Recommendations for Cardiovascular Health and Disease Surveillance for 2030 and Beyond: A Policy Statement From the American Heart Association

Cardiovascular predicted risk: A population-based comparison of the pooled cohorts equation and PREVENT

BACKGROUND

While the new cardiovascular risk score (PREVENT) has improvements, its implementation may lead to significant changes in the distribution of atherosclerotic cardiovascular diseases (ASCVD) in the United States. We aimed to quantify and characterize the distribution of the 10-year predicted absolute ASCVD risk using the Pooled Cohorts Equation (PCE) and PREVENT.

METHODS

We utilized the latest (2017-March 2020) round of the National Health and Nutrition Examination Survey (NHANES). Accounting for the complex survey design of the NHANES, we computed the mean predicted ASCVD risk overall and by sex, race, and education; similarly, we computed the prevalence of cardiovascular risk groups (<5%, 5%-7.4%, 7.5%-19.9%, and ≥ 20%).

RESULTS

The study included 3845 observations, representing 109,692,509 people. Using the PREVENT calculator resulted in a reduction of the mean 10-year ASCVD absolute risk by half compared to the PCE: 9.1% vs 4.7%. Under the PCE, the high-risk category accounted for 12.5% of the population, whereas under PREVENT it fell to 0.4%. Among those previously classified as high-risk under the PCE, 3.5% would remain in this category with PREVENT, while 93% would be reclassified as intermediate risk.

CONCLUSIONS

The adoption of the novel cardiovascular risk score, PREVENT, could lower the average predicted ASCVD risk and reduce the prevalence of high-risk individuals. While this shift might suggest improved cardiovascular health, it could also lead to complacency, potentially undermining ongoing public health efforts aimed at preventing cardiovascular disease.

Derivation and Validation of ICD-10 Codes for Identifying Incident Stroke

Importance

Claims data with International Statistical Classification of Diseases, Tenth Revision (ICD-10) codes are routinely used in clinical research. However, the use of ICD-10 codes to define incident stroke has not been validated against expert-adjudicated outcomes in the US population.

Objective

To develop and validate the accuracy of an ICD-10 code list to detect incident stroke events using Medicare inpatient fee-for-service claims data.

Design, Setting, and Participants

This cohort study used data from 2 prospective population-based cohort studies, the Atherosclerosis Risk in Communities (ARIC) study and the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, and included participants aged 65 years or older without prior stroke who had linked Medicare claims data. Stroke events in the ARIC and REGARDS studies were identified via active surveillance and adjudicated by expert review. Medicare-linked ARIC data (2016-2018) were used to develop a list of ICD-10 codes for incident stroke detection. The list was validated using Medicare-linked REGARDS data (2016-2019). Data were analyzed from September 1, 2022, through September 30, 2023.

Exposures

Stroke events detected in Medicare claims vs expert-adjudicated stroke events in the ARIC and REGARDS studies.

Main Outcomes and Measures

The main outcomes were sensitivity and specificity of incident stroke detection using ICD-10 codes.

Results

In the ARIC study, there were 110 adjudicated incident stroke events among 5194 participants (mean [SD] age, 80.1 [5.3] years) over a median follow-up of 3.0 (range, 0.003-3.0) years. Most ARIC participants were women (3160 [60.8%]); 993 (19.1%) were Black and 4180 (80.5%) were White. Using the primary diagnosis code on a Medicare billing claim, the ICD-10 code list had a sensitivity of 81.8% (95% CI, 73.3%-88.5%) and a specificity of 99.1% (95% CI, 98.8%-99.3%) to detect incident stroke. Using any diagnosis code on a Medicare billing claim, the sensitivity was 94.5% (95% CI, 88.5%-98.0%) and the specificity was 98.4% (95% CI, 98.0%-98.8%). In the REGARDS study, there were 140 adjudicated incident strokes among 6359 participants (mean [SD] age, 75.8 [7.0] years) over a median follow-up of 4.0 (range, 0-4.0) years. More than half of the REGARDS participants were women (3351 [52.7%]); 1774 (27.9%) were Black and 4585 (72.1%) were White. For the primary diagnosis code, the ICD-10 code list had a sensitivity of 70.7% (95% CI, 63.2%-78.3%) and a specificity of 99.1% (95% CI, 98.9%-99.4%). For any diagnosis code, the ICD-10 code list had a sensitivity of 77.9% (95% CI, 71.0%-84.7%) and a specificity of 98.9% (95% CI, 98.6%-99.2%).

Conclusions and Relevance

These findings suggest that ICD-10 codes could be used to identify incident stroke events in Medicare claims with moderate sensitivity and high specificity.

Cardiovascular Risk Profile Among Reproductive-Aged Women in the U.S.: The Behavioral Risk Factor Surveillance System, 2015-2020

Introduction

Suboptimal cardiovascular health is associated with adverse pregnancy outcomes and long-term cardiovascular risk. The authors examined trends in cardiovascular risk factors and correlates of suboptimal cardiovascular risk profiles among reproductive-aged U.S. women.

Methods

With data from 335,959 women in the Behavioral Risk Factor Surveillance System (2015-2020), the authors conducted serial cross-sectional analysis among nonpregnant reproductive-aged women (18-44 years) without cardiovascular disease who self-reported information on 8 cardiovascular risk factors selected on the basis of Life's Essential 8 metrics. The authors estimated the prevalence of each risk factor and suboptimal cardiovascular risk profile (≥2 risk factors) and examined trends overall and by age and race/ethnicity. Using multivariable Poisson regression, the authors assessed the sociodemographic correlates of suboptimal cardiovascular risk profile.

Results

The weighted prevalence of women aged <35 years was approximately 64% in each survey year. The prevalence of suboptimal cardiovascular risk profile increased modestly from 72.4% (71.6%-73.3%) in 2015 to 75.9% (75.0%-76.7%) in 2019 (p<0.001). This increase was mainly driven by increases in overweight/obesity (53.1%-58.4%; p<0.001). Between 2015 and 2019, significant increases in suboptimal cardiovascular risk profile were observed among non-Hispanic White (69.8%-72.6%; p<0.001) and Hispanic (75.1%-80.3%; p<0.001) women but not among non-Hispanic Black (82.7%-83.7%; p=0.48) or Asian (68.1%-73.2%; p=0.09) women. Older age, rural residence, and non-Hispanic Black and Hispanic race and ethnicity were associated with a higher prevalence of suboptimal cardiovascular risk profile.

Conclusions

There has been a modest but significant increase in suboptimal cardiovascular risk profile among U.S. women of reproductive age. Urgent preventive efforts are needed to reverse this trend and improve cardiovascular health, particularly among subgroups at increased risk, to mitigate its implications.

Forecasting the Burden of Cardiovascular Disease and Stroke in the United States Through 2050-Prevalence of Risk Factors and Disease: A Presidential Advisory From the American Heart Association

BACKGROUND

Cardiovascular disease and stroke are common and costly, and their prevalence is rising. Forecasts on the prevalence of risk factors and clinical events are crucial.

METHODS

Using the 2015 to March 2020 National Health and Nutrition Examination Survey and 2015 to 2019 Medical Expenditure Panel Survey, we estimated trends in prevalence for cardiovascular risk factors based on adverse levels of Life's Essential 8 and clinical cardiovascular disease and stroke. We projected through 2050, overall and by age and race and ethnicity, accounting for changes in disease prevalence and demographics.

RESULTS

We estimate that among adults, prevalence of hypertension will increase from 51.2% in 2020 to 61.0% in 2050. Diabetes (16.3% to 26.8%) and obesity (43.1% to 60.6%) will increase, whereas hypercholesterolemia will decline (45.8% to 24.0%). The prevalences of poor diet, inadequate physical activity, and smoking are estimated to improve over time, whereas inadequate sleep will worsen. Prevalences of coronary disease (7.8% to 9.2%), heart failure (2.7% to 3.8%), stroke (3.9% to 6.4%), atrial fibrillation (1.7% to 2.4%), and total cardiovascular disease (11.3% to 15.0%) will rise. Clinical CVD will affect 45 million adults, and CVD including hypertension will affect more than 184 million adults by 2050 (>61%). Similar trends are projected in children. Most adverse trends are projected to be worse among people identifying as American Indian/Alaska Native or multiracial, Black, or Hispanic.

CONCLUSIONS

The prevalence of many cardiovascular risk factors and most established diseases will increase over the next 30 years. Clinical and public health interventions are needed to effectively manage, stem, and even reverse these adverse trends.

Association of ankylosing spondylitis with cardiovascular disease: a bidirectional two-sample mendelian randomization study

Backgrounds

Current observational investigations hint at a potential linkage between ankylosing spondylitis and cardiovascular wellness. However, the nature of this causality remains to be elucidated. Consequently, this study is designed to evaluate the causal interconnection between ankylosing spondylitis and cardiovascular-related conditions utilizing a bidirectional two-sample Mendelian Randomization (MR) methodology.

Methods

In this study, we conducted Mendelian randomization (MR) analyses using genome-wide association study (GWAS) data. The fixed-effects inverse variance weighted (IVW) model was used as the primary analysis method, and MR-Egger regression and the weighted median method were employed as supplementary approaches. Horizontal pleiotropy and heterogeneity were evaluated using various statistical tests, including MR-PRESSO global test, MR-Egger intercept, and Cochran's Q test.

Results

The MR result demonstrated an increased risk of heart failure in individuals with ankylosing spondylitis (OR: 1.0132, 95% CI = 1.0043-1.0221, p = 0.003). The MR analysis results did not demonstrate a causal relationship between ankylosing spondylitis and other cardiovascular diseases, such as atrial fibrillation, coronary artery disease, ischemic stroke, myocardial infarction, and valvular heart disease (all p > 0.05). No evidence of reverse causality was found between ankylosing spondylitis and mentioned cardiovascular diseases in reverse MR analyses. Sensitivity analysis verified the reliability of the results.

Conclusion

Our MR study indicates a relationship between ankylosing spondylitis and an increased risk of heart failure. Further research is needed to confirm these findings and elucidate the underlying mechanisms involved.

Establishment and evaluation of a nomogram for in-hospital new-onset atrial fibrillation after percutaneous coronary intervention for acute myocardial infarction

Background

New-onset atrial fibrillation (NOAF) is prognostic in acute myocardial infarction (AMI). The timely identification of high-risk patients is essential for clinicians to improve patient prognosis.

Methods

A total of 333 AMI patients were collected who underwent percutaneous coronary intervention (PCI) at Zhejiang Provincial People's Hospital between October 2019 and October 2020. Least absolute shrinkage and selection operator regression (Lasso) and multivariate logistic regression analysis were applied to pick out independent risk factors. Secondly, the variables identified were utilized to establish a predicted model and then internally validated by 10-fold cross-validation. The discrimination, calibration, and clinical usefulness of the prediction model were evaluated using the receiver operating characteristic (ROC) curve, calibration curve, Hosmer-Lemeshow test decision curve analyses, and clinical impact curve.

Result

Overall, 47 patients (14.1%) developed NOAF. Four variables, including left atrial dimension, body mass index (BMI), CHA2DS2-VASc score, and prognostic nutritional index, were selected to construct a nomogram. Its area under the curve is 0.829, and internal validation by 10-fold cross-folding indicated a mean area under the curve is 0.818. The model demonstrated good calibration according to the Hosmer-Lemeshow test (P = 0.199) and the calibration curve. It showed satisfactory clinical practicability in the decision curve analyses and clinical impact curve.

Conclusion

This study established a simple and efficient nomogram prediction model to assess the risk of NOAF in patients with AMI who underwent PCI. This model could assist clinicians in promptly identifying high-risk patients and making better clinical decisions based on risk stratification.

Early Diagnosis of Cardiovascular Diseases in the Era of Artificial Intelligence: An In-Depth Review

Cardiovascular diseases (CVDs) are significant health issues that result in high death rates globally. Early detection of cardiovascular events may lower the occurrence of acute myocardial infarction and reduce death rates in people with CVDs. Traditional data analysis is inadequate for managing multidimensional data related to the risk prediction of CVDs, heart attacks, medical image interpretations, therapeutic decision-making, and disease prognosis due to the complex pathological mechanisms and multiple factors involved. Artificial intelligence (AI) is a technology that utilizes advanced computer algorithms to extract information from large databases, and it has been integrated into the medical industry. AI methods have shown the ability to speed up the advancement of diagnosing and treating CVDs such as heart failure, atrial fibrillation, valvular heart disease, hypertrophic cardiomyopathy, congenital heart disease, and more. In clinical settings, AI has shown usefulness in diagnosing cardiovascular illness, improving the efficiency of supporting tools, stratifying and categorizing diseases, and predicting outcomes. Advanced AI algorithms have been intricately designed to analyze intricate relationships within extensive healthcare data, enabling them to tackle more intricate jobs compared to conventional approaches.

Lifestyle behaviors, social and economic disadvantages, and all-cause and cardiovascular mortality: results from the US National Health Interview Survey

Aim

To examine the independent relationships of lifestyle and social and economic factors with all-cause and cardiovascular disease (CVD) mortality in a large representative sample of the US adult population. Furthermore, the association between the combination of lifestyle and social and economic factors with mortality was analyzed in detail.

Methods

The sample included 103,314 participants with valid records and eligible for mortality follow-up, and information on lifestyle factors and social and economic disadvantages (NHIS waves 2000, 2005, 2010, and 2015). An unhealthy lifestyle score was constructed using information on physical activity, alcohol consumption, diet, and smoking status. Social and economic disadvantages were assessed using information on education, receipt of dividends, employment, family's home, and access to private health. Information on mortality data was determined by the National Death Index records.

Results

Compared with favorable lifestyle, unfavorable lifestyle was associated with higher all-cause (HR 2.07; 95% CI 1.97-2.19) and CVD (HR 1.84; 95% CI 1.68-2.02) mortality. Higher social and economic disadvantages were also associated with higher all-cause (HR 2.44; 95% CI 2.30-2.59) and CVD mortality (HR 2.44; 95% CI 2.16-2.77), compared to low social and economic disadvantages. In joint associations, participants in the high social and economic disadvantage and unfavorable lifestyle showed a greater risk of all-cause (HR 4.06; 95% CI 3.69-4.47) and CVD mortality (HR 3.98; 95% CI 3.31-4.79).

Conclusion

Lifestyle and social and economic disadvantages are associated with all-cause and CVD mortality. The risk of mortality increases as the number of social and economic disadvantages and unhealthy lifestyles increases.

Trajectory of Cognitive Function After Incident Heart Failure

Background

The size/magnitude of cognitive changes after incident heart failure (HF) are unclear. We assessed whether incident HF is associated with changes in cognitive function after accounting for pre-HF cognitive trajectories and known determinants of cognition.

Methods

This pooled cohort study included adults without HF, stroke, or dementia from six US population-based cohort studies from 1971-2019: Atherosclerosis Risk in Communities Study, Coronary Artery Risk Development in Young Adults Study, Cardiovascular Health Study, Framingham Offspring Study, Multi-Ethnic Study of Atherosclerosis, and Northern Manhattan Study. Linear mixed-effects models estimated changes in cognition at the time of HF (change in the intercept) and the rate of cognitive change over the years after HF (change in the slope), controlling for pre-HF cognitive trajectories and participant factors. Change in global cognition was the primary outcome. Change in executive function and memory were secondary outcomes. Cognitive outcomes were standardized to a t-score metric (mean [SD], 50 [10]); a 1-point difference represented a 0.1-SD difference in cognition.

Results

The study included 29,614 adults (mean [SD] age was 61.1 [10.5] years, 55% female, 70.3% White, 22.2% Black 7.5% Hispanic). During a median follow-up of 6.6 (Q1-Q3: 5-19.8) years, 1,407 (4.7%) adults developed incident HF. Incident HF was associated with an acute decrease in global cognition (-1.08 points; 95% CI -1.36, -0.80) and executive function (-0.65 points; 95% CI -0.96, -0.34) but not memory (-0.51 points; 95% CI -1.37, 0.35) at the time of the event. Greater acute decreases in global cognition after HF were seen in those with older age, female sex and White race. Individuals with incident HF, compared to HF-free individuals, demonstrated faster declines in global cognition (-0.15 points per year; 95% CI, -0.21, -0.09) and executive function (-0.16 points per year; 95% CI -0.23, -0.09) but not memory ( -0.11 points per year; 95% CI -0.26, 0.04) compared with pre-HF slopes.

Conclusions

In this pooled cohort study, incident HF was associated with an acute decrease in global cognition and executive function at the time of the event and faster declines in global cognition and executive function over the following years.

Causal relationship of cereal intake and type with cardiovascular disease: a Mendelian randomization study

Background

Observational studies have suggested that cereal consumption is associated with a reduced risk of cardiovascular disease (CVD). However, the potential causal relationship is not clear. We aimed to investigate the association of cereal intake and cereal type with CVD risk.

Methods

Two-step Mendelian randomization (MR) analysis was performed to confirm the causal association of cereal intake and cereal type with the risk of several common CVDs. Furthermore, two-step MR analysis was used to explore the mediating effect of cardiovascular metabolic factors, and multivariable MR analysis was used to assess the impact of socioeconomic status, such as education and income, on the causal association.

Results

The MR analysis indicated that genetically predicted cereal intake is associated with reduced risk of large artery stroke (LAS) (odd ratio (OR): 0.421; 95% confidence interval (CI) [0.193, 0.918]; p = 0.030), and muesli as the primary cereal intake is associated with reduced risk of coronary heart disease (CHD) (OR: 0.100; 95% CI [0.023, 0.437]; p = 0.002), myocardial infarction (MI) (OR: 0.101; 95% CI [0.020, 0.509]; p = 0.005), heart failure (OR: 0.210; 95% CI [0.064, 0.684]; p = 0.010), ischemic stroke (IS) (OR: 0.130; 95% CI [0.029, 0.591]; p = 0.008), LAS (OR: 0.017; 95% CI [0.0004, 0.737]; p = 0.034), and small-vessel stroke (OR: 0.021; 95% CI [0.001, 0.708]; p = 0.005). In contrast, genetically predicted biscuits as the primary cereal intake increased the risk of CHD (OR: 6.557; 95% CI [1.197, 36.031]; p = 0.031), and other cereals, such as cornflakes, as the primary cereal intake increased the risk of CHD (OR: 3.803; 95% CI [1.194, 12.111]; p = 0.024), MI (OR: 4.240; 95% CI [1.185, 15.174]; p = 0.026), stroke (OR: 3.154; 95% CI [1.070, 9.298]; p = 0.037), and IS (OR: 3.736; 95% CI [1.185, 11.782]; p = 0.024). Multivariable MR analysis underscored the significant role of education and income in the causal association, and two-step MR analysis indicated that body mass index, lipids, and blood glucose exerted important mediating effects in the causal association.

Conclusion

The findings of our study underscore the causal beneficial influence of muesli as the primary cereal intake on CVDs. A reasonable consumption of muesli may provide primary prevention of CVDs.

Acute high-dose MitoQ does not increase urinary kidney injury markers in healthy adults: a randomized crossover trial

Several human studies have used the mitochondrial antioxidant MitoQ. Recent in vitro data indicating that MitoQ may induce nephrotoxicity caused concern regarding the safety of MitoQ on the kidneys, but the doses were supraphysiological. Therefore, we sought to determine whether acute MitoQ elicits changes in urinary biomarkers associated with tubular injury in healthy adults with our hypothesis being there would be no changes. Using a randomized crossover design, 32 healthy adults (16 females and 16 males, 29 ± 11 yr old) consumed MitoQ (100-160 mg based on body mass) or placebo capsules. We obtained serum samples and a 4- to 6-h postcapsule consumption urine sample. We assessed creatinine clearance and urine kidney injury biomarkers including the chitinase 3-like-1 gene product YKL-40, kidney-injury marker-1, monocyte chemoattractant protein-1, epidermal growth factor, neutrophil gelatinase-associated lipocalin, interleukin-18, and uromodulin using multiplex assays. We used t tests, Wilcoxon tests, and Hotelling's T2 to assess global differences in urinary kidney injury markers between conditions. Acute MitoQ supplementation did not influence urine flow rate (P = 0.086, rrb = 0.39), creatinine clearance (P = 0.085, rrb = 0.42), or urinary kidney injury markers (T22,8 = 30.6, P = 0.121, univariate ps > 0.064). Using exploratory univariate analysis, MitoQ did not alter individual injury markers compared with placebo (e.g., placebo vs. MitoQ: YKL-40, 507 ± 241 vs. 442 ± 236 pg/min, P = 0.241; kidney injury molecule-1, 84.1 ± 43.2 vs. 76.2 ± 51.2 pg/min, P = 0.890; and neutrophil gelatinase-associated lipocalin, 10.8 ± 10.1 vs. 9.83 ± 8.06 ng/min, P = 0.609). In conclusion, although longer-term surveillance and data are needed in clinical populations, our findings suggest that acute high-dose MitoQ had no effect on urinary kidney injury markers in healthy adults.NEW & NOTEWORTHY We found acute high-dose mitochondria-targeted antioxidant (MitoQ) supplementation was not nephrotoxic and had no effect on markers of acute kidney injury in healthy adults. These findings can help bolster further confidence in the safety of MitoQ, particularly for future investigations seeking to examine the role of mitochondrial oxidative stress, via acute MitoQ supplementation, on various physiological outcomes.

Next Generation, Modifiable Cardiometabolic Biomarkers: Mitochondrial Adaptation and Metabolic Resilience: A Scientific Statement From the American Heart Association

Cardiometabolic risk is increasing in prevalence across the life span with disproportionate ramifications for youth at socioeconomic disadvantage. Established risk factors and associated disease progression are harder to reverse as they become entrenched over time; if current trends are unchecked, the consequences for individual and societal wellness will become untenable. Interrelated root causes of ectopic adiposity and insulin resistance are understood but identified late in the trajectory of systemic metabolic dysregulation when traditional cardiometabolic risk factors cross current diagnostic thresholds of disease. Thus, children at cardiometabolic risk are often exposed to suboptimal metabolism over years before they present with clinical symptoms, at which point life-long reliance on pharmacotherapy may only mitigate but not reverse the risk. Leading-edge indicators are needed to detect the earliest departure from healthy metabolism, so that targeted, primordial, and primary prevention of cardiometabolic risk is possible. Better understanding of biomarkers that reflect the earliest transitions to dysmetabolism, beginning in utero, ideally biomarkers that are also mechanistic/causal and modifiable, is critically needed. This scientific statement explores emerging biomarkers of cardiometabolic risk across rapidly evolving and interrelated "omic" fields of research (the epigenome, microbiome, metabolome, lipidome, and inflammasome). Connections in each domain to mitochondrial function are identified that may mediate the favorable responses of each of the omic biomarkers featured to a heart-healthy lifestyle, notably to nutritional interventions. Fuller implementation of evidence-based nutrition must address environmental and socioeconomic disparities that can either facilitate or impede response to therapy.

Leveraging Digital Health to Improve the Cardiovascular Health of Women

Purpose of Review

In this review, we present a comprehensive discussion on the population-level implications of digital health interventions (DHIs) to improve cardiovascular health (CVH) through sex- and gender-specific prevention strategies among women.

Recent Findings

Over the past 30 years, there have been significant advancements in the diagnosis and treatment of cardiovascular diseases, a leading cause of morbidity and mortality among men and women worldwide. However, women are often underdiagnosed, undertreated, and underrepresented in cardiovascular clinical trials, which all contribute to disparities within this population. One approach to address this is through DHIs, particularly among racial and ethnic minoritized groups. Implementation of telemedicine has shown promise in increasing adherence to healthcare visits, improving BP monitoring, weight control, physical activity, and the adoption of healthy behaviors. Furthermore, the use of mobile health applications facilitated by smart devices, wearables, and other eHealth (defined as electronically delivered health services) modalities has also promoted CVH among women in general, as well as during pregnancy and the postpartum period. Overall, utilizing a digital health approach for healthcare delivery, decentralized clinical trials, and incorporation into daily lifestyle activities has the potential to improve CVH among women by mitigating geographical, structural, and financial barriers to care.

Summary

Leveraging digital technologies and strategies introduces novel methods to address sex- and gender-specific health and healthcare disparities and improve the quality of care provided to women. However, it is imperative to be mindful of the digital divide in specific populations, which may hinder accessibility to these novel technologies and inadvertently widen preexisting inequities.

Psychological couple-oriented interventions for patients with heart disease and their partners: a scoping review and guidelines for future interventions

Objective

This scoping review aims to provide an accessible summary of available evidence on the efficacy of psychological couple-based interventions among patients with heart disease and their partners focusing on specific aspects and strategies by assessing different emotional and physical cardiac-related outcome measures.

Methods

A literature search was performed in PubMed, Scopus, Medline, PsycINFO, and Web of Science databases using the keywords "heart diseases" and "couple-based intervention." A literature search using systematic methods was applied. Data were extracted to address the review aims and were presented as a narrative synthesis.

Results

The database search produced 11 studies. Psychological couple-based interventions varied in terms of the type of intervention, personnel, format (group or individual, phone or in person), number of sessions, and duration. Most of the contributions also lacked adequate details on the training of professionals, the contents of the interventions, and the theoretical models on which they were based. Finally, although partners were involved in all the treatment, in most studies, the psychological strategies and outcomes were focused on the patient.

Conclusion

The variability of the psychological couple-based interventions of included studies represents a challenge in summarizing the existing literature. Regarding their impact, psychological interventions for patients with cardiovascular disease and their partners were found to moderately improve patients' and partners' outcomes.

Educational inequalities in mortality and their mediators among generations across four decades: nationwide, population based, prospective cohort study based on the ChinaHEART project

OBJECTIVES

To assess the different educational inequalities in mortality among generations born between 1940 and 1979 in China, and to investigate the role of socioeconomic, behavioural, and metabolic factors as potential contributors to the reduction of educational inequalities.

DESIGN

Nationwide, population based, prospective cohort study.

SETTING

The ChinaHEART (China Health Evaluation And risk Reduction through nationwide Teamwork) project in all 31 provinces in the mainland of China.

PARTICIPANTS

1 283 774 residents aged 35-75 years, divided into four separate cohorts born in 1940s, 1950s, 1960s, and 1970s.

MAIN OUTCOME MEASURES

Relative index of inequality and all cause mortality.

RESULTS

During a median follow-up of 3.5 years (interquartile range 2.1-4.7), 22 552 deaths were recorded. Among the four generations, lower education levels were found to be associated with a higher risk of all cause death: Compared with participants with college level education or above, the hazard ratio for people with primary school education and below was 1.4 (95% confidence interval 1.2 to 1.7) in the 1940s cohort, 1.8 (1.5 to 2.1) in the 1950s cohort, 2.0 (1.7 to 2.4) in the 1960s cohort, and 1.8 (1.4 to 2.4) in the 1970s cohort. Educational relative index of inequality in mortality increased from 2.1 (95% confidence interval 1.9 to 2.3) in the 1940s cohort to 2.6 (2.1 to 3.3) in the 1970s cohort. Overall, the mediation proportions were 37.5% (95% confidence interval 32.6% to 42.8%) for socioeconomic factors, 13.9% (12.0% to 16.0%) for behavioural factors, and 4.7% (3.7% to 5.8%) for metabolic factors. Except for socioeconomic measurements, the mediating effects by behavioural and metabolic factors decreased in younger generations.

CONCLUSION

Educational inequalities in mortality increased over generations in China. Improving healthy lifestyles and metabolic risk control for less educated people, especially for younger generations, is essential to reduce health inequalities.

Three-Dimensional Cardiomyocyte-Nanobiosensing System for Specific Recognition of Drug Subgroups

Abnormal cardiac electrophysiological activities significantly contribute to the incidence of cardiovascular diseases. Therefore, it is crucial to recognize effective drugs, which require an accurate, stable, and sensitive platform. Although conventional extracellular recordings offer a non-invasive and label-free manner to monitor the electrophysiological state of cardiomyocytes, the misrepresented and low-quality extracellular action potentials are difficult to provide accurate and high-content information for drug screening. This study presents the development of a three-dimensional cardiomyocyte-nanobiosensing system that can specifically recognize drug subgroups. The nanopillar-based electrode is manufactured by template synthesis and standard microfabrication technology on a porous polyethylene terephthalate membrane. Based on the cardiomyocyte-nanopillar interface, high-quality intracellular action potentials can be recorded by the minimally invasive electroporation. We validate the performance of a cardiomyocyte-nanopillar-based intracellular electrophysiological biosensing platform by two subclasses of sodium channel blockers, quinidine and lidocaine. The recorded intracellular action potentials accurately reveal the subtle differences between these drugs. Our study indicates that high-content intracellular recordings utilizing nanopillar-based biosensing can provide a promising platform for the electrophysiological and pharmacological investigation of cardiovascular diseases.

A causal relationship between irritability and cardiovascular diseases: a Mendelian randomization study

Background

Observational studies have suggested that irritability is associated with a higher risk of cardiovascular disease (CVD). However, the potential causal association is not clear. Therefore, we used Mendelian randomization (MR) analysis to assess the causal association of irritability with CVD risk.

Methods

A two-sample MR analysis was performed to confirm the causal association of irritability with the risk of several common CVDs. The exposure data were derived from the UK biobank involving 90,282 cases and 232,386 controls, and outcome data were collected from the published genome-wide association studies (GWAS) and FinnGen database. Inverse-variance weighted (IVW), MR-Egger, and weighted median methods were performed to assess the causal association. Furthermore, the mediating effect of smoking, insomnia, and depressed affect was explored by using a two-step MR.

Results

The MR analysis indicated that genetically predicted irritability increased the risk of CVD, including coronary artery disease (CAD) (Odds ratio, OR: 2.989; 95% confidence interval, CI: 1.521-5.874, p = 0.001), myocardial infarction (MI) (OR: 2.329, 95% CI: 1.145-4.737, p = 0.020), coronary angioplasty (OR: 5.989, 95% CI: 1.696-21.153, p = 0.005), atrial fibrillation (AF) (OR: 4.646, 95% CI: 1.268-17.026, p = 0.02), hypertensive heart disease (HHD) (OR: 8.203; 95% CI: 1.614-41.698, p = 0.011), non-ischemic cardiomyopathy (NIC) (OR: 5.186; 95% CI: 1.994-13.487, p = 0.001), heart failure (HF) (OR: 2.253; 95% CI: 1.327-3.828, p = 0.003), stroke (OR: 2.334; 95% CI: 1.270-4.292, p = 0.006), ischemic stroke (IS) (OR: 2.249; 95% CI: 1.156-4.374, p = 0.017), and ischemic stroke of large-artery atherosclerosis ISla (OR: 14.326; 95% CI: 2.750-74.540, p = 0.002). The analysis also indicated that smoking, insomnia, and depressed affect play an important role in the process of irritability leading to cardiovascular disease.

Conclusion

Our findings support the first genetic evidence of the causality of genetically predicted irritability with the risk of developing into CVDs. Our results deliver a viewpoint that more early active interventions to manage an individual's anger and related unhealthy lifestyle habits are needed to prevent the occurrence of adverse cardiovascular events.

Vitamin B12 alleviates myocardial ischemia/reperfusion injury via the SIRT3/AMPK signaling pathway

AIM

To examine the protective effect of vitamin B12 against myocardial ischemia/reperfusion (I/R) injury and elucidate its underlying mechanism of action.

METHODS

Mice were subjected to myocardial I/R injury by left anterior descending coronary artery (LAD) occlusion followed by 24 h reperfusion. Cardiac function and injury were evaluated by echocardiography, triphenyl tetrazolium chloride (TTC) and cardiac troponin T (cTnT) staining, and measuring lactate dehydrogenase (LDH) levels. In addition, various molecular and biochemical methods, as well as RNA sequencing were used to determine the effects and mechanism of action of vitamin B12 on I/R injury.

RESULTS

We found that high doses of vitamin B12 inhibited myocardial I/R injury. Furthermore, our data indicated that vitamin B12 supplementation alleviated cardiac dysfunction and injury by mitigating oxidative stress and apoptosis through downregulation of Nox2, the Ac-SOD2/SOD2 and Bax/Bcl-2 ratios and cleaved caspase-3 expression, and upregulation of SIRT3 expression and AMPK activity. However, these effects were largely reversed following treatment with the SIRT3 inhibitor, 3-TYP. Our RNA-sequencing data further demonstrated that vitamin B12 supplementation reduced inflammation during I/R injury.

CONCLUSION

High doses of vitamin B12 supplements improved myocardial I/R injury by suppressing the accumulation of reactive oxygen species and apoptosis of myocardial tissue through modulation of the SIRT3/AMPK signaling pathway, while reducing inflammation. Our findings suggested that vitamin B12 administered at high doses could be a potential therapy for myocardial I/R damage.

Leveraging Electronic Health Record Data for Timely Chronic Disease Surveillance: The Multi-State EHR-Based Network for Disease Surveillance

CONTEXT

Electronic health record (EHR) data can potentially make chronic disease surveillance more timely, actionable, and sustainable. Although use of EHR data can address numerous limitations of traditional surveillance methods, timely surveillance data with broad population coverage require scalable systems. This report describes implementation, challenges, and lessons learned from the Multi-State EHR-Based Network for Disease Surveillance (MENDS) to help inform how others work with EHR data to develop distributed networks for surveillance.

PROGRAM

Funded by the Centers for Disease Control and Prevention (CDC), MENDS is a data modernization demonstration project that aims to develop a timely national chronic disease sentinel surveillance system using EHR data. It facilitates partnerships between data contributors (health information exchanges, other data aggregators) and data users (state and local health departments). MENDS uses query and visualization software to track local emerging trends. The program also uses statistical and geospatial methods to generate prevalence estimates of chronic disease risk measures at the national and local levels. Resulting data products are designed to inform public health practice and improve the health of the population.

IMPLEMENTATION

MENDS includes 5 partner sites that leverage EHR data from 91 health system and clinic partners and represents approximately 10 million patients across the United States. Key areas of implementation include governance, partnerships, technical infrastructure and support, chronic disease algorithms and validation, weighting and modeling, and workforce education for public health data users.

DISCUSSION

MENDS presents a scalable distributed network model for implementing national chronic disease surveillance that leverages EHR data. Priorities as MENDS matures include producing prevalence estimates at various geographic and subpopulation levels, developing enhanced data sharing and interoperability capacity using international data standards, scaling the network to improve coverage nationally and among underrepresented geographic areas and subpopulations, and expanding surveillance of additional chronic disease measures and social determinants of health.

Macrophage polarization states in atherosclerosis

Atherosclerosis, a chronic inflammatory condition primarily affecting large and medium arteries, is the main cause of cardiovascular diseases. Macrophages are key mediators of inflammatory responses. They are involved in all stages of atherosclerosis development and progression, from plaque formation to transition into vulnerable plaques, and are considered important therapeutic targets. Increasing evidence suggests that the modulation of macrophage polarization can effectively control the progression of atherosclerosis. Herein, we explore the role of macrophage polarization in the progression of atherosclerosis and summarize emerging therapies for the regulation of macrophage polarization. Thus, the aim is to inspire new avenues of research in disease mechanisms and clinical prevention and treatment of atherosclerosis.

Constipation and cardiovascular disease: A two-sample Mendelian randomization analysis

Background

Although several observational studies have suggested positive associations between constipation and cardiovascular disease (CVD), a solid causal association has not been demonstrated. Therefore, a two-sample Mendelian randomization (MR) study was performed to investigate the causal associations between constipation and CVD.

Methods

Independent genetic variants strongly associated with constipation were obtained from the FinnGen consortium. Summary-level data for CVD, including coronary artery disease (CAD), myocardial infarction (MI), heart failure (HF), atrial fibrillation (AF), stroke, and its subtypes, were collected from a few extensive genome-wide association studies (GWASs). The inverse-variance weighted methods, weighted median, and MR-Egger were used for the MR estimates. The Cochran's Q test, MR-Egger intercept tests, MR-PRESSO, MR Steiger test, leave-one-out analyses, and funnel plot were used in the sensitivity analysis.

Results

Genetically determined constipation was suggestively associated with AF risk (odds ratio (OR), 1.07; 95% confidence interval (CI), 1.01, 1.14; p = 0.016). Constipation and other CVD do not appear to be causally related. It was demonstrated that the results were robust through sensitivity analyses.

Conclusion

This MR study demonstrated suggestive causal associations of constipation on AF, despite no associations achieving a significance value after multiple testing corrections. There was no evidence of an association between constipation and the risk of CAD, MI, HF, stroke, or stroke subtypes.

Racial disparities and prevalence of cardiovascular disease risk factors, cardiometabolic risk factors, and cardiovascular health metrics among US adults: NHANES 2011-2018

This study estimated the prevalence of cardiovascular disease (CVD) risk factors, cardiometabolic (CM) risk factors, and cardiovascular health metrics (CVHMs) among US adults and across race/ethnicity groups. The study comprised 8370 US adults aged ≥ 20 years from the National Health and Nutrition Examination Survey (NHANES) 2011-2018, free of coronary heart disease/heart failure, angina/angina pectoris, heart attack, and stroke, who provided complete data for the outcome variables of interest. Age-adjusted prevalence of CVD and CM risk factors, and CVHMs were computed for all adults and across race/ethnicity groups. All analyses accounted for the complex, multi-stage survey sampling design of the NHANES. Hypertension (45.0%), obesity (40.0%), fasting plasma glucose ≥ 100 mg/dL or hypoglycemic medication (51.0%), ideal physical activity (59.2%) and ideal smoking status (56.9%) were most prevalent for the whole sample. Mexican Americans and non-Hispanic Blacks had elevated risk for some, but not all, CVD and CM risk factors compared to non-Hispanic Whites and non-Hispanic Asians. Reducing further health disparities and persisting differences among racial and ethnic groups is vital to achieving the American Heart Association vision of all people having ideal cardiovascular health, living healthier and longer.

[DNVF Memorandum: Health Services Research in the Last Year of Life]

This memorandum outlines current issues concerning health services research on seriously ill and dying people in the last year of their lives as well as support available for their relatives. Patients in the last phase of life can belong to different disease groups, they may have special characteristics (e. g., people with cognitive and complex impairments, economic disadvantage or migration background) and be in certain phases of life (e. g., parents of minor children, (old) age). The need for a designated memorandum on health services research in the last year of life results from the special situation of those affected and from the special features of health services in this phase of life. With reference to these special features, this memorandum describes methodological and ethical specifics as well as current issues in health services research and how these can be adequately addressed using quantitative, qualitative and mixed methods. It has been developed by the palliative medicine section of the German Network for Health Services Research (DNVF) according to the guidelines for DNVF memoranda.

Inflammatory bowel disease and cardiovascular disease: A two-sample Mendelian randomization analysis

Background

Although epidemiological studies have shown a positive relationship between inflammatory bowel disease (IBD) and risk of cardiovascular disease (CVD) outcomes, a solid causal relationship has not been established. Thus, a two-sample Mendelian randomization (MR) study was conducted to explore the potential causal effect between IBD and CVD outcomes.

Methods

We performed a two-sample MR analysis to analyze the causal effect of the IBD on CVD outcome by using summary-level genome-wide association studies of European descent. The inverse-variance weighted (IVW) method was used as the main MR analysis, with complementary analyses of MR Egger, maximum likelihood, weighted median, penalized weighted media, simple mode, weighted mode, and MR-PRESSO methods. Multiple sensitivity analyses were used to evaluate the robustness of our results.

Results

All P-values were greater than 0.05 in the IVW method, showing no evidence of a causal association between circulating IBD and CVD. Similar results were observed by using other MR methods. No evidence of heterogeneity, pleiotropy, or outlier single-nucleotide polymorphisms was detected. Sensitivity analyses demonstrated the robustness of the results.

Conclusion

The findings of this study provided no evidence to support that IBD has a large effect on risk of CVD outcomes, which is in contrast to many previous observational reports. Further studies are needed to determine the potential mechanism of association identified in observational studies.

Improving cardiac rehabilitation patient adherence via personalized interventions

Objectives

Despite documented benefits and physicians’ recommendations to participate in cardiac rehabilitation (CR) programs, the average dropout rate remains between 12–56%. This study’s goal was to demonstrate that using personalized interventions can significantly increase patient adherence.

Method

Ninety-five patients (ages 18–90) eligible for the CR program were randomly recruited and received personalized interventions using the Well-Beat system. Adherence levels were compared to those of a historical control group. The Well-Beat system provided Sheba CR Health Care Provider (HCP) guidelines for personalized patient-therapist dialogue. The system also generated ongoing personalized text messages for each patient sent twice a week and related each patient’s dynamic profile to their daily behavior, creating continuity, and reinforcing the desired behavior.

Results

A significant increase in patient adherence to the CR program: Three months after initiation, 76% remained active compared to the historical average of 24% in the matched control group (log-rank p-value = 0.001).

Conclusions

Using an Artificial Intelligence (AI)-based engine that generated recommendations and messages made it possible to improve patient adherence without increasing HCP load, benefiting all. Presenting customized patient insights to the HCP and generating personalized communications along with action motivating text messages can also be useful for remote care.

Life's Essential 8: Updating and Enhancing the American Heart Association's Construct of Cardiovascular Health: A Presidential Advisory From the American Heart Association

In 2010, the American Heart Association defined a novel construct of cardiovascular health to promote a paradigm shift from a focus solely on disease treatment to one inclusive of positive health promotion and preservation across the life course in populations and individuals. Extensive subsequent evidence has provided insights into strengths and limitations of the original approach to defining and quantifying cardiovascular health. In response, the American Heart Association convened a writing group to recommend enhancements and updates. The definition and quantification of each of the original metrics (Life's Simple 7) were evaluated for responsiveness to interindividual variation and intraindividual change. New metrics were considered, and the age spectrum was expanded to include the entire life course. The foundational contexts of social determinants of health and psychological health were addressed as crucial factors in optimizing and preserving cardiovascular health. This presidential advisory introduces an enhanced approach to assessing cardiovascular health: Life's Essential 8. The components of Life's Essential 8 include diet (updated), physical activity, nicotine exposure (updated), sleep health (new), body mass index, blood lipids (updated), blood glucose (updated), and blood pressure. Each metric has a new scoring algorithm ranging from 0 to 100 points, allowing generation of a new composite cardiovascular health score (the unweighted average of all components) that also varies from 0 to 100 points. Methods for implementing cardiovascular health assessment and longitudinal monitoring are discussed, as are potential data sources and tools to promote widespread adoption in policy, public health, clinical, institutional, and community settings.

Cardiovascular health and four epigenetic clocks

BACKGROUND

Cardiovascular health (CVH) was defined by the American Heart Association as an integrative idealness of seven clinical or lifestyle factors. Based on populations of European ancestry, recent studies have shown that ideal CVH is associated with a slower aging rate. The aging rate is measured by levels of epigenetic age acceleration (EAA), usually obtained from the residuals of regressing DNA methylation (DNAm) age on chronological age. However, little has been known about the association of CVH with biological aging in Asian populations.

METHODS AND RESULTS

We here analyzed blood DNAm data and clinical/lifestyle factors of 2474 Taiwan Biobank (TWB) participants, to investigate the association of CVH with EAA. CVH was assessed by seven components: smoking status, physical activity, dietary habits, body mass index, total cholesterol, fasting glucose, and blood pressure levels. Four measures of EAA were applied, among which two were based on the first-generation DNAm clocks (HannumEAA and IEAA) and two were based on the second-generation clocks (PhenoEAA and GrimEAA). After excluding 276 individuals with cardiovascular diseases, we regressed EAA on the CVH score (ranging from 0 to 7, integrating the abovementioned seven components) while adjusting for sex, drinking status, and educational attainment. Our results showed that a decrease in one point in the CVH score was associated with a 0.350-year PhenoEAA (p = 4.5E-4) and a 0.499-year GrimEAA (p = 4.2E-15). By contrast, HannumEAA and IEAA were not significantly associated with the CVH score. We have obtained consistent results within each generation of epigenetic clocks.

CONCLUSIONS

This is one of the first studies to comprehensively investigate the associations of CVH with four epigenetic clocks. Our TWB data showed that ideal CVH is associated with lower levels of EAA calculated according to the second-generation epigenetic clocks (PhenoEAA and GrimEAA). Having an ideal CVH status can lower EAA and reduce the risk of aging-related disorders.

Call to Action for Cardiovascular Disease in Women: Epidemiology, Awareness, Access, and Delivery of Equitable Health Care: A Presidential Advisory From the American Heart Association

Addressing the pervasive gaps in knowledge and care delivery to reduce sex-based disparities and achieve equity is fundamental to the American Heart Association's commitment to advancing cardiovascular health for all by 2024. This presidential advisory serves as a call to action for the American Heart Association and other stakeholders around the globe to identify and remove barriers to health care access and quality for women. A concise and current summary of existing data across the areas of risk and prevention, access and delivery of equitable care, and awareness and education provides a framework to consider knowledge gaps and research needs critical toward achieving significant progress for the health and well-being of all women.

Towards Integrated Air Pollution Monitoring and Health Impact Assessment Using Federated Learning: A Systematic Review

Environmental issues such as environmental pollutions and climate change are the impacts of globalization and become debatable issues among academics and industry key players. One of the environmental issues which is air pollution has been catching attention among industrialists, researchers, and communities around the world. However, it has always neglected until the impacts on human health become worse, and at times, irreversible. Human exposure to air pollutant such as particulate matters, sulfur dioxide, ozone and carbon monoxide contributed to adverse health hazards which result in respiratory diseases, cardiorespiratory diseases, cancers, and worst, can lead to death. This has led to a spike increase of hospitalization and emergency department visits especially at areas with worse pollution cases that seriously impacting human life and health. To address this alarming issue, a predictive model of air pollution is crucial in assessing the impacts of health due to air pollution. It is also critical in predicting the air quality index when assessing the risk contributed by air pollutant exposure. Hence, this systemic review explores the existing studies on anticipating air quality impact to human health using the advancement of Artificial Intelligence (AI). From the extensive review, we highlighted research gaps in this field that are worth to inquire. Our study proposes to develop an AI-based integrated environmental and health impact assessment system using federated learning. This is specifically aims to identify the association of health impact and pollution based on socio-economic activities and predict the Air Quality Index (AQI) for impact assessment. The output of the system will be utilized for hospitals and healthcare services management and planning. The proposed solution is expected to accommodate the needs of the critical and prioritization of sensitive group of publics during pollution seasons. Our finding will bring positive impacts to the society in terms of improved healthcare services quality, environmental and health sustainability. The findings are beneficial to local authorities either in healthcare or environmental monitoring institutions especially in the developing countries.

Establishing a National Cardiovascular Disease Surveillance System in the United States Using Electronic Health Record Data: Key Strengths and Limitations

Cardiovascular disease surveillance involves quantifying the evolving population-level burden of cardiovascular outcomes and risk factors as a data-driven initial step followed by the implementation of interventional strategies designed to alleviate this burden in the target population. Despite widespread acknowledgement of its potential value, a national surveillance system dedicated specifically to cardiovascular disease does not currently exist in the United States. Routinely collected health care data such as from electronic health records (EHRs) are a possible means of achieving national surveillance. Accordingly, this article elaborates on some key strengths and limitations of using EHR data for establishing a national cardiovascular disease surveillance system. Key strengths discussed include the: (1) ubiquity of EHRs and consequent ability to create a more "national" surveillance system, (2) existence of a common data infrastructure underlying the health care enterprise with respect to data domains and the nomenclature by which these data are expressed, (3) longitudinal length and detail that define EHR data when individuals repeatedly patronize a health care organization, and (4) breadth of outcomes capable of being surveilled with EHRs. Key limitations discussed include the: (1) incomplete ascertainment of health information related to health care-seeking behavior and the disconnect of health care data generated at separate health care organizations, (2) suspect data quality resulting from the default information-gathering processes within the clinical enterprise, (3) questionable ability to surveil patients through EHRs in the absence of documented interactions, and (4) the challenge in interpreting temporal trends in health metrics, which can be obscured by changing clinical and administrative processes.

Could Artificial Intelligence/Machine Learning and Inclusion of Diet-Gut Microbiome Interactions Improve Disease Risk Prediction? Case Study: Coronary Artery Disease

Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and the main leading cause of morbidity and mortality worldwide, posing a huge socio-economic burden to the society and health systems. Therefore, timely and precise identification of people at high risk of CAD is urgently required. Most current CAD risk prediction approaches are based on a small number of traditional risk factors (age, sex, diabetes, LDL and HDL cholesterol, smoking, systolic blood pressure) and are incompletely predictive across all patient groups, as CAD is a multi-factorial disease with complex etiology, considered to be driven by both genetic, as well as numerous environmental/lifestyle factors. Diet is one of the modifiable factors for improving lifestyle and disease prevention. However, the current rise in obesity, type 2 diabetes (T2D) and CVD/CAD indicates that the “one-size-fits-all” approach may not be efficient, due to significant variation in inter-individual responses. Recently, the gut microbiome has emerged as a potential and previously under-explored contributor to these variations. Hence, efficient integration of dietary and gut microbiome information alongside with genetic variations and clinical data holds a great promise to improve CAD risk prediction. Nevertheless, the highly complex nature of meals combined with the huge inter-individual variability of the gut microbiome poses several Big Data analytics challenges in modeling diet-gut microbiota interactions and integrating these within CAD risk prediction approaches for the development of personalized decision support systems (DSS). In this regard, the recent re-emergence of Artificial Intelligence (AI) / Machine Learning (ML) is opening intriguing perspectives, as these approaches are able to capture large and complex matrices of data, incorporating their interactions and identifying both linear and non-linear relationships. In this Mini-Review, we consider (1) the most used AI/ML approaches and their different use cases for CAD risk prediction (2) modeling of the content, choice and impact of dietary factors on CAD risk; (3) classification of individuals by their gut microbiome composition into CAD cases vs. controls and (4) modeling of the diet-gut microbiome interactions and their impact on CAD risk. Finally, we provide an outlook for putting it all together for improved CAD risk predictions.

Contemporary Management of Dyslipidemia

The treatment of dyslipidemia continues to be a dynamic and controversial topic. Even the most appropriate therapeutic range for lipid levels-including that of triglycerides and low-density lipoprotein cholesterol-remain actively debated. Furthermore, with ever-increasing options and available treatment modalities, the management of dyslipidemia has progressed in both depth and complexity. An understanding of appropriate lipid-lowering therapy remains an essential topic of review for practitioners across medical specialties. The goal of this review is to provide an overview of recent research developments and recommendations for patients with dyslipidemia as a means of better informing the clinical practice of lipid management. By utilizing a guideline-directed approach, we provide a reference point on optimal lipid-lowering therapies across the spectrum of dyslipidemia. Special attention is paid to long-term adherence to lipid-lowering therapies, and the benefits derived from instituting appropriate medications in a structured manner alongside monitoring. Novel therapies and their impact on lipid lowering are discussed in detail, as well as potential avenues for research going forward. The prevention of cardiovascular disease remains paramount, and this review provides a roadmap for instituting appropriate therapies in cardiovascular disease prevention.

Identification of Incident Atrial Fibrillation From Electronic Medical Records

Background Electronic medical records are increasingly used to identify disease cohorts; however, computable phenotypes using electronic medical record data are often unable to distinguish between prevalent and incident cases. Methods and Results We identified all Olmsted County, Minnesota residents aged ≥18 with a first-ever International Classification of Diseases, Ninth Revision (ICD-9) diagnostic code for atrial fibrillation or atrial flutter from 2000 to 2014 (N=6177), and a random sample with an International Classification of Diseases, Tenth Revision (ICD-10) code from 2016 to 2018 (N=200). Trained nurse abstractors reviewed all medical records to validate the events and ascertain the date of onset (incidence date). Various algorithms based on number and types of codes (inpatient/outpatient), medications, and procedures were evaluated. Positive predictive value (PPV) and sensitivity of the algorithms were calculated. The lowest PPV was observed for 1 code (64.4%), and the highest PPV was observed for 2 codes (any type) >7 days apart but within 1 year (71.6%). Requiring either 1 inpatient or 2 outpatient codes separated by >7 days but within 1 year had the best balance between PPV (69.9%) and sensitivity (95.5%). PPVs were slightly higher using ICD-10 codes. Requiring an anticoagulant or antiarrhythmic prescription or electrical cardioversion in addition to diagnostic code(s) modestly improved the PPVs at the expense of large reductions in sensitivity. Conclusions We developed simple, exportable, computable phenotypes for atrial fibrillation using structured electronic medical record data. However, use of diagnostic codes to identify incident atrial fibrillation is prone to some misclassification. Further study is warranted to determine whether more complex phenotypes, including unstructured data sources or using machine learning techniques, may improve the accuracy of identifying incident atrial fibrillation.

Favorable Cardiovascular Health Is Associated With Lower Prevalence, Incidence, Extent, and Progression of Extracoronary Calcification: MESA

BACKGROUND

Ideal cardiovascular health (CVH) is associated with a lower incidence of cardiovascular disease. Extracoronary calcification (ECC)-measured at the aortic valve, mitral annulus, ascending thoracic aorta, and descending thoracic aorta-is an indicator of systemic atherosclerosis. This study examined whether favorable CVH was associated with a lower risk of ECC.

METHODS

We analyzed data from MESA (Multi-Ethnic Study of Atherosclerosis) participants aged 45 to 84 years without cardiovascular disease at baseline. ECC was measured by noncontrast cardiac computed tomography scan at baseline and after an average of 2.4 years. Prevalent ECC was defined as an Agatston score >0 at the baseline scan. Incident ECC was defined as Agatston score >0 at the follow-up scan among participants with Agatston score of 0 at the baseline scan. Each CVH metric (smoking, physical activity, body mass index, diet, blood pressure, total cholesterol, and blood glucose) was scored 0 to 2 points, with 2 indicating ideal; 1, intermediate; and 0, poor. The aggregated CVH score was 0 to 14 points (0-8, inadequate; 9-10, average; 11-14, optimal). We used Poisson and linear mixed-effects regression models to examine the association between CVH and ECC adjusted for sociodemographic factors.

RESULTS

Of 6504 participants, 53% were women with a mean age (SD) of 62 (10) years. Optimal and average CVH scores were associated with lower ECC prevalence, incidence, and extent. For example, optimal CVH scores were associated with 57%, 56%, 70%, and 54% lower risk of incident aortic valve calcification, mitral annulus calcification, ascending thoracic aorta calcification, and descending thoracic aorta calcification, respectively. In addition, optimal and average CVH scores were associated with lower ECC progression at 2 years, although these associations were only significant for mitral annulus calcification and descending thoracic aorta calcification.

CONCLUSIONS

In this multiethnic cohort, favorable CVH was associated with a lower risk of extracoronary atherosclerosis. These findings emphasize the importance of primordial prevention as an intervention to reduce the burden of cardiovascular disease.

Methods for the Comprehensive in vivo Analysis of Energy Flux, Fluid Homeostasis, Blood Pressure, and Ventilatory Function in Rodents

Cardiovascular disease represents the leading cause of death in the United States, and metabolic diseases such as obesity represent the primary impediment to improving cardiovascular health. Rodent (mouse and rat) models are widely used to model cardiometabolic disease, and as a result, there is increasing interest in the development of accurate and precise methodologies with sufficiently high resolution to dissect mechanisms controlling cardiometabolic physiology in these small organisms. Further, there is great utility in the development of centralized core facilities furnished with high-throughput equipment configurations and staffed with professional content experts to guide investigators and ensure the rigor and reproducibility of experimental endeavors. Here, we outline the array of specialized equipment and approaches that are employed within the Comprehensive Rodent Metabolic Phenotyping Core (CRMPC) and our collaborating laboratories within the Departments of Physiology, Pediatrics, Microbiology & Immunology, and Biomedical Engineering at the Medical College of Wisconsin (MCW), for the detailed mechanistic dissection of cardiometabolic function in mice and rats. We highlight selected methods for the analysis of body composition and fluid compartmentalization, electrolyte accumulation and flux, energy accumulation and flux, physical activity, ingestive behaviors, ventilatory function, blood pressure, heart rate, autonomic function, and assessment and manipulation of the gut microbiota. Further, we include discussion of the advantages and disadvantages of these approaches for their use with rodent models, and considerations for experimental designs using these methods.

Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools

Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on sex- and gender-based differences in cardiovascular disease development and outcomes, the need for more effective approaches to screening for risk factors and phenotypes in women is ever urgent. Public health surveillance and health care delivery systems now continuously generate massive amounts of data that could be leveraged to enable both screening of cardiovascular risk and implementation of tailored preventive interventions across a woman's life span. However, health care providers, clinical guidelines committees, and health policy experts are not yet sufficiently equipped to optimize the collection of data on women, use or interpret these data, or develop approaches to targeting interventions. Therefore, we provide a broad overview of the key opportunities for cardiovascular screening in women while highlighting the potential applications of artificial intelligence along with digital technologies and tools.

Identifying Cardiovascular Risk Profiles Clusters among Mediterranean Adolescents across Seven Countries

Cardiovascular diseases (CVDs) are the number one cause of death globally and are partially due to the inability to control modifiable lifestyle risk factors. The aim of this study was to analyze the profiles of adolescents from seven Mediterranean countries (Greece, Israel, Italy, Macedonia, Malta, Portugal, Spain) according to their modifiable lifestyle risk factors for CVD (overweight/obesity, physical activity, smoking, alcohol consumption). The sample consisted of 26,110 adolescents (52.3% girls) aged 11, 13, and 15 years who participated in the Health Behavior in School-aged Children (HBSC) survey in 2018 across the seven countries. Sociodemographic characteristics (sex, age, country of residence, socioeconomic status) and CVD modifiable lifestyle risk factors (overweight/obesity, physical activity, smoking, alcohol consumption) were recorded. A two-step cluster analysis, one-way analysis of variance, and chi-square test were performed. Four different cluster groups were identified: two low-risk groups (64.46%), with risk among those with low physical activity levels; moderate-risk group (14.83%), with two risk factors (unhealthy weight and low physical activity level); and a high-risk group (20.7%), which presented risk in all modifiable lifestyle risk factors. Older adolescents reported a higher likelihood of being in the high-risk group. Given that the adolescence period constitutes an important time for interventions aimed at CVD prevention, identifying profiles of moderate- and high-risk adolescents is crucial.

Favorable Cardiovascular Health Is Associated With Lower Hepatocyte Growth Factor Levels in the Multi-Ethnic Study of Atherosclerosis

Introduction: Hepatocyte growth factor (HGF) is a cytokine released in response to endothelial injury and a potential biomarker of cardiovascular disease (CVD) risk. We examined the association between cardiovascular health (CVH) and HGF in a multi-ethnic cohort of adults free from CVD at baseline. Methods: This cross-sectional study conducted between 2020 and 2021 used MESA baseline examination data (2000-2002) from 6,490 US adults aged 45-84 years. The independent variable was CVH measured by the CVH score and number of ideal metrics. The score was derived from seven metrics: smoking, body mass index, physical activity, diet, total cholesterol, blood pressure and blood glucose. Each metric was scored 0 points (poor), 1 point (intermediate) and 2 points (ideal). The total CVH score ranged from 0 to 14. An inadequate score was 0-8, average, 9-10 and optimal, 11-14. The dependent variable was logarithmically transformed HGF. We used regression analyses to estimate associations between CVH and HGF adjusting for sociodemographic factors. Results: Participants' mean (SD) age was 62 (10) years. Fifty-three percent were female. A one-unit increment in the CVH score was significantly associated with 3% lower HGF levels. Average and optimal CVH scores were significantly associated with 8% and 12% lower HGF levels, respectively, compared to inadequate scores. Additionally, a greater number of ideal metrics was associated with lower HGF levels. Conclusion: Favorable CVH was significantly associated with lower HGF levels in this ethnically diverse cohort. Interventions aimed at promoting and preserving favorable CVH may reduce the risk of endothelial injury as indicated by lower serum HGF levels.

Constructing Epidemiologic Cohorts from Electronic Health Record Data

In the United States, electronic health records (EHR) are increasingly being incorporated into healthcare organizations to document patient health and services rendered. EHRs serve as a vast repository of demographic, diagnostic, procedural, therapeutic, and laboratory test data generated during the routine provision of health care. The appeal of using EHR data for epidemiologic research is clear: EHRs generate large datasets on real-world patient populations in an easily retrievable form permitting the cost-efficient execution of epidemiologic studies on a wide array of topics. Constructing epidemiologic cohorts from EHR data involves as a defining feature the development of data machinery, which transforms raw EHR data into an epidemiologic dataset from which appropriate inference can be drawn. Though data machinery includes many features, the current report focuses on three aspects of machinery development of high salience to EHR-based epidemiology: (1) selecting study participants; (2) defining “baseline” and assembly of baseline characteristics; and (3) follow-up for future outcomes. For each, the defining features and unique challenges with respect to EHR-based epidemiology are discussed. An ongoing example illustrates key points. EHR-based epidemiology will become more prominent as EHR data sources continue to proliferate. Epidemiologists must continue to improve the methods of EHR-based epidemiology given the relevance of EHRs in today’s healthcare ecosystem.

Ecological Associations Between Inclusionary Zoning Policies and Cardiovascular Disease Risk Prevalence: An Observational Study

BACKGROUND

Providing an adequate supply of affordable housing has become an increasingly difficult challenge for US cities. Inclusionary zoning (IZ) policies have become an increasingly popular response. Substantial research has demonstrated the health benefits of stable, affordable housing. There is anecdotal but not systematic evidence that IZ policies may be associated with some health benefits of affordable housing.

METHODS

We rely on data from the 2017 500 Cities Project, the 2016 to 2017 Lincoln Institute for Land Policy survey, and the 2011 to 2015 American Community Survey. We perform bivariate tests and cluster ordinary least squares regression to examine associations at the municipal level between having inclusionary zoning (IZ) policies, the attributes of those policies, and the prevalence of several cardiovascular outcomes.

RESULTS

Cardiovascular outcomes and socioeconomic characteristics were uniformly better in cities with IZ policies. IZ policies were associated with lower blood pressure (95% CI, -0.50 to -0.13), cholesterol (CI, -0.89 to -0.31), and blood pressure medication (CI, -0.57 to -0.03) prevalence. Some characteristics of IZ programs such as being mandatory, prioritizing rental development, and allocating a larger share of affordable housing are associated with cardiovascular risk prevalence.

CONCLUSIONS

Characteristics of IZ programs that ultimately benefit low-income residents are associated with favorable municipal-level cardiovascular health. Further, IZ policies could potentially address complex health challenges among economically vulnerable households.

The Effects of Ischemic Preconditioning Supplementation on Endothelial Function: A Systematic Review and Meta-Analysis

Objective

Ischemic preconditioning (IPC) has gradually been promoted in clinical practice to lower the risk of cardiovascular surgery and postoperative complications. We investigated the role of IPC on vascular endothelial function and the relationship between IPC, flow-mediated dilation (FMD), and brachial artery diameter (BAD).

Methods

Systematic searches were conducted in PubMed, Medline, Cochrane Library, Embase, and Scopus databases from their inception to March 20, 2020. This research included randomized controlled trials (RCTs) with adults, and the values of FMD and BAD were considered as the primary outcomes. Ten studies comprising 292 participants were included in the meta-analysis.

Results

Regarding FMD, we observed beneficial effects of IPC on endothelial function (standardized mean difference (SMD): 1.82; 95% confidence interval (CI): 0.64, 3.01; p < 0.001; I ² = 89.9%). However, the available evidence did not indicate that IPC affected BAD (SMD: 0.08; 95% CI: -0.03, 0.18; p > 0.05; I ² = 76.5%).

Conclusions

Our meta-analysis indicated a significant effect of IPC on the endothelial function of the blood vessels, affecting FMD but not BAD.

Further understanding of ideal cardiovascular health score metrics and cardiovascular disease

INTRODUCTION

The American Heart Association (AHA) introduced the construct of 'cardiovascular health (CVH)', to focus on primordial prevention to reduce the burden of cardiovascular disease (CVD). The CVH score includes seven health and behavioral metrics (smoking, physical activity, body mass index, diet, total cholesterol, blood pressure, blood glucose), which are characterized as being ideal, intermediate, or poor.

AREAS COVERED

In this review, we describe the utility of the CVH score for monitoring and promoting wellness, overall and by key sociodemographic groups, and for tracking of temporal trends.

EXPERT OPINION

Notably, the seven factors are all modifiable, which differs from 10-year CVD risk scores that include non-modifiable components such as age, sex, and race. Numerous epidemiological studies have shown that achievement of a greater number of ideal CVH metrics is associated with lower incidences of CVD, cardiovascular mortality, and all-cause mortality. Longer duration of favorable CVH is associated with greater longevity and compressed morbidity. Nevertheless, the prevalence of favorable CVH is low, with <20% of U.S. adults meeting ≥5 metrics at ideal levels and significant racial/ethnic disparities persist. Many challenges must be overcome to improve CVH at individual and societal levels if the AHA Impact Goals are to be fully realized.

Association of Autism Spectrum Disorder, Neuroticism, and Subjective Well-Being With Cardiovascular Diseases: A Two-Sample Mendelian Randomization Study

Background: Previous observational studies have reported an association between psychiatric traits and cardiovascular diseases (CVDs). In this two-sample Mendelian randomization (MR) study, we aimed to investigate the causality between psychiatric traits and CVDs.

Methods: Single-nucleotide polymorphisms (SNPs) associated with autism spectrum disorder (ASD), neuroticism, and subjective well-being at genome-wide significance (P < 1 × 10⁻⁸) were identified from genome-wide association studies. Summary-level data of the outcomes, including coronary artery disease (CAD), myocardial infarction (MI), atrial fibrillation (AF), and heart failure (HF), were obtained from several largest datasets. The inverse-variance weighted (IVW) method was used as our main analyses to conduct this MR study. Sensitivity analyses included the weighted median, the MR-robust adjusted profile score (MR-RAPS), and the MR pleiotropy residual sum and outlier (MR-PRESSO) method. Repeated MR analyses using a more relaxed threshold (P < 1 × 10⁻⁶) for instruments selection and multivariable MR analyses were also applied to evaluate the robustness of results.

Results: The MR analyses showed that genetic predisposition to ASD was associated with a higher risk of AF [odds ratio (OR), 1.109; 95% confidence interval (CI), 1.023–1.201; P = 0.011] and HF (OR, 1.138; 95% CI, 1.036–1.251; P = 0.007). Neuroticism was casually associated with an increased risk of AF (OR, 1.201; 95% CI, 1.037–1.392; P = 0.015), whereas subjective well-being had a protective effect on HF (OR, 0.732; 95% CI, 0.574–0.933; P = 0.012). No other causal association between psychiatric traits and CVDs was observed. Consistent results were obtained in sensitivity analyses.

Conclusion: This study provided evidence of causal associations of ASD with a higher risk of AF and HF. Besides, neuroticism was casually associated with an increased risk of AF, and subjective well-being was associated with a decreased risk of HF.

Epidemiology of Heart Failure: A Contemporary Perspective

Designated as an emerging epidemic in 1997, heart failure (HF) remains a major clinical and public health problem. This review focuses on the most recent studies identified by searching the Medline database for publications with the subject headings HF, epidemiology, prevalence, incidence, trends between 2010 and present. Publications relevant to epidemiology and population sciences were retained for discussion in this review after reviewing abstracts for relevance to these topics. Studies of the epidemiology of HF over the past decade have improved our understanding of the HF syndrome and of its complexity. Data suggest that the incidence of HF is mostly flat or declining but that the burden of mortality and hospitalization remains mostly unabated despite significant ongoing efforts to treat and manage HF. The evolution of the case mix of HF continues to be characterized by an increasing proportion of cases with preserved ejection fraction, for which established effective treatments are mostly lacking. Major disparities in the occurrence, presentation, and outcome of HF persist particularly among younger Black men and women. These disturbing trends reflect the complexity of the HF syndrome, the insufficient mechanistic understanding of its various manifestations and presentations and the challenges of its management as a chronic disease, often integrated within a context of aging and multimorbidity. Emerging risk factors including omics science offer the promise of discovering new mechanistic pathways that lead to HF. Holistic management approaches must recognize HF as a syndemic and foster the implementation of multidisciplinary approaches to address major contributors to the persisting burden of HF including multimorbidity, aging, and social determinants of health.

Greater Acculturation is Associated With Poorer Cardiovascular Health in the Multi-Ethnic Study of Atherosclerosis

Background Greater acculturation is associated with increased risk of cardiovascular disease. However, little is known about the association between acculturation and ideal cardiovascular health (CVH) as measured by the American Heart Association's 7 CVH metrics. We investigated the association between acculturation and ideal CVH among a multi-ethnic cohort of US adults free of clinical cardiovascular disease at baseline. Methods and Results This was a cross-sectional analysis of 6506 men and women aged 45 to 84 years of 4 races/ethnicities. We examined measures of acculturation(birthplace, language spoken at home, and years lived in the United States [foreign-born participants]) by CVH score. Scores of 0 to 8 indicate inadequate, 9 to 10 average and 11 to 14 optimal CVH. We used multivariable regression to examine associations between acculturation and CVH, adjusting for age, sex, race/ethnicity, education, income and health insurance. The mean (SD) age was 62 (10) years, 53% were women, 39% non-Hispanic White-, 26% non-Hispanic Black-, 12% Chinese- and 22% Hispanic-Americans. US-born participants had lower odds of optimal CVH (odds ratio [OR]: 0.63 [0.50-0.79], P<0.001) compared with foreign-born participants. Participants who spoke Chinese and other foreign languages at home had greater odds of optimal CVH compared with those who spoke English (1.91 [1.08-3.36], P=0.03; and 1.65 [1.04-2.63], P=0.03, respectively). Foreign-born participants who lived the longest in the United States had lower odds of optimal CVH (0.62 [0.43-0.91], P=0.02). Conclusions Greater US acculturation was associated with poorer CVH. This finding suggests that the promotion of ideal CVH should be encouraged among immigrant populations since more years lived in the United States was associated with poorer CVH.

Long Noncoding RNAs in Myocardial Ischemia-Reperfusion Injury

Following an acute myocardial infarction, reperfusion therapy is currently the most effective way to save the ischemic myocardium; however, restoring blood flow may lead to a myocardial ischemia-reperfusion injury (MIRI). Recent studies have confirmed that long-chain noncoding RNAs (LncRNAs) play important roles in the pathophysiology of MIRIs. These LncRNA-mediated roles include cardiomyocyte apoptosis, autophagy, necrosis, oxidative stress, inflammation, mitochondrial dysfunction, and calcium overload, which are regulated through the expression of target genes. Thus, LncRNAs may be used as clinical diagnostic markers and therapeutic targets to treat or prevent MIRI. This review evaluates the research on LncRNAs involved in MIRIs and provides new ideas for preventing and treating this type of injury.