Incidence Of Heart Disease Research Articles

Associations Between Mosaic Loss of Sex Chromosomes and Incident Hospitalization for Atrial Fibrillation in the United Kingdom.

Mosaic loss of chromosome Y (mLOY) in leukocytes of men reflects genomic instability from aging, smoking, and environmental exposures. A similar mosaic loss of chromosome X (mLOX) occurs among women. However, the associations between mLOY, mLOX, and risk of incident heart diseases are unclear. We estimated associations between mLOY, mLOX, and risk of incident heart diseases requiring hospitalization, including atrial fibrillation, myocardial infarction, ischemic heart disease, cardiomyopathy, and heart failure. We analyzed 190 613 men and 224 853 women with genotyping data from the UK Biobank. Among these participants, there were 37 037 men with mLOY and 13 978 women with mLOX detected using the Mosaic Chromosomal Alterations caller. Multivariable Cox regression was used to estimate hazard ratios (HRs) and 95% CIs of each incident heart disease in relation to mLOY in men and mLOX in women. Additionally, Mendelian randomization was conducted to estimate causal associations. Among men, detectable mLOY was associated with elevated risk of atrial fibrillation (HR, 1.06 [95% CI, 1.03-1.11]). The associations were apparent in both never smokers (HR, 1.07 [95% CI, 1.01-1.14]) and ever smokers (HR, 1.05 [95% CI, 1.01-1.11]) as well as men aged >60 and ≤60 years. Mendelian randomization analyses supported causal associations between mLOY and atrial fibrillation (HRMR-PRESSO, 1.15 [95% CI, 1.13-1.18]). Among postmenopausal women, we found a suggestive inverse association between detectable mLOX and atrial fibrillation risk (HR, 0.90 [95% CI, 0.83-0.98]). However, associations with mLOY and mLOX were not found for other heart diseases. Our findings suggest that mLOY and mLOX reflect sex-specific biological processes or exposure profiles related to incident atrial fibrillation requiring hospitalization.

A Comparative Examination of Machine Learning Algorithms for Predicting Cardiovascular Disease

Over the previous few years, India’s heart disease incidence has varied between 1.2% and 13.2% in urban areas and 1.6% and 7.4% in rural areas. India would probably have more CVD deaths in 2020 which is 4.77 million compared to 2.26 million in 1990. Worldwide, 200 million individuals are estimated to be affected by heart disease. Heart disease affects over 110 million men and 80 million women globally. This study explores the use of machine learning (ML) with various models and data to predict cardiovascular illness with the goal of improving accuracy. Clinician parameters, lifestyle indicators, and demographic data are used to train and assess an assortment of machine learning methods, including Logistic Regression, Support Vector Machines, Random Forests, Decision Trees, and Naive Bayes.

The Mortality of Politics: An American Paradox

Introduction: The USA has the poorest health statistics of any high-income country. Political polarization has risen dramatically; newer safety net programs (the Affordable Care Act [ACA]) are unevenly provided because many Republican-leaning states refused expanded Federal coverage. Democratic programs have reduced physician leadership of medicine. Both have been deleterious. Here, we investigated associations among four key health measures two of which directly impact pregnancy outcomes and two that affect all patients by percentage of each state that voted for the Republican versus Democratic candidate in the 2020 presidential election. Methods: For each state, we used public, non-partisan databases to assess the incidence of COVID, maternal, and infant mortality per 100,000 population and average life expectancy. Correlations among these four outcome variables and percentage Republican vote were calculated (r), contextualized by measuring associations with related variables including COVID vaccination rates, access to medical care, and incidences of heart disease, obesity, diabetes, gunshot deaths, and automotive fatalities. Results: COVID mortality, maternal and infant mortality, and life expectancy were highly correlated with percentage Republican (“red”) vote per state. If “red” states had vaccination rates equivalent to Democratic-leaning (“blue”) states, 72,000 deaths could have been avoided. Overall, “red” states have lower health metrics, reduced access to care, and higher comorbidities. Conclusion: The percent Republican vote was strongly associated, but not the whole answer, with worse health outcomes for multiple key measures of public health including mortality, access to care, and various comorbidities. Overall, the ACA has improved patient access to care but has also led to “maternity care deserts” disproportionately in rural areas in “red” states. Translating insurance coverage into improved care and outcomes requires further analysis and will require multi-pronged approaches including expanding coverage and incentivizing quality care.

Luteinizing hormone is independently associated with high-sensitive cardiac troponin T elevation in postmenopausal T2DM patients: A cross-sectional study.

It is known that the risk of ischemic heart disease increases in patients with type 2 diabetes mellitus (T2DM). For female patients, the incidence of heart disease can be even greater after menopause, accompanied by dramatic changes in sex hormones. We investigated the correlations between sex hormones and markers of ischemic heart diseases in postmenopausal females with T2DM patients. This cross-sectional study collected data from 324 hospitalized postmenopausal females with T2DM. Multiple linear regression analyses were conducted to determine the correlations between sex hormones and cardiac markers including high-sensitive cardiac troponin T (hs-cTnT) and N-terminal prohormone of brain natriuretic peptide (NT-proBNP) levels. Multiple linear regression analyses revealed that luteinizing hormone (LH) was positively and independently associated with hs-cTnT concentrations in postmenopausal females with T2DM (β = 0.189, p = 0.002). Postmenopausal females with T2DM and subclinical myocardial injury had higher LH levels than those without subclinical myocardial injury (29.67 vs. 25.08 mIU/mL, p < 0.001). A multivariate logistic regression analysis confirmed an independent and significant association between elevated LH and subclinical myocardial injury in postmenopausal females with T2DM (adjusted odds ratio [OR] = 1.077, 95% confidence interval [CI], 1.033-1.124; p < 0.001). As another gonadotropin, the follicle-stimulating hormone did not show independent correlations with hs-cTnT or NT-proBNP (p > 0.05). Neither estrogen nor testosterone was correlated with cardiac markers. Elevated LH levels were positively and independently associated with increased hs-cTnT levels in postmenopausal women with T2DM. Our findings suggest that LH could serve as a potential marker for assessing the risk of subclinical myocardial injury in postmenopausal females with T2DM.

Optimization of multidimensional feature engineering and data partitioning strategies in heart disease prediction models

The relentless rise in heart disease incidence, a leading global cause of death, presents a significant public health challenge. Precise prediction of heart disease risk and early interventions are crucial. This study investigates the performance improvement of heart disease prediction models using machine learning and deep learning algorithms. Initially, we utilized the Heart Failure Prediction Dataset from Kaggle. After preprocessing to ensure data quality, three distinct feature engineering techniques were applied: PCA for dimensionality reduction, ET for feature selection, and Pearson's correlation coefficient for feature selection. We assessed their impact on model performance. The dataset was then partitioned into three different data split ratios—1:9, 2:8, and 3:7—to determine their specific effects on model performance. Twelve machine learning classifiers—LGBM, Adaboost, XGB, RF, DT, KNN, LR, GNB, ET, SVC, GB, and Bagging—were trained and evaluated based on five key metrics: accuracy, recall, precision, F1 score, and training time. The influence of different feature engineering methods and data partitioning ratios on model performance were systematically analyzed using paired-sample t-tests. Among the feature engineering methods compared, the Bagging classifier, when combined with feature selection via ET, exhibited superior performance. It achieved an accuracy of 97.48 % and an F1-Score of 97.48 % with a data split ratio of 1:9 between the test and training sets. With a 2:8 split, the accuracy was 94.96 % and the F1-Score was 94.95 %. For a 3:7 split, the accuracy was 94.12 % and the F1-Score was 94.11 %. Paired sample T-test results indicate that feature selection using Pearson correlation coefficient can shorten training duration, but this also leads to a decline in classifier performance. After applying PCA dimensionality reduction, compared with the control group, there was no significant difference in the training efficiency and efficacy of the classifier. However, feature selection through ET significantly reduced the training time for various classifiers while ensuring their performance.

Relation of Cognitive Reserve Indicator to Heart Disease and Cardiac Structure and Function: A Large Community-Based Longitudinal Study.

High cognitive reserve (CR) has been related to lower dementia risk, but its association with heart disease (HD) is unknown. We aimed to explore the relation of CR to HD and cardiac structure and function. Within the UK Biobank, 349 907 HD-free participants were followed up. A composite CR indicator involving education/occupation attainment/television viewing time/confiding frequency/social connection frequency/variety of leisure activities was generated, and further categorized into low/moderate/high levels. Incident HD, including coronary HD, cardiac arrhythmia, and heart failure, was ascertained on the basis of medical records. During the follow-up, a subsample (n=31 182) underwent cardiac magnetic resonance imaging to assess ventricular structure and function. Data were analyzed using Cox regression, Laplace regression, and linear regression. Compared with low CR, the hazard ratio and 95% CI of any HD for high CR was 0.78 (0.75-0.80) (including 0.68 [0.66-0.71] for coronary HD, 0.91 [0.87-0.95] for cardiac arrhythmia, and 0.63 [0.58-0.68] for heart failure). Furthermore, high CR was associated with delayed HD onset by 1.59 (95% CI, 1.37-1.82) years compared with low CR. In cardiac magnetic resonance imaging data analysis, compared with low CR, high CR was associated with larger left ventricular end-diastolic volume (β, 0.13 [95% CI, 0.09-0.17]), left ventricular end-systolic volume (β, 0.05 [95% CI, 0.01-0.10]), left ventricular stroke volume (β, 0.16 [95% CI, 0.12-0.21]), and left ventricular ejection fraction (β, 0.08 [95% CI, 0.03-0.13]). High CR is associated with favorable HD health. Our findings suggest that the beneficial effect of CR is not limited to dementia but also HD.

Research on the Influence Factors of Heart Disease

Heart disease accounts for almost 30% of all deaths worldwide and about 18 million deaths each year, making it the primary cause of death and disability worldwide. Recent research highlights variations in incidence rates and causative factors among different populations and regions, underscoring the need for detailed studies to develop effective prevention and treatment strategies. This article explores the various factors that influence heart disease. Although many studies have been done to show that the incidence of heart disease is related to dietary habits, genes, and other factors, there are still many details that should be investigated. This paper focuses on determining which factors have effects on the incidence of heart disease, such as age, gender, and some diseases. Binary logistic regression is used to statistically analyse the data and found that certain factors, such as gender, chest pain, thallium stress, exercise-induced ST depression and major fluoroscopy vessels were associated with the development of heart disease. The use of binary logistic regression modelling enabled the study to quantify the impact of these factors and provided a useful tool for predicting heart disease risk. The study’s findings serve as a valuable resource for the formulation of heart disease prevention and treatment plans.

Association of complete blood count parameters with the risk of incident pulmonary heart disease in pneumoconiosis: a retrospective cohort study

BackgroundPneumoconiosis mostly combines pulmonary and cardiovascular diseases, among which pulmonary heart disease (PHD) is of major concern due to its significant impact on the survival of pneumoconiosis patients. White cell...

The Effectiveness of Early Detection of Heart Disease and Health Promotion on Attitude and Lifestyle Changes of Residents At Risk Of Heart Disease Post-Covid-19 Pandemic

During the Covid-19 pandemic, heart disease patients were at very high risk of experiencing severe complications if exposed to the virus. One important effort in preventing cardiovascular diseases is to identify the cardiovascular risk factors in each individual. There are several models for detecting risk, one of which is the Jakarta Cardiovascular Score. Health promotion is also an effort to manage modifiable risk factors for heart disease. Health promotion is expected to prevent risky behaviors that lead to an increase in heart disease incidence in the long term. This study aims to assess the effectiveness of early detection and health promotion in changing the attitudes and lifestyles of residents at risk of heart disease post-Covid-19 pandemic. The research method used in this study is a quasi-experimental design with one group of 30 respondents. The study was conducted in the working area of the Pasar Minggu District Health Center in Jakarta. The results showed that after the intervention, which included early detection and health promotion, there was a change in attitude by 0.8 points, from 88.13 (before intervention) to 88.95 (after intervention). The T-test results showed a p-value of 0.004, indicating a statistically significant difference between before and after the intervention. The respondents' lifestyle also changed by 5.5 points, from 66.03 (before intervention) to 71.62 (after intervention), with a p-value of 0.004, indicating a statistically significant difference between before and after the intervention.

Incidence of heart disease and stroke among patients with bipolar disorder

Abstract Background Increased vulnerability to cardiovascular diseases (CVD) and stroke has been observed among people with mental disorders, such as bipolar disorder (BP). Yet, the evidence for the association between severe mental disorders and CVD and stroke events remains inconclusive. Purpose By running a cohort study based on large retrospective data, we aimed to establish the relative risk of CVD problems and stroke in patients admitted to the hospital and diagnosed with BP. Methods The study was conducted on electronic health records provided by 113 healthcare organizations worldwide from the TriNetX Global Collaborative Network, containing at least 690,946 patients with BP symptoms. The assessment was focused on the first incidence of ischemic heart diseases, nontraumatic brain hemorrhage, or cerebral infarction among patients after BP diagnosis. After propensity score matching age, gender, race and comorbidities, the rates were compared against a cohort of patients with no mental, behavioral, or neurodevelopmental disorders who also suffered from similar CVD and stroke events. In addition, Kaplan-Meier Analysis was performed to compare their survivability to CVD, taking into account patient censoring. Results Patient count after applying the score matching yielded 532,082 per cohort. The odds ratio (OR) of ischemic heart diseases, nontraumatic brain hemorrhage, or cerebral infarction on BP compared to people without any mental disorder was equal to 2.349, indicating a significantly elevated risk for such events. The Kaplan-Meier analysis showed that patients with BP diagnosis had 9.88% less survival probability to having CVD problems after 20 years since the diagnosis than patients without any mental disorder. With a hazard ratio of 1.970 (95%CI 1.935-2.005), the risk of developing a CVD problem on the former (patients with BP diagnosis) was almost twice greater than for patients suffering without mental health disorders. Conclusion There is an increased risk of developing cardiovascular problems and stroke among patients with bipolar disorder compared to patients affected by such symptoms without mental disorders. The robust results were ensured by limiting the potential confounders with the propensity score matching procedure, such as demographics, comorbidity, and medication. The study implies that monitoring and prevention approaches for cardiovascular and cerebral vascular diseases must be tailored to symptoms of mental disorders.

Associations between mosaic loss of sex chromosomes and incident hospitalization for atrial fibrillation in the United Kingdom.

Mosaic loss of chromosome Y (mLOY) in leukocytes of men reflects genomic instability from aging, smoking, and environmental exposures. A similar mosaic loss of chromosome X (mLOX) occurs among women. However, the associations between mLOY, mLOX, and risk of incident heart diseases are unclear. We estimated associations between mLOY, mLOX, and risk of incident heart diseases requiring hospitalization, including atrial fibrillation, myocardial infarction, ischemic heart disease, cardiomyopathy, and heart failure. We analyzed 190,613 men and 224,853 women with genotyping data from the UK Biobank. Among these participants, we analyzed 37,037 men with mLOY and 13,978 women with mLOX detected using Mosaic Chromosomal Alterations caller. Multivariable Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of each incident heart disease in relation to mLOY in men and mLOX in women. Additionally, Mendelian randomization (MR) was conducted to estimate causal associations. Among men, detectable mLOY was associated with elevated risk of atrial fibrillation (HR=1.06, 95%CI:1.03-1.11). The associations were apparent in both never-smokers (HR=1.07, 95%:1.01-1.14) and ever-smokers (HR=1.05, 95%CI:1.01-1.11) as well as men > and ≤60 years of age. MR analyses supported causal associations between mLOY and atrial fibrillation (HRMR-PRESSO=1.15, 95%CI:1.13-1.18). Among post-menopausal women, we found a suggestive inverse association between detectable mLOX and atrial fibrillation risk (HR=0.90, 95%CI:0.83-0.98). However, associations with mLOY and mLOX were not found for other heart diseases. Our findings suggest that mLOY and mLOX reflect sex-specific biological processes or exposure profiles related to incident atrial fibrillation requiring hospitalization.

Ataxia Telangiectasia-Mutated Kinase Deficiency Induces Cardiac Dysfunction with Increased Myocyte Apoptosis and Hypertrophy with Age

Background: Heart failure is the leading cause of death globally. The risk for heart disease increases exponentially with age. The incidence of heart disease is approximately 40% in humans that are 40-59 years old. Ataxia telangiectasia-mutated kinase (ATM), a cell cycle protein, controls growth and repair in response to double-stranded DNA damage. Mutations in the ATM gene lead to a multisystemic disease known as Ataxia Telangiectasia (A-T). These individuals exhibit signs of premature aging. A-T heterozygotes make up about 2% of the population and are more susceptible to ischemic heart disease and die 11 years earlier compared to non-carriers. Previous work has shown that ATM deficiency increases myocyte hypertrophy in 4-month-old (young) ATM heterozygous knockout (hKO) mice vs. age-matched wild-type (WT) mice. However, there was no difference in myocyte apoptosis or heart function between the two groups. Hypothesis: It is hypothesized that with age, ATM deficiency induces myocytes apoptosis and hypertrophy, and cardiac dysfunction. Methods: Heart function was measured in young and 14-month-old WT and hKO mice using echocardiography. Cross sections (5 μm) of heart were used to measure myocyte apoptosis and hypertrophy using terminal deoxynucleotidyl transferase nick end labeling (TUNEL) and rhodamine wheat germ agglutinin (WGA) staining, respectively. Results: Heart function, measured by fractional shortening (%FS) and ejection fraction (%EF), remained unchanged in young and 14-month-old WT mice. However, %FS and %EF were significantly lower in 14-month-old hKO mice vs. young hKO and age-matched WT mice. Myocyte apoptosis and cross-sectional area (hypertrophy) were significantly higher in 14-month-old hKO vs. age-matched WT mice. Conclusion: The data indicates that ATM deficiency induces cardiac dysfunction with increased myocyte apoptosis and hypertrophy with age. This research was supported by Department of Biological Sciences, Undergraduate Research Honors Program, Offce of Research and Sponsored Programs, Department of Biomedical Sciences, and Department of Health Sciences. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Dose-response association between Chinese visceral adiposity index and cardiovascular disease: a national prospective cohort study.

Chinese visceral adiposity index (CVAI) is a reliable visceral obesity index, but the association between CVAI and risk of cardiovascular disease (CVD) remains unclear. We explored the associations of CVAI with incident CVD, heart disease, and stroke and compared the predictive power of CVAI with other obesity indices based on a national cohort study. The present study included 7,439 participants aged ≥45 years from China Health and Retirement Longitudinal Study (CHARLS). Cox regression models were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Restricted cubic splines analyses were adopted to model the dose-response associations. Receiver operator characteristic (ROC) analyses were used to compare the predictive ability of different obesity indices (CVAI, visceral adiposity index [VAI], a body shape index [ABSI], conicity index [CI], waist circumference [WC], and body mass index [BMI]). During 7 years' follow-up, 1,326 incident CVD, 1,032 incident heart disease, and 399 stroke cases were identified. The HRs (95% CI) of CVD, heart disease, and stroke were 1.50 (1.25-1.79), 1.29 (1.05-1.57), and 2.45 (1.74-3.45) for quartile 4 versus quartile 1 in CVAI. Linear associations of CVAI with CVD, heart disease, and stroke were observed (P nonlinear >0.05) and per-standard deviation (SD) increase was associated with 17% (HR 1.17, 1.10-1.24), 12% (1.12, 1.04-1.20), and 31% (1.31, 1.18-1.46) increased risk, respectively. Per-SD increase in CVAI conferred higher risk in participants aged<60 years than those aged ≥60 years (P interaction<0.05). ROC analyses showed that CVAI had higher predictive value than other obesity indices (P<0.05). CVAI was linearly associated with risk of CVD, heart disease, and stroke and had best performance for predicting incident CVD. Our findings indicate CVAI as a reliable and applicable obesity index to identify higher risk of CVD.

Modification of Life Style in Myocardial Infarction Clients in Selected Hospitals at Guntur District

Heart disease is responsible for more deaths and disability among both males and females than any other killer and it is quickly establishing itself as the leading cause of death and disability. Furthermore, the incidence of heart disease is spreading worldwide. Asian countries adopt a more sedentary Westernized lifestyle, together with a high fat, high salt diet and processed foods that have come to be associated with technological offence, researchers are noticing that Western diseases are becoming more prevalent causes of death in Asia. Objectives: To assess pretest knowledge regarding lifestyle modification for the prevention of myocardial infarction to evaluate cardiac patients' posttest knowledge of lifestyle modifications to prevent myocardial infarction by administering a structured teaching program to them. To assess the effectiveness of a structured teaching programme by comparing pre and post-test scores to see if there is a correlation between certain demographic characteristics of cardiac patients and knowledge. Results: Among 60 patients 47 (78.3%) had inadequate knowledge, 13 (21.7%) had moderately adequate knowledge and 0(0%) had adequate knowledge in the pre-test. Among 60 patients 0(0%) had inadequate knowledge, 7(11.7%) had moderate adequate knowledge and 53(88.3%) had adequate knowledge in the post-test. Among 60 patients 52 (86.7%) had poor practice,8 (13.3%) had average practice and 0(0%) had a good level of practice in the pre-test. Among 60 clients 0(0%) had poor practice, 2(3.3%) had average practice and 58 (96.7%) had good practice levels in the post-test. In the pre-test, the mean value is 10.28 with a standard deviation of 6.31 and the mean percentage is 34.6%. In the post-test, the mean value is 24.40 with a standard deviation of 4.02 and the mean percentage is 81.3%. The calculated value t=18.7241 is the tabulated value at the level of t59=2.000. The calculated value is more than the tabulated value. The post-test value is greater than the pre-test value hence there is a high significance of improvement of knowledge levels in the post-test. In the pre-test, the mean value is 3.77 with a standard deviation of 1.88 and the mean percentage is 37.7% in post-test the mean value is 8.13 with a standard deviation of 1.08 and the mean percentage is 81.3%. The calculated value t= 12.5887 at the level t59 the tabulated value is 2.000 hence, the calculated value is more than the tabulated value. The post-test mean score is higher than the pre-test value so there is a high significance in post-practice levels.

Data attribution and quantitative analysis for heart disease screening

Heart disease is a globally common fatal diseases, and its appearance has always been of great concern. The goal of this paper was to analyse factors of variation in the appearance of heart disease in Cleveland area with a view to provide a scientific basis for the prevention and comprehension of heart disease. This paper utilized data which includes the prevalence of heart disease in Cleveland region, which contains several characteristic variables such as age, gender, type of chest pain, etc., as well as the target variable, the prevalence of heart disease. First, the data were subjected to data pre-processing, including missing value treatment, outlier treatment, and feature engineering. Then, Granger causality test could be utilized to find out the correlation among features and target in order to distinguish the features that have a significant impact on the prevalence of heart disease. The outcome of the experiment showed that there was a major causal relationship between features such as ST depression led by oldpeak, slope of the highest exercise ST segment, a blood disorder called thalassemia (thal), and heart disease incidence. And different degrees of blood diseases may increase the risk of the disease. These results have significant implications for the progression of targeted heart disease prevention strategies and health management policies. Further studies can incorporate more features and data to enhance models precision and accuracy and interpretability, providing more valuable information for better understanding the pathogenesis of heart disease and predicting risk.

Association between number of children and incident heart disease and stroke in parents – results from the Survey of Health, Ageing and Retirement in Europe (SHARE)

BackgroundIn former studies, parity was associated with adverse cardiovascular outcomes in parents. This study aims to extend the limited existing data regarding the association between the number of children and heart disease and/or stroke in a large longitudinal study in different European countries in both men and women.MethodsFor 42 075 subjects (18 080 men, 23 995 women; median age 58 years (interquartile range: 53 to 65)) from 19 European countries and Israel in the Survey of Health, Ageing and Retirement in Europe (SHARE), odds ratios (OR) for the association between number of children and incident self-reported heart disease and/or stroke (HDS) were estimated using logistic regression analyses. Persons with one or two children were used as reference. The final model was adjusted for baseline age, sex, education, region, and marital status. All analyses were stratified by sex.ResultsWomen with seven or more children had the highest OR for the association between the number of children and incident HDS (OR = 2.12 [95% CI: 1.51 to 2.98]), while men with six children showed the highest OR (OR = 1.62 [1.13 to 2.33]). Stratified by education, across all education levels, men and women with five or more children had the highest ORs for this association. The highest OR was observed in both women and men in the group with primary education (OR = 1.66 [1.29 to 2.15] and OR = 1.60 [1.19 to 2.14], respectively). Stratified by region, both men and women with five or more children showed the highest ORs in Southern Europe (OR = 2.07 [1.52 to 2.82] and OR = 1.75 [1.25 to 2.44], respectively).ConclusionIn this long-term follow-up study in various countries in Europe and Israel we found a positive association between number of children and incident HDS. This association was more pronounced in lower educated subjects and showed regional variations.

Lower incidence of new-onset heart disease following covid-19 compared to viral pneumonia despite more echocardiography

Abstract Background Studies have shown an increased risk of cardiac disease and dysfunction following COVID-19. However, it remains unknown whether infection with COVID-19 differs from other viral pneumonias with respect to subsequent incident heart disease. Purpose To determine the incidence of heart disease and use of cardiac procedures in patients following a diagnosis of COVID-19 compared to other viral pneumonias. Methods In a retrospective, observational study, we compared incidence rates for cardiac disease diagnosed after hospitalization with COVID-19 February-November 2020 versus hospitalization with viral pneumonia as the main diagnosis in 2018-2019. Data was obtained from The Norwegian Patient Registry and the Norwegian Surveillance System for Communicable Diseases, and linked with a unique national person identification number. We defined heart disease using ICD-10 codes and used Cox regression models to compare the hazard of first episodes of myocarditis, acute myocardial infarction, atrial fibrillation/flutter, heart failure, ischemic disease, other cardiac disease, and total heart disease (any of these conditions). Patients were followed until 31 December 2020, with censoring on this date or a maximum of 274 days after hospital admission. Results Patients hospitalized with COVID-19 in 2020 (n = 2,359) were younger, mean 59 (SD 18) vs 69 (19) years, had fewer comorbidities, had fewer hospitalizations prior to the index hospitalization (0.5 (1.2) vs 0.9 (1.8)), were more frequently treated with respiratory support (14.2% vs 7.8%) and had higher in-hospital mortality (6.9% vs 2.3%) than patients hospitalized with viral pneumonia in 2018-2019 (n = 9,018). Patients hospitalized with COVID-19 had a lower crude incidence of new total heart disease than those with viral pneumonia (56 [95%CI 48-65] vs 75 [95%CI 71-79] per 100,000 person-years). This difference persisted after adjusting for age, sex, Charlson comorbidity score (comprising age, sex, and 17 dichotomized comorbidities), hospital admission during the previous year, respiratory support, and a propensity score for being hospitalized for COVID-19 vs. other pneumonia: Hazard ratio (HR) 0.79 [95%CI 0.67-0.94], p = 0.006. Patients with COVID-19 more frequently underwent echocardiography: HR 1.41 [1.23-1.63], p = &amp;lt;0.001 (Fig. 1). Conclusion Following hospitalization for COVID-19, the incidence of total heart disease and heart failure was lower than for patients hospitalized with viral pneumonia, despite more frequent examinations with echocardiography.Figure 1

The ability of the geriatric nutritional risk index to predict the risk of heart diseases in Korean adults: a Korean Genome and Epidemiology Study cohort

IntroductionThe predictive ability of nutritional risk index on cardiovascular outcomes in middle-aged and non-hospitalized adults has not yet been reported. This study investigated whether the Geriatric Nutritional Risk Index (GNRI), an index for assessing the risk of developing malnutrition, could predict heart disease in middle-aged Korean adults.MethodsThe cohort used in this study consisted of 3,783 participants selected from 10,030 Korean adults who participated in the Ansan-Ansung cohort study as part of the Korean Genome and Epidemiology Study. The GNRI was determined based on serum albumin level, proportion of current weight, and ideal body weight. Participants were then divided into two groups: GNRI ≤98 and &amp;gt; 98, which corresponded to the risk of malnutrition and normal, respectively. The major outcome of this study was coronary artery disease (CAD) or congestive heart failure (CHF) during a 15-year-follow period.ResultsDuring the follow-up period spanning 2004–2018, 136 events of heart disease occurred. Using a Kaplan–Meier analysis, event-free rates were found to be associated with 90.5% on a GNRI ≤98 and 96.6% on a GNRI &amp;gt;98 (p &amp;lt; 0.0009). GNRI ≤98 showed a 3.2-fold (hazard ratio, 3.22; 95% credit interval, 1.49–6.96; p = 0.0029) increase in the incidence of heart disease, including CAD or CHF, compared with GNRI &amp;gt;98, after controlling for potential confounders.ConclusionMalnutrition risk confers a significantly increased risk for heart disease in middle-aged Koreans. Further studies with larger cohorts are needed to verify the efficacy of the GNRI in predicting disease risk in adults with pre-disease.

Improved stacked ensemble with genetic algorithm for automatic ECG diagnosis of children living in high-altitude areas

Electrocardiogram (ECG) is a commonly used diagnostic tool in clinical practice that plays a vital role in the diagnosis and treatment of various heart diseases. Previous studies have indicated that the incidence of heart disease in children living in high-altitude areas is significantly higher than those in low-altitude areas, which increases the demand for ECG examinations in these regions. However, there is a lack of research and technology that focus on automatic ECG diagnosis for children in high-altitude areas. This study utilized electronic medical records of pediatric electrocardiograms (ECGs) from high-altitude areas in Yunnan Province, China as research data. An improved genetic algorithm (GA) was employed to find the best combination of base classifiers, and a stacked ensemble approach was utilized to develop a reliable model for automatic diagnosis of pediatric ECGs. The developed model is capable of identifying abnormal ECGs and classifying heart rhythm types into four categories: normal sinus rhythm, sinus tachycardia, sinus bradycardia, and other arrhythmias. The model was tested and compared with commonly used classification methods. The results show that the model developed in this paper exhibits better performance in terms of accuracy, recall, and F1 score. The model’s classification effectiveness was further demonstrated by creating a receiver operating characteristic (ROC) curve. Finally, feature importance analysis highlighted the significance heart rate, developmental stage, and QRS complex axis deviation angle in the model.

A-046 Investigating the Role of RNase L in Metabolic Syndrome

Abstract Background Metabolic syndrome is closely associated with the incidence of heart disease, type 2 diabetes, and stroke. Though the exact cause of metabolic syndrome is not known, many features of the metabolic syndrome are caused by insulin resistance. Recent years, accumulating evidence has shown that dysregulation of insulin signaling leads to insulin resistance. Interestingly, we have observed that RNase L affects the insulin signaling pathway by regulating the activation of insulin receptor subtrate-1 (IRS-1) in primary mouse embryonic fibroblasts (MEFs) and primary mouse hepatocyte. RNase L is an enzyme that plays a critical role in interferon function against viral infection and cellular proliferation. How RNase L affects the insulin signaling pathway is still unknown. Methods Age-matched C57BL/6 background RNase L wild type (WT) and knockout (KO) mice (n = 6–8) were fed on a chow diet. Metabolic tolerance tests including glucose tolerance test (GTT) and insulin tolerance test (ITT) were conducted on mice between 12 and 16 weeks old. Mice were subjected to either a morning (4 h) or an overnight (12 h) fast, then intraperitoneally injected with glucose (1.5 g/kg body weight) in PBS, pH 7.4, for GTT and insulin (1.0I U/kg body weight) for ITT. Blood was collected via tail vein at different time intervals over a span of 2 h and blood glucose was measured using a glucometer. Results We found that RNase L KO mice displayed significantly increased glucose tolerance in compared to RNase L WT mice as measured in the intraperitoneal glucose tolerance test. The glucose level in RNase L KO mice was 150% higher than that in RNase L WT mice after IP injection of glucose in 60 min. In the ITT experiment, the glucose level in RNase L KO mice was 130% higher than that in WT mice in 60 min post injection. Taken together, the results in GTT and ITT indicated that RNase L mediates the metabolism of glucose in vivo. Further investigation of molecular mechanisms is currently being conducted. Conclusion Our results suggests that RNase L plays a role in insulin sensitivity, which affects glucose metabolism.