2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk

Identifying antinuclear antibody positive individuals at risk for developing systemic autoimmune disease: development and validation of a real-time risk model

Objective

Positive antinuclear antibodies (ANAs) cause diagnostic dilemmas for clinicians. Currently, no tools exist to help clinicians interpret the significance of a positive ANA in individuals without diagnosed autoimmune diseases. We developed and validated a risk model to predict risk of developing autoimmune disease in positive ANA individuals.

Methods

Using a de-identified electronic health record (EHR), we randomly chart reviewed 2,000 positive ANA individuals to determine if a systemic autoimmune disease was diagnosed by a rheumatologist. A priori, we considered demographics, billing codes for autoimmune disease-related symptoms, and laboratory values as variables for the risk model. We performed logistic regression and machine learning models using training and validation samples.

Results

We assembled training (n = 1030) and validation (n = 449) sets. Positive ANA individuals who were younger, female, had a higher titer ANA, higher platelet count, disease-specific autoantibodies, and more billing codes related to symptoms of autoimmune diseases were all more likely to develop autoimmune diseases. The most important variables included having a disease-specific autoantibody, number of billing codes for autoimmune disease-related symptoms, and platelet count. In the logistic regression model, AUC was 0.83 (95% CI 0.79-0.86) in the training set and 0.75 (95% CI 0.68-0.81) in the validation set.

Conclusion

We developed and validated a risk model that predicts risk for developing systemic autoimmune diseases and can be deployed easily within the EHR. The model can risk stratify positive ANA individuals to ensure high-risk individuals receive urgent rheumatology referrals while reassuring low-risk individuals and reducing unnecessary referrals.

Comparative Analysis of Three Atherosclerotic Cardiovascular Disease Risk Prediction Models in Individuals Aged 75 and Older

Purpose

To evaluate the performance of the Framingham cardiovascular risk score (FRS)/pooled cohort equations (PCE)/China prediction for atherosclerotic cardiovascular disease (ASCVD) risk (China-PAR model) in a prospective cohort of Chinese older adults.

Patients and Methods

We assessed 717 older adults aged 75-85 years without ASCVD at the baseline from the Sichuan province of China. The participants were followed annually from 2011 to 2021. We obtained the participants' information through the medical records of physical examination and evaluated their 10-year ASCVD risk using FRS, PCE, and China-PAR. We further evaluated the predictive abilities of three assessment models.

Results

During the 10-year follow-up, 206 participants developed ASCVD, with an incidence rate of 28.73%. The FRS and China-PAR moderately underestimated the risk of ASCVD (22.1% and 12.4%, respectively), but while PCE overestimated the risk (36.1%). FRS and China-PAR were found to underestimate the risk of ASCVD (26% and 63%, respectively) for men, while PCE overestimated the risk by 8%; For women, FRS and China-PAR were found to underestimate the risk of ASCVD (14% and 35%, respectively), while PCE overestimated the risk by 88%.

Conclusion

The 10-year ASCVD risk was found to be overestimated by PCE. China-PAR had the most accurate predictions in women, while FRS was particularly well-calibrated in males. All three risk models have good discrimination, with FRS and PCE being well-calibrated in men and all three being well-calibrated in women. Therefore, accurate risk models are warranted to facilitate the prevention of ASCVD at the baseline among Chinese older adults.

Fitness age outperforms body mass index in differentiating aging patterns and health risk profiles of healthy adults aged 51-80 years

Physical fitness has been extensively shown to strongly associate with general health status and major health risks. Here we tested the ability of a novel estimate of fitness age (FitAge) to differentiate aging trajectories.This study aimed at (1) testing the ability of FitAge to differentiate aging patterns among decelerated, normal, and accelerated agers in selected health domains, (2) estimating the risk for developing major health issues depending on the aging trajectory, and (3) comparing FitAge to body mass index (BMI) categorization in differentiating healthy from unhealthy aging patterns.A total of 176 volunteers participated in this cross-sectional study. Participants underwent clinical screening and a comprehensive assessment of body composition, nutritional and health-related status, cognitive functioning, and haematochemical analyses with routine tests, oxidative stress, and inflammation markers. Scores for major health risks were also computed.FitAge outperformed BMI in estimating major health risk scores and was able to differentiate decelerated from normal and accelerated agers for health risk profile and several physiological domains. Body composition, immune system activation, and inflammation markers emerged as those variables flagging the largest differences between decelerated and accelerated aging patterns.The novel estimate of biological aging can accurately differentiate both in women and men decelerated from accelerated agers in almost all the domains scrutinized. Overall, decelerated aging is linked to positively oriented features which associate with reduced risk of developing major health issues.The present findings have potential relevance and practical implications to identify individuals at higher risk of accelerated aging according to their FitAge estimated via simple and cost-effective motor tests.

Dyslipidemia and cardiovascular disease among childhood cancer survivors: a St. Jude Lifetime Cohort report

BACKGROUND

Childhood cancer survivors have increased risk of dyslipidemia and atherosclerotic cardiovascular disease (CVD). The aim of this study was to evaluate the prevalence and associated cardiovascular risks of specific lipid abnormalities among childhood cancer survivors.

METHODS

Comprehensive lipid panel measurements were obtained from 4115 5-year survivors, with 3406 (mean age at evaluation = 35.2 years, SD = 10.4 years) not having previous dyslipidemia diagnosis, as well as 624 age, sex, and race and ethnicity matched community controls.

