Jala, Saisree Reddy Adla

Background: Metabolic-associated fatty liver disease (MAFLD) affects approximately 30% of the global population and is associated with obesity and metabolic syndrome. Anthropometric indices such as body mass index (BMI), waist circumference (WC), and weight are crucial markers for evaluating the progression of MAFLD. Curcumin, a bioactive compound with anti-inflammatory and antioxidant properties, has been investigated for its potential to improve metabolic outcomes. This umbrella review aimed to systematically evaluate the effects of curcumin supplementation on anthropometric indices in patients with MAFLD, considering epidemiological strength and power analysis. Methods: An umbrella review of meta-analyses from randomized controlled trials was conducted. PubMed, Scopus, and Web of Science were searched up to September 2024. Meta-analyses assessing curcumin’s effects on BMI, weight, and WC in MAFLD patients were included. Quality was assessed using the A Measurement Tool to Assess Systematic Reviews version (AMSTAR-2) tool, and heterogeneity was evaluated using the I 2 statistic. Statistical analyses were performed using R and Stata 18 software. Results: Curcumin supplementation had no significant effect on BMI (standardized mean difference [SMD]: −0.01; 95% confidence interval [CI]: −0.24 to 0.21, P = .91) with low power (1-β = 0.03) and a low epidemiological grade according to GRADE criteria. Similarly, curcumin showed no significant effect on WC (SMD: −0.27; 95% CI: −0.57 to 0.04, P = .08) with high power (1-β = 0.96) but low epidemiological strength. However, curcumin significantly reduced weight (SMD: −0.12; 95% CI: −0.19 to −0.04, P < .01) with moderate power (1-β = 0.56) and moderate epidemiological strength. No significant effect of dose or effect of supplementation duration was found. Conclusion: Curcumin supplementation may result in a statistically detectable but clinically modest reduction in body weight in patients with MAFLD, while showing limited or no efficacy on BMI and waist circumference. The epidemiological strength of the evidence varies across outcomes and is of low to moderate quality. Further well-designed, high-quality randomized controlled trials are needed to confirm the clinical relevance of curcumin’s effects on anthropometric indices.

Background: The application of artificial intelligence (AI) in cardiac imaging has rapidly evolved, offering enhanced accuracy and efficiency in the diagnosis and management of cardiovascular diseases. This bibliometric study aimed to evaluate research trends, impact, and scholarly output in this expanding field. Methods: A systematic search was conducted on 14 August 2024 using the Web of Science Core Collection database. VOSviewer, CiteSpace, and Biblioshiny were utilized for data analysis. Results: The findings revealed a significant increase in publications on AI in cardiovascular imaging, particularly from 2018 to 2023, with the United States leading in research output. England and the United States have emerged as central hubs in the global research network, highlighting their role in generating high-quality and impactful publications. The University of London was identified as the top contributing institution, while Frontiers in Cardiovascular Medicine was the most prolific journal. Keyword analysis highlighted machine learning, echocardiography, and diagnosis as the most frequently occurring terms. A time trend analysis showed a shift in research focus toward AI applications in cardiac computed tomography (CT) and magnetic resonance imaging (MRI), with recent keywords like ejection fraction, risk, and heart failure reflecting emerging areas of interest. Conclusion: Healthcare providers should consider integrating AI tools into cardiovascular imaging practice, as AI has demonstrated the potential to enhance diagnostic accuracy and improve patient outcomes. This study highlights the rising importance of AI in personalized and predictive cardiovascular care, urging healthcare providers to stay informed about these advancements to enhance clinical decision-making and patient management.

Objective: This study aims to conduct a bibliometric analysis of the triglyceride-glucose (TyG) index in relation to cardiovascular disorders. Methods: Data for the analysis were extracted from the Web of Science Core Collection database on 13 July 2024. We utilized VOSviewer, CiteSpace, and Biblioshiny tools for the analysis. Results: The study revealed a marked increase in research outputs on the TyG index in recent years, peaking with 137 publications in 2023. China emerged as the leading contributor, followed by the USA. The Chinese Academy of Medical Sciences and Peking Union Medical College were among the top contributing institutions. Shouling Wu and Shuohua Chen emerged as the leading authors, with the journal Cardiovascular Diabetology publishing the most articles on this topic. Keyword analysis identified “insulin-resistance” as the most frequently occurring term, followed by “risk.” Cluster analysis identified eleven key research areas, including “percutaneous coronary intervention,” “obesity indicators,” “arterial stiffness,” and “heart failure.” Conclusion: This bibliometric analysis highlights the expanding role of the TyG index in metabolic and cardiovascular research. Key clusters such as percutaneous coronary intervention, obesity indicators, arterial stiffness, heart failure, new-onset hypertension, predicting outcomes, and subclinical coronary artery disease emphasize its wide applicability across diverse clinical settings. The keyword “risk” was the most frequently occurring term, underscoring the importance of the TyG index in cardiovascular risk assessment, alongside its growing use in prognostic applications. These findings reflect the increasing recognition of the TyG index as a pivotal biomarker in cardiovascular medicine and encourage further exploration of its clinical integration.

BACKGROUND: COVID-19 patients are at higher risk of major adverse cardiovascular and cerebrovascular events (MACCE). The underpinning effect of cancer in COVID-19 enhances this risk. Currently, we have limited nationwide data on MACCE events in cancer patients hospitalized with COVID-19. This study aims to identify demographic and clinical predictors of MACCE in this population. METHODS: We identified COVID-19-hospitalized cancer patients using the 2020 National Inpatient Sample. MACCE, inpatient mortality, and baseline demographics and comorbidities were assessed. Predictors of MACCE were calculated using multivariable regression analysis. RESULTS: Of 68,755 cancer patients hospitalized with COVID-19, 24% had MACCE, and 20.4% died in the hospital, with both outcomes being more significant among males, Asian or Pacific Islanders, and those in the fourth income quartile (all p<0.05). Comorbidities exhibited statistically significant associations for MACCE (all p<0.05). Higher adjusted odds of MACCE were found in age groups >65 (OR 4.17; 95% CI 2.94-5.91) and 45-64 (OR 1.77; 95% CI 1.26-2.48) than 18-44 years, self-paying patients (OR 2.15) than Medicare, urban non-teaching (OR 1.25) and urban teaching hospitalizations (OR 1.24) than rural, prior MI (OR 1.36; 95% CI 1.11-1.66), CKD (OR 1.37; 95% CI 1.22-1.54), severe sepsis (OR 2.75; 95% CI 2.42-2.13), respiratory failure (OR 2.67; 95% CI 2.41-2.96), and mechanical ventilation (OR 12.15; 95% CI 10.40-14.21). Compared to the Northeast, hospitals in the Midwest, West, and South had lower odds of MACCE. Obesity, tobacco use, hyperlipidemia, and prior chemotherapy also exhibited lower odds of MACCE (all p<0.05) (Table. 1). CONCLUSION: Our study using contemporary large-scale data found a concerning burden and higher risk of MACCE, particularly in the elderly, patients with CKD, prior MI, severe sepsis, respiratory failure, and mechanical ventilation.

Background: Limited research has focused on the rising incidence of major adverse cardiac and cerebrovascular events (MACCE) among young women (aged 18-44) with at least one traditional cardiovascular disease risk factor (CVD), especially in rural hospital settings. We aimed to address this research gap by providing insights into the burden of CVD in this population. Methods: Using data from the National Inpatient Sample (2019), we identified young women (aged 18-44) with at least one cardiovascular risk factor admitted to rural hospitals. Baseline demographics, comorbidities, and outcomes were assessed, including MACCE and all-cause mortality. Multivariable logistic regression was performed, adjusting for age, race, income, and comorbidities. Results: Among 179,410 young women, MACCE occurred in 2,455 individuals (1.4%), with varying rates among racial groups: whites (1.2%), blacks (2.4%), Hispanics (1.3%), Asian or Pacific Islanders (API) (2%), Native Americans (NA) (1.6%), and others (1%). All-cause mortality was observed in 385 women (0.2%), with rates of 0.2% for whites and 0.4% for blacks. Blacks had twice the event rates of MACCE, and all-cause mortality compared to whites. Comorbidities and substance abuse were associated with MACCE (P<0.001). In higher-income households, multivariable analysis adjusted for confounders revealed significantly higher odds of MACCE in blacks (OR 1.23, 95% CI 0.11-14.08), API (OR 4.48, 95% CI 1.06-18.93), and NA (OR 10.22, 95% CI 1.03-101.50) compared to whites. In contrast, mortality rates were lower for Hispanics than whites (OR 0.24, 95% CI 0.02-3.80) (all p < 0.001) (Table 1). Conclusion: In higher-income households, greater odds of MACCE were noted among blacks, API, and NA compared to whites. Future research should focus on understanding factors contributing to these disparities and developing interventions to prioritize equitable healthcare access for rural women across diverse ethnic and income classes.

INTRODUCTION: The relentless toll of cardiovascular disease in the United States demands a breakthrough in reliable and cost-effective prognostic markers. Amidst the limited knowledge surrounding the role of adiponectin in stable coronary artery disease (CAD), this study aims to unveil its power in predicting all-cause mortality and major adverse cardiovascular events (MACE) among patients with stable coronary artery disease (CAD). METHODS: We systematically screened PubMed, Scopus, and Google Scholar for articles until May 2023 to identify relevant studies. Random-effects model estimated the pooled odds ratio (OR) with 95% confidence intervals (CI), and I2 statistics assessed heterogeneity. The leave-one-out method was used for sensitivity analysis. RESULTS: Following the screening, five prospective studies involving 3225 patients with a median follow-up duration of 3.8 years were included. In the study population, hypertension, diabetes, hyperlipidemia, and smoking were prevalent risk factors, and common medications included angiotensin-converting enzyme inhibitors, beta-blockers, and statins. The pooled adjusted OR for all-cause mortality was 2.51 (95%CI: 1.36-4.62), with moderate heterogeneity (I2=65.51%, p=0.03), and the pooled adjusted OR for MACE was 1.04 (95%CI: 1.02-1.06), with no significant heterogeneity (I2=0%, p=0.68) (Fig. 1) . The leave-one-out sensitivity analysis showed that no single study significantly influenced the meta-analysis results, indicating robustness. CONCLUSION: Higher adiponectin levels were associated with higher odds of long-term mortality and MACE in stable CAD patients, highlighting its potential as a cost-effective marker for risk stratification and guiding management strategies. Further studies exploring the role of adiponectin can significantly impact clinical decision-making and resource allocation in cardiovascular care.