

Objective: This study aimed to evaluate the impact on mortality of maintaining BB in patients with decompensated HF.

Methods: A systematic review and meta-analysis was performed, using the databases PubMed, Cochrane Library, SCIELO and BVS, selecting only cohort studies and Randomized Clinical Trials (RCTs) from the last 10 years, which have been selected based on inclusion and exclusion criteria.

Results: An 86% reduction in the risk of in-hospital death was found (RR=0.14, 95% CI: 0.10- 0.18) in patients with HF who maintained the use of BB during hospitalization. A second analysis found a 44% (RR=0.56, 95% CI: 0.47-0.66) lower chance of in-hospital death in the group that previously used BB. Regarding the analysis of mortality after hospital discharge, only studies that have evaluated the use of BB in HF with reduced ejection fraction pointed to a reduction in mortality. Furthermore, some articles have found a relationship between the reduction in readmissions and the use of post-discharge BB.

Conclusion: There is still no consensus regarding the use of BB in patients hospitalized with decompensated HF. In view of the limitations of the data found in the present study, the need for more RCTs that address this topic is emphasized in order to resolve this uncertainty in the management of cardiovascular patients.