RESULTS

Previously undiagnosed dyslipidemia with abnormal low-density lipoprotein (LDL) cholesterol (>160 mg/dL), non-high density lipoprotein (HDL) cholesterol (>190 mg/dL), HDL cholesterol (<40 mg/dL for men, <50 mg/dL for women), and triglycerides (>150 mg/dL) were identified in 4%, 6%, 30%, and 17%, respectively. Survivors without previous dyslipidemia diagnosis had higher LDL cholesterol and non-HDL cholesterol and lower HDL cholesterol than community controls. Cranial radiotherapy (relative risk [RR] = 2.2, 95% confidence interval [CI] = 1.6 to 3.0 for non-HDL cholesterol) and total body irradiation for hematopoietic cell transplantation (RR = 6.7, 95% CI = 3.5 to 13.0 for non-HDL cholesterol; RR = 9.9, 95% CI = 6.0 to 16.3 for triglycerides) were associated with greater risk of dyslipidemia. Diagnoses of low HDL cholesterol (hazard ratio [HR] = 2.9, 95% CI = 1.8 to 4.7) and elevated triglycerides (HR = 3.1, 95% CI = 1.9 to 5.1) were associated with increased risk for myocardial infarction, and diagnoses of high LDL cholesterol (HR = 2.2, 95% CI = 1.3 to 3.7), high non-HDL cholesterol (HR = 2.2, 95% CI = 1.3 to 3.7), low HDL cholesterol (HR = 3.9, 95% CI = 2.8 to 5.4), and elevated triglycerides (HR = 3.8, 95% CI = 2.7 to 5.5) were associated with increased risk for cardiomyopathy.

CONCLUSIONS

Previously undiagnosed dyslipidemia among childhood cancer survivors was associated with increased risk for myocardial infarction and cardiomyopathy. Comprehensive dyslipidemia evaluation and treatment are needed to reduce cardiovascular morbidity in this population.

Association Between Pharmacy Proximity With Cardiovascular Medication Use and Risk Factor Control in the United States

BACKGROUND

Poor neighborhood-level access to health care, including community pharmacies, contributes to cardiovascular disparities in the United States. The authors quantified the association between pharmacy proximity, antihypertensive and statin use, and blood pressure (BP) and low-density lipoprotein cholesterol (LDL-C) among a large, diverse US cohort.

METHODS AND RESULTS

A cross-sectional analysis of Black and White participants in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study during 2013 to 2016 was conducted. The authors designated pharmacy proximity by census tract using road network analysis with population-weighted centroids within a 10-minute drive time, with 5- and 20-minute sensitivity analyses. Pill bottle review measured medication use, and BP and LDL-C were assessed using standard methods. Poisson regression was used to quantify the association between pharmacy proximity with medication use and BP control, and linear regression for LDL-C. Among 16 150 REGARDS participants between 2013 and 2016, 8319 (51.5%) and 8569 (53.1%) had an indication for antihypertensive and statin medication, respectively, and pharmacy proximity data. The authors did not find a consistent association between living in a census tract with higher pharmacy proximity and antihypertensive medication use, BP control, or statin medication use and LDL-C levels, regardless of whether the area was rural, suburban, or urban. Results were similar among the 5- and 20-minute drive-time analyses.

CONCLUSIONS

Living in a low pharmacy proximity census tract may be associated with antihypertensive and statin medication use, or with BP control and LDL-C levels. Although, in this US cohort, outcomes were similar for adults living in high or low pharmacy proximity census tracts.

Genetic-Guided Pharmacotherapy for Coronary Artery Disease: A Systematic and Critical Review of Economic Evaluations

BACKGROUND

Genetic-guided pharmacotherapy (PGx) is not recommended in clinical guidelines for coronary artery disease (CAD). We aimed to examine the extent and quality of evidence from economic evaluations of PGx in CAD and to identify variables influential in changing conclusions on cost-effectiveness.

METHODS AND RESULTS

From systematic searches across 6 databases, 2 independent reviewers screened, included, and rated the methodological quality of economic evaluations of PGx testing to guide pharmacotherapy for patients with CAD. Of 35 economic evaluations included, most were model-based cost-utility analyses alone, or alongside cost-effectiveness analyses of PGx testing to stratify patients into antiplatelets (25/35), statins (2/35), pain killers (1/35), or angiotensin-converting enzyme inhibitors (1/35) to predict CAD risk (8/35) or to determine the coumadin doses (1/35). To stratify patients into antiplatelets (96/151 comparisons with complete findings of PGx versus non-PGx), PGx was more effective and more costly than non-PGx clopidogrel (28/43) but less costly than non-PGx prasugrel (10/15) and less costly and less effective than non-PGx ticagrelor (22/25). To predict CAD risk (51/151 comparisons), PGx using genetic risk scores was more effective and less costly than clinical risk score (13/17) but more costly than no risk score (16/19) or no treatment (9/9). The remaining comparisons were too few to observe any trend. Mortality risk was the most common variable (47/294) changing conclusions.

CONCLUSIONS

Economic evaluations to date found PGx to stratify patients with CAD into antiplatelets or to predict CAD risk to be cost-effective, but findings varied based on the non-PGx comparators, underscoring the importance of considering local practice in deciding whether to adopt PGx.

Nurse-Led Strategy to Improve Blood Pressure and Cholesterol Level Among People With HIV: A Randomized Clinical Trial

Importance

Despite higher atherosclerotic cardiovascular disease (ASCVD) risk, people with HIV (PWH) experience unique barriers to ASCVD prevention, such as changing models of HIV primary care.

Objective

To test whether a multicomponent nurse-led strategