Prevalence Of Coronary Heart Disease Research Articles

Exploring the Factors Influencing Coronary Heart Disease Prevalence in the US Population: A Retrospective Observational Study.

Coronary heart disease (CHD) remains a significant global health concernand is characterized by inadequate blood supply to the myocardium due to the accumulation of plaque in the coronary arteries. Despite therapeutic advancements, prevalence disparities persist across various segments of the U.S. population, posing a significant challenge to healthcare systems. This study aims to find the prevalence disparities of CHD using Behavioral Risk Factor Surveillance System (BRFSS) data. A retrospective observational study was done using the 2022 BRFSS dataset on January 17, 2024. The study examined the presence of CHD as the dependent variable and investigated various independent variables. Descriptive and logistic regression analyses were conducted using the BRFSS Web Enabled Analysis Tool (Centers for Disease Control and Prevention, Atlanta, GA). Data management and storage utilized Microsoft Excel, and graphical analysis employed GraphPad Prism, version 9.4.1 (GraphPad Software, Inc., San Diego, CA). In demographics, respondents aged 65+ had higher CHD odds, while females exhibited lower risk than males. Hispanics had the lowest odds of CHD among all races. Socioeconomically, inability to work and retirees had higher CHD odds, as did income below $20,000 but ≥$15,000. Poor physical health increased CHD odds, as did having multiple healthcare providers. Medicare users had the highest CHD odds among insurance options. Significant disparities in CHD prevalence were seen across demographic, socioeconomic, health status, and healthcare access dimensions in the United States, emphasizing the urgent need for targeted interventions to address these disparities and improve overall public health outcomes.

Prevalence of familial hypercholesterolemia and coronary heart disease in a tertiary referral hospital in Lithuania

Prevalence of familial hypercholesterolemia and coronary heart disease in a tertiary referral hospital in Lithuania

High Throughput Plasma Proteomics and Risk of Heart Failure and Frailty in Late Life

ImportanceHeart failure (HF) and frailty frequently coexist and may share a common pathobiology, although the underlying mechanisms remain unclear. Understanding these mechanisms may provide guidance for preventing and treating both conditions.ObjectiveTo identify shared pathways between incident HF and frailty in late life using large-scale proteomics.Design, Setting, and ParticipantsIn this cohort study, 4877 aptamers (Somascan v4) were measured among participants in the community-based longitudinal Atherosclerosis Risk In Communities (ARIC) cohort study at visit 3 (V3; 1993-1995; n = 10 638) and at visit 5 (V5; 2011-2013; n = 3908). Analyses were externally replicated among 3189 participants in the Cardiovascular Health Study (CHS). Data analysis was conducted from February 2022 to June 2023.ExposuresProtein aptamers, measured at study V3 and V5.Main Outcomes and MeasuresOutcomes assessed included incident HF hospitalization after V3 and after V5, prevalent frailty at V5, and incident frailty between V5 and visit 6 (V6; 2016-2017; n = 4131). Frailty was assessed using the Fried criteria. Analyses were adjusted for age, gender, race, field center, hypertension, diabetes, smoking status, body mass index, estimated glomerular filtration rate, prevalent coronary heart disease, prevalent atrial fibrillation, and history of myocardial infarction. Mendelian randomization (MR) analysis was performed to assess potential causal effects of candidate proteins on HF and frailty.ResultsA total of 4877 protein aptamers were measured among 10 638 participants at V3 (mean [SD] age, 60 [6] years; 4886 [46%] men). Overall, 286 proteins were associated with incident HF after V3 (822 events; P < 1.0 × 10−5), 83 of which were also associated with incident after V5 (336 events; P < 1.7 × 10−4). Among HF-free participants at V5 (n = 3908; mean [SD] age, 75 [5] years; 1861 [42%] men), 48 of 83 HF-associated proteins were associated with prevalent frailty (223 cases; P < 6.0 × 10−4), 18 of which were also associated with incident frailty at V6 (152 cases; P < 1.0 × 10−3). These proteins enriched fibrosis and inflammation pathways and demonstrated stronger associations with incident HF with preserved ejection fraction (HFpEF) than HF with reduced ejection fraction. All 18 proteins were associated with both prevalent frailty and incident HF in CHS. MR identified potential causal effects of several proteins on frailty and HF.Conclusions and RelevanceIn this study, the proteins associated with risk of HF and frailty enrich for pathways related to inflammation and fibrosis as well as risk of HFpEF. Several of these proteins could potentially contribute to the shared pathophysiology of frailty and HF.

Atherogenic index of plasma as a predictor of coronary artery disease: a cohort study in south of Iran

BackgroundCoronary artery disease (CAD) is an atherosclerotic disease of an inflammatory nature. Previous studies examining the relationship between triglycerides and high-density lipoprotein cholesterol have highlighted the importance of plasma atherogenic index (AIP) as an important predictor of coronary heart disease. However, due to the lack of adequate information on this topic, this study aimed to investigate the relationship between AIP and coronary heart disease risk.ResultsThis study included 2,226 women and 1,690 men aged 35–70 years who participated in the Bandar Kong Cohort study and met the eligibility criteria. The data was collected using a checklist and questionnaires, which were designed by experienced individuals. After participants completed a registration form and gave informed consent, face-to-face interviews were conducted by trained experts. The validity and reliability of the questionnaire had been verified by the national cohort team prior to its use. The Ethics Committee of Hormozgan University of Medical Sciences (IR.HUMS.REC.1400.171) approved the study. Data from the initial cohort survey using SPSS software version 25, were analyzed to include several factors, including age, sex, smoking status, body mass index (BMI), physical activity level, socioeconomic status, AIP, systolic blood pressure, and diastolic blood pressure. The prevalence of coronary heart disease was found to be 7.5% higher in people with a BMI of 25 or higher. Also, Individuals with low physical activity had a higher prevalence. Individuals with CAD had significantly higher mean values for the AIP, age, systolic blood pressure, and diastolic blood pressure (0.46, 57.50, 128.43, and 81.10, respectively) compared to those without CAD. Furthermore, patients with CAD had lower years of education (2649.45 and 3.59) than individuals without CAD (P < 0.05). Importantly, our findings showed that AIP increased the odds ratio of coronary heart disease by 1.86 as an independent risk factor.ConclusionsBased on our investigation, the AIP is a valuable and independent predictive risk factor for coronary artery disease. This index can be utilized effectively due to its accessibility and affordability, making it a promising tool for risk assessment in clinical settings.

#1458 Adverse muscle composition predicts all-cause mortality in CKD

Abstract Background and Aims Sarcopenia is common in CKD and associates with morbidity and mortality. A rapid and standardized MRI (Magnetic Resonance Imaging) scan protocol allows an accurate muscle composition analysis by quantification of skeletal muscle volume and muscle fat infiltration (MFI). The combined observation of low muscle volume and high muscle fat infiltration, i.e. adverse muscle composition (AMC), is a prevalent muscle composition phenotype within CKD and associates to poor function, high prevalence of comorbidity, and an increased risk for coronary heart disease (CHD). It has also been shown that AMC is an independent predictor of all-cause mortality in patients with non-alcoholic fatty liver disease and in general population. In this study we aimed to investigate muscle composition as predictor of all-cause mortality within participants with CKD in the UK Biobank imaging study (UKB). Method This is a prospective study including UKB participants with CKD defined as having an eGFR cystatin C &amp;lt; 60 ml/min/1, 73 m2. A control group was created by matching each participant with CKD for sex, age, and BMI to four participants with normal eGFR. Cystatin C was analyzed based on blood samples at time of study enrolment 7-9 years prior to the MRI. Fat-tissue free thigh muscle volume and MFI were quantified using a rapid neck-to-knee water and fat separated MRI protocol and automated image analysis (AMRA® Researcher). For each participant, a personalized muscle volume z-score (sex- and body size-specific) was calculated and combined with MFI to divide the participants into four muscle composition phenotype groups; 1) normal muscle composition, 2) only low muscle volume, 3) only high MFI and 4) AMC, using previously published thresholds based on the whole UKB cohort. The thresholds were the 25th percentile (&amp;lt; -0.68 SD) for muscle volume z-score and the 75th percentile (men &amp;gt;7.69%; women &amp;gt;8.82%) for MFI. The mortality data were obtained through the UKB´s linkage to national death registries. All-cause mortality was investigated using Kaplan-Meier curves and Cox regression. Models within participants with CKD were crude and subsequently adjusted for sex, age, BMI, low hand grip strength (&amp;lt;16/27 kg for females/males), physical activity, smoking, alcohol, and previous diagnosis of cancer, prevalent CHD and type 2 diabetes, all assessed at the time of imaging. Results Conclusion AMC, determined by standardized MRI, was a strong predictor of all-cause mortality in CKD. The study results indicate that CKD patients with poor muscle health, identified as having both low muscle volume z-score and high MFI, have a significantly higher mortality risk. This vulnerable group would potentially benefit from targeted interventions and is also of specific interest when evaluating new treatments for CKD.

Association between Abdominal Aortic Calcification and Coronary Heart Disease in Essential Hypertension: A Cross-Sectional Study from the 2013-2014 National Health and Nutrition Examination Survey.

This study aimed to investigate the association between abdominal aortic calcification (AAC) and coronary heart disease (CHD) in essential hypertension (EH). This study included patients diagnosed with EH during the 2013-2014 NHANES survey cycle. The study cohort was categorized into the following four groups based on their AAC-24 score: no AAC (0); mild AAC (1-4); moderate AAC (5-15); and severe AAC (16-24). Logistic regression models were used to assess the association between AAC and CHD. Restricted cubic spline curves (RCS) were used to explore possible nonlinear relationships between AAC and CHD. The prevalence of CHD was found to be higher in the moderate AAC and severe AAC groups than in the group without AAC (40.1% versus 30.9%, 47.7% versus 30.9%). On a continuous scale, the fully adjusted model showed a 7% increase in the risk of CHD prevalence per score increase in AAC [OR (95% CI) = 1.07 (1.03-1.11)]. On a categorical scale, the fully adjusted model showed the risk of CHD prevalence in EH patients with moderate AAC and severe AAC was 2.06 (95%CI, 1.23-3.45) and 2.18 (1.09-5.25) times higher than that in patients without AAC, respectively. The RCS curve suggested a dose-response linear relationship between AAC and CHD. These findings highlight that in patients with EH, a higher severity of AAC is associated with a higher risk of CHD prevalence.

Deep Learning–Based Assessment of Built Environment From Satellite Images and Cardiometabolic Disease Prevalence

Built environment plays an important role in development of cardiovascular disease. Large scale, pragmatic evaluation of built environment has been limited owing to scarce data and inconsistent data quality. To investigate the association between image-based built environment and the prevalence of cardiometabolic disease in urban cities. This cross-sectional study used features extracted from Google satellite images (GSI) to measure the built environment and link them with prevalence of cardiometabolic disease. Convolutional neural networks, light gradient-boosting machines, and activation maps were used to assess the association with health outcomes and identify feature associations with coronary heart disease (CHD), stroke, and chronic kidney disease (CKD). The study obtained aerial images from GSI covering census tracts in 7 cities (Cleveland, Ohio; Fremont, California; Kansas City, Missouri; Detroit, Michigan; Bellevue, Washington; Brownsville, Texas; and Denver, Colorado). The study used census tract-level data from the US Centers for Disease Control and Prevention's 500 Cities project. The data were originally collected from the Behavioral Risk Factor Surveillance System that surveyed people 18 years and older across the country. Analyses were conducted from February to December 2022. GSI images of built environment and cardiometabolic disease prevalence. Census tract-level estimated prevalence of CHD, stroke, and CKD based on image-based built environment features. The study obtained 31 786 aerial images from GSI covering 789 census tracts. Built environment features extracted from GSI using machine learning were associated with prevalence of CHD (R2 = 0.60), stroke (R2 = 0.65), and CKD (R2 = 0.64). The model performed better at distinguishing differences between cardiometabolic prevalence between cities than within cities (eg, highest within-city R2 = 0.39 vs between-city R2 = 0.64 for CKD). Addition of GSI features both outperformed and improved the model that only included age, sex, race, income, education, and composite indices for social determinants of health (R2 = 0.83 vs R2 = 0.76 for CHD; P <.001). Activation maps from the features revealed certain health-related built environment such as roads, highways, and railroads and recreational facilities such as amusement parks, arenas, and baseball parks. In this cross-sectional study, a significant portion of cardiometabolic disease prevalence was associated with GSI-based built environment using convolutional neural networks.

Higher LDL-C/HDL-C Ratio Is Associated with Elevated HbA1c and Decreased eGFR Levels and Cardiac Remodeling in Elderly with Hypercholesterolemia.

Background: This study aims to explore the relationship of the low-density lipoprotein cholesterol (LDL-C)/high-density lipoprotein (HDL-C) ratio with glycated hemoglobin (HbA1c), renal dysfunction, coronary heart disease (CHD) and cardiac structure and function in elderly patients with hypercholesterolemia. Methods: A total of 1129 hospitalized Chinese elderly (aged ≥ 65 years) with hypercholesterolemia were collected retrospectively. The patients were divided into low (<2.63), moderate (≥2.63 to <3.33) and high (≥3.33) LDL-C/HDL-C ratio groups according to the tertiles of LDL-C/HDL-C. Results: Regression analysis of the LDL-C/HDL-C ratio with metabolic and echocardiographic parameters revealed that a high LDL-C/HDL-C ratio (≥3.33) was associated independently with male gender, elevated HbA1c, decreased estimated glomerular filtration rate (eGFR), prevalent CHD and left ventricular dilatation (all p < 0.05). Conclusions: A high LDL-C/HDL-C ratio was associated with male gender, increased HbA1c, decreased eGFR, CHD and enlarged left ventricle in elderly with hypercholesterolemia.

Association of advanced glycation end products with ear lobe crease: A cross-sectional study.

Several studies have demonstrated a significant association between the presence of the ear lobe crease (ELC) and cardiovascular disease. Advanced glycation end-products (AGEs) can affect the structures and functions of proteins and contribute to the development of diabetic complications. However, few studies have reported the relationship between AGEs and ELC. The purpose of this study was to investigate the correlation of skin autofluorescence (SAF)-AGEage (SAF-AGEs × age/100) with ELC. This cross-sectional study enrolled 6500 eligible participants from two communities in Beijing. Skin autofluorescence (SAF) was used to measure skin AGEs (SAF-AGEs). SAF-AGEage was defined as AGEs × age/100. Binary logistic regression analysis and linear regression analysis nested in logistic models were applied to test outcomes. The overall prevalence of ELC with an average age of 62.7 years participants was 57.1% (n = 3714). Age, fasting blood glucose, systolic blood pressure, and lipoprotein cholesterol were all greater in participants with ELC. ELC-positive participants had higher prevalence of coronary heart disease. Logistic analysis showed a significantly positive relationship between quartiles of SAF-AGEage and ELC (odds ratio [OR] 1.526, 95% CI 1.324-1.759; OR 2.072, CI 1.791-2.396; and OR 2.983, CI 2.551-3.489) for the multivariate-adjusted models, respectively. Stratified research revealed that those with a history of diabetes, hypertension, or coronary heart disease experienced the connection between SAF-AGEage and ELC. ELC is associated with coronary heart disease, and the SAF-AGE has a potential role in ELC development in elder people.

Artificial intelligence-based assessment of built environment from Google Street View and coronary artery disease prevalence.

Built environment plays an important role in the development of cardiovascular disease. Tools to evaluate the built environment using machine vision and informatic approaches have been limited. This study aimed to investigate the association between machine vision-based built environment and prevalence of cardiometabolic disease in US cities. This cross-sectional study used features extracted from Google Street View (GSV) images to measure the built environment and link them with prevalence of coronary heart disease (CHD). Convolutional neural networks, linear mixed-effects models, and activation maps were utilized to predict health outcomes and identify feature associations with CHD at the census tract level. The study obtained 0.53 million GSV images covering 789 census tracts in seven US cities (Cleveland, OH; Fremont, CA; Kansas City, MO; Detroit, MI; Bellevue, WA; Brownsville, TX; and Denver, CO). Built environment features extracted from GSV using deep learning predicted 63% of the census tract variation in CHD prevalence. The addition of GSV features improved a model that only included census tract-level age, sex, race, income, and education or composite indices of social determinant of health. Activation maps from the features revealed a set of neighbourhood features represented by buildings and roads associated with CHD prevalence. In this cross-sectional study, the prevalence of CHD was associated with built environment factors derived from GSV through deep learning analysis, independent of census tract demographics. Machine vision-enabled assessment of the built environment could potentially offer a more precise approach to identify at-risk neighbourhoods, thereby providing an efficient avenue to address and reduce cardiovascular health disparities in urban environments.

Abstract P439: Atherosclerotic Cardiovascular Risk Factor Burden Among Marijuana Users in the US Population

Background: The prevalence of marijuana use in the US is increasing. Marijuana use has been associated with increased atherosclerotic cardiovascular disease (ASCVD) events. The ASCVD risk factor burden among marijuana users compared with non-users and tobacco users has not been defined. We sought to define ASCVD risk factor burden among marijuana users in a nationally representative sample of the US population. Methods: We analyzed cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) from the 2017-2018 cycle including 4991 participants aged 18-59 representing 223 million US adults. Participants were placed in 4 groups: marijuana and cigarette user (MS), exclusive marijuana user (M), exclusive cigarette user (S), and non-users (NS). ASCVD risk factors were assessed and compared using chi-squared and ANOVA with Tukey’s adjustment for multiple hypothesis testing. Results: The N=4991 participants representing 223 million US adults were a mean 51 years old, 54.82% female and BMI of 32.53. The N=1691 M-users were compared to the N=2552 NS, N=2439 S-users, and N=1020 MS users (Table 1). The M-users were younger, mean age (38.8 years) with a higher BMI (32.9 kg/m 2 ) compared to exclusive smokers, dual-users and non-users. Prevalent coronary heart disease differed by use-group (p &lt; 0.05). Conclusion: Exclusive M-users and dual users had higher prevalent CHD. ASCVD risk factor burden differed slightly between the groups.

Identifying the health benefits of city bike infrastructure expansion policy

ABSTRACT The aim of this study was to understand how policy actions implemented by city governments to improve infrastructure within the built environment can in turn influence healthy behaviors and population health. The authors investigated the associations between policy actions implemented by city governments to improve biking infrastructure and multiple health outcomes including leisure-time physical inactivity, obesity and coronary heart disease (CHD). In addition, this study tested if bike use for commuting and leisure-time physical activity were mediators between policy actions to improve biking infrastructure and health outcomes, and whether the health effects of bike infrastructure were different in cities of different population density. We merged local sustainability survey data with city-level chronic disease measures for the largest cities in the U.S. (n = 457). Results from regressions using Ordinary Least Squares estimation and mediation tests showed policies implemented to improve biking infrastructure were associated with lower prevalence of leisure-time physical inactivity, obesity and CHD. These relationships were most notable in medium-density cities (1,500–3,000/sq. mi). Moreover, leisure-time physical activity and active commuting mediated the relationship between bike infrastructure improvement policies and health outcomes. This study demonstrated the value of a policy-based intervention in enhancing population health.

Serum soluble alpha-klotho klotho and cognitive functioning in older adults aged 60 and 79: an analysis of cross-sectional data of the National Health and Nutrition Examination Survey 2011 to 2014

ObjectivesKlotho, consisting of membrane klotho and soluble alpha-klotho, is found to be associated with better cognitive outcomes in small samples of the aged population. We aimed to examine the association of serum soluble alpha-klotho with cognitive functioning among older adults using a nationally representative sample of U.S. older adults.MethodA total of 2,173 U.S. older adults aged 60–79 years in the National Health and Nutrition Examination Survey from 2011 to 2014 were included in this cross-sectional analysis. Serum soluble alpha-klotho was measured in the laboratory and analyzed with an ELISA kit. Cognitive function was measured using the Consortium to Establish a Registry for Alzheimer’s Disease Word Learning subtest (CERAD-WL) immediate and delayed memory, the Animal fluency test (AFT), and the Digit Symbol Substitution Test (DSST). Test-specific and global cognition z-scores were calculated based on sample means and standard deviations. Multivariable linear regression models were applied to examine the association of quartiles and continuous value of serum soluble alpha-klotho with test-specific and global cognition z-scores. Subgroup analysis was conducted by sex. The following covariates were included in the analysis- age, sex, race/ethnicity, education, depressive symptoms, smoking status, body mass index (BMI), physical activity, stroke, prevalent coronary heart disease, total cholesterol, and systolic blood pressure. All the information was self-reported or obtained from health exams.ResultsSerum soluble alpha-klotho level in the lowest quartile was associated with lower z-scores for DSST (beta [β] =-0.13, 95% confidence interval [CI]: -0.25, -0.01). For subgroup analysis, serum soluble alpha-klotho level in the lowest quartile was associated with lower z-scores for DSST (β=-0.16, 95% CI: -0.32, -0.003) and global cognition (β=-0.14, 95% CI: -0.28, -0.01) among female participants. No association was found between continuous serum soluble alpha-klotho and cognitive functioning among the participants.ConclusionsLower serum soluble alpha-klotho quartile was associated with poorer cognitive functioning among older women. Future studies are expected to examine the longitudinal association between klotho levels and cognitive outcomes.

Patients with Coronary Heart Disease with Lipid Profile

Background: The lipid profile and their ratio are important in management and follow up of patients with coronary heart disease. We studied the lipid profile and their ratios with proven coronary artery disease. Methods: It was retrospective study to determine the lipid profile and their ratios in patients with proven coronary artery disease at Shakuntala Pathology Lab., Nagpur. 200 patients were studied. Results: Out of 200 patients studied, 126 (63%) were males while 74 (37%) were females. out of 126 males,12 (9.52%) had raised cholesterol values of &gt;200 mg/dL. 20 (15.87%) had raised triglyceride values of &gt;200 mg/dL. 30 (23.80%) had lower HDL values of 150 mg/dL. 90 (71.42%) had raised values of &gt;3.5 for cholesterol to HDL ratio. Out of 74 female patients, 20 (27.02%) patients had raised cholesterol values. 12 (16.21%) patients had raised triglycerides values. 13 (17.56%) patients had lower HDL values. 6 (8.10%) patients had raised LDL values. 50 (67.56%) patients had raised values for cholesterol to HDL ratio. Conclusions: Our study shows more prevalence of coronary heart disease in males than females. Hypercholesteremia and hypertriglyceridemia was more prevalent in females. HDL values were lowered in more number of males than females. LDL values were raised in more number of females than males. Total cholesterol to HDL ratio was raised in more number of males than females.

The severity of chronic heart failure and the parameters of daily blood pressure profile in patients with coronary heart disease

Aim: Although the prevalence of coronary heart disease (CHD) and hypertension which are the most common causes of the development and progression of chronic heart failure (CHF) is high, 24-hour ambulatory blood pressure (BP) monitoring (ABPM) in patients with CHF is not mandatory to be performed. The growing number of evidence suggests that excessive decrease in BP which clearly reflects increased BP variability (BPV) affects the survival of patients with heart failure (HF). The objective of the study was to investigate the relationship between the parameters specific to CHF severity and features of daily BP profiles in patients with ischemic CHF and hypertension. Methods: Ninety patients with functional class II–IV of CHF and CHD (the main group) and 50 non-CHF patients with hypertension (the comparative group) were examined. The transthoracic echocardiography (TTE) [atrial end-systolic dimension (ESD), ventricular end-diastolic dimension (EDD), left ventricular mass index (LVMI), and left ventricular ejection fraction (LVEF)] and 24-hour ABPM (BPV parameters and proportions of hypotensive episodes) were performed. The relationships between the abovementioned parameters were evaluated using the univariate correlation analysis and stepwise multiple linear regression. Results: Higher functional class of CHF is found to be associated with a higher incidence of daytime systolic BP (SBP) decline and nighttime SBP and diastolic BP (DBP) variability while higher LVEF is related to the hypotensive episodes regardless of CHF. Conclusions: It appears that the larger trials involving CHF patients with reduced LVEF should be conducted to clarify the obtained results.

The Impact of Nurse-led Interventions on Improving Self-management and Quality of Life for Patients with Heart Failure

According to the American Heart Association, over 5 million Americans suffer from heart failure, and an additional 500,000 are diagnosed with the condition every year. It's crucial that you comprehend the nature of the illness and your possibilities for treatment because of this. We provide you the inside scoop so you can give this expanding patient population the finest treatment possible. According to National Institutions of Health, It is anticipated that the number of fatalities in India from CVD will increase from 2.26 million in 1990 to 4.77 million in 2020. According to estimates throughout the past few decades, the prevalence of coronary heart disease in India has varied between 1.6% and 7.4% in rural areas and between 1% and 13.2% in urban areas. Heart failure remains the most common cause of hospitalization for adults over 65, making it a serious public health concern in the US. Regretfully, there isn't much hope for this illness: within four years, 50% of heart failure sufferers will pass away from the condition. Heart failure claims the lives of over 287,000 individuals annually, and 40% of patients who are hospitalized for the illness either pass away or return within a year. Not to add that in 2006, the anticipated yearly cost of treating heart failure was $29.6 billion. In this paper, we will discuss through the pathophysiology, causes, and symptoms of heart failure in this post. I'll also cover key diagnostic resources, available treatments, and patient education techniques to assist your patient take care of his condition

Associations of asymptomatic coronary heart disease in a cohort of stable type 2 diabetic subjects in a tertiary health center in south eastern Nigeria: A cross sectional study

Background: Coronary heart disease (CHD) is a type of heart disease where the lumina of the major arteries of the heart (coronary arteries) are narrowed by a build-up of plaque with a resultant limitation of blood flow to and oxygenation of the heart. Coronary heart disease can pose a diagnostic challenge in diabetic subjects due to the fact that it is often asymptomatic with a resultant lack of overt clinical complaint by the patients. It is an important cause of diabetes-associated morbidity and mortality and also a huge contributor to the cost of diabetes care. Objective: To determine the association between CHD and age, sex, cigarette smoking, duration of diabetes, central obesity, glycaemic control, hypertension, chronic kidney disease (CKD), stroke, transient ischaemic attack (TIA), dyslipidaemia, lack of exercise and metabolic syndrome in type 2 diabetic subjects attending the diabetes outpatient clinic of Nnamdi Azikiwe University Teaching Hospital, Nnewi in South Eastern Nigeria. Materials and Methods: This was a cross-sectional, observational study comprising 136 clinically stable T2DM subjects that were asymptomatic of coronary heart disease. The participants had two contacts with the researcher. Firstly, all the participants were evaluated with resting ECG for the diagnosis of CHD, 30 subjects had CHD while 106 had not. Next, the 30 subjects that had CHD and 98 of the 106 that had not, were met a second time on another clinic visit where medical history was extracted and anthropometric measurements were done. Next, biochemical tests, which included fasting blood glucose (FBG), glycated haemoglobin (HbA1c), fasting lipid profile (FLP) and serum creatinine were done and the glomerular filtration rate estimated using the Modification of Diet in Renal Disease (MDRD) calculator. Data were analyzed using the Statistical Package for Social Sciences (SPSS) version 25 (Chicago, IL, USA). The level of significance was set at p &lt; 0.05. Results: A total of 128 subjects completed the study and had their data analyzed. 30 subjects had CHD while 98 had not. There was significant association between CHD and TIA (p = 0.040), but no significant association between CHD and age (p = 0.959), sex (p = 0.679), educational status (p = 0.094), cigarette smoking (p = 1.000), duration of diabetes (p = 0.335), central obesity (p = 0.726), glycaemic control (p = 1.000), hypertension (p = 1.000), CKD (p = 0.570), stroke (p = 0.141), dyslipidaemia (p = 0.290), exercise (p = 0.641) and metabolic syndrome (p = 0.633) respectively among the subjects. Conclusion: There was a high prevalence of asymptomatic CHD among stable type 2 diabetic subject and with the exception of TIA, there was no significant association between CHD and all the other risk factors for CHD that were studied, although these risk factors were found more among the subjects that had CHD compared with those that had not.

Prevalence of Cardiometabolic Diseases Among Racial and Ethnic Subgroups in Adults - Behavioral Risk Factor Surveillance System, United States, 2013-2021.

Although diabetes and cardiovascular disease account for substantial disease prevalence among adults in the United States, their prevalence among racial and ethnic subgroups is inadequately characterized. To fill this gap, CDC described the prevalence of diagnosed cardiometabolic diseases among U.S. adults, by disaggregated racial and ethnic subgroups, among 3,970,904 respondents to the Behavioral Risk Factor Surveillance System during 2013-2021. Prevalence of each disease (diabetes, myocardial infarction, angina or coronary heart disease, and stroke), stratified by race and ethnicity, was based on self-reported diagnosis by a health care professional, adjusting for age, sex, and survey year. Overall, mean respondent age was 47.5 years, and 51.4% of respondents were women. Prevalence of cardiometabolic diseases among disaggregated race and ethnicity subgroups varied considerably. For example, diabetes prevalence within the aggregated non-Hispanic Asian category (11.5%) ranged from 6.3% in the Vietnamese subgroup to 15.2% in the Filipino subgroup. Prevalence of angina or coronary heart disease for the aggregated Hispanic or Latino category (3.8%) ranged from 3.1% in the Cuban subgroup to 6.3% in the Puerto Rican subgroup. Disaggregation of cardiometabolic disease prevalence data by race and ethnicity identified health disparities among subgroups that can be used to better help guide prevention programs and develop culturally relevant interventions.

Real-time three-dimensional transthoracic echocardiography in quantification of left ventricular dyssynchrony

Aim. To compare endocardial and epicardial left ventricular (LV) pacing using real-time electrocardiography (ECG)-synchronized three-dimensional echocardiography (3DE).Methods. Experimental intraoperative study included 88 points obtained from 12 patients with compensated heart failure of II-IV functional class NYHA (LV ejection fraction &lt; 35%) and cardiac resynchronization therapy indications - ECG pattern of complete left bundle branch block (LBBB) and QRS complex duration &gt; 150 ms. During isolated LV pacing as part of cardiac resynchronization therapy implantation procedure endocardial and epicardial stimulation points matched under fluoroscopic control using quadripolar coronary sinus leads and endocardial electrodes for temporary pacing were obtained. The overall number of corresponding pacing sites included 44 endocardial and 44 epicardial stimulation positions. The mean age of patients was 68.5 [63; 73.5] years, 83% males (n=10). Before study enrollment, 12-channel ECG, echocardiography, and a six-minute walk test were performed for all participants along with cardiac magnetic resonance imaging and control coronary angiography if indicated. The prevalence of coronary heart disease was 50% (n=6) while dilated cardiomyopathy was the most common etiology of chronic heart failure in other cases. Intraoperative ECG with estimation of paced QRS complex morphology at each point was registered via LabSystem Pro Electrophysiological Recording System (Bard Electrophysiology, USA). 3DE was performed using TomTec and Philips Qlab 3DQ Advanced software (Philips Medical Systems, USA).Results. Three-dimensional parametric imaging of LV regional segmental excursion and myocardial contractility using 3DE revealed statistically significant difference in semi-quantative parameters such as ExcAvg (p&lt;0.001), ExcMax (p=0.001), ExcMin (p&lt;0.001) and LV ejection fraction based on 3D modelling (p=0.003) while endocardial pacing was more beneficial. During the course of endocardial stimulation, the 3DE dyssynchrony index estimated at the 2nd stimulation site was also significantly lower (p=0.03). Identical dyssynchrony parameters valid for the 16 and 12-segment 3D models (SDI-16, Tmsv-12SD) (at p=0.06) demonstrated only a tendency for significant difference. The duration of QRS complex at the time of endocardial pacing was significantly shorter (&lt;190 [179;215] ms) (p=0.0008). Semi-quantitative and quantitative 3DE parameters showed the benefit of endocardial pacing resulting in cardiac contractility improvement with less dyssynchrony and LV volume reducing during intraoperative period.Conclusion. Endocardial pacing has potential benefit over the epicardial pacing represented by intraoperative dynamics of LV global and local contractility, intraventricular dyssynchrony estimated by 3DE and also ECG criteria. 3DE is helpful in more precise and reproducibile determing of late activation zone for target LV lead placement that is more manoeuvrable in case of endocardial stimulation.

Comparison of seven surrogate insulin resistance indexes for prediction of incident coronary heart disease risk: a 10-year prospective cohort study.

There were seven novel and easily accessed insulin resistance (IR) surrogates established, including the Chinese visceral adiposity index (CVAI), the visceral adiposity index (VAI), lipid accumulation product (LAP), triglyceride glucose (TyG) index, TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC) and TyG-waist to height ratio (TyG-WHtR). We aimed to explore the association between the seven IR surrogates and incident coronary heart disease (CHD), and to compare their predictive powers among Chinese population. This is a 10-year prospective cohort study conducted in China including 6393 participants without cardiovascular disease (CVD) at baseline. We developed Cox regression analyses to examine the association of IR surrogates with CHD (hazard ratio [HR], 95% confidence intervals [CI]). Moreover, the receiver operating characteristic (ROC) curve was performed to compare the predictive values of these indexes for incident CHD by the areas under the ROC curve (AUC). During a median follow-up period of 10.25 years, 246 individuals newly developed CHD. Significant associations of the IR surrogates (excepted for VAI) with incident CHD were found in our study after fully adjustment, and the fifth quintile HRs (95% CIs) for incident CHD were respectively 2.055(1.216-3.473), 1.446(0.948-2.205), 1.753(1.099-2.795), 2.013(1.214-3.339), 3.169(1.926-5.214), 2.275(1.391-3.719) and 2.309(1.419-3.759) for CVAI, VAI, LAP, TyG, TyG-BMI, TyG-WC and TyG-WHtR, compared with quintile 1. Furthermore, CVAI showed maximum predictive capacity for CHD among these seven IR surrogates with the largest AUC: 0.632(0.597,0.667). The seven IR surrogates (excepted for VAI) were independently associated with higher prevalence of CHD, among which CVAI is the most powerful predictor for CHD incidence in Chinese populations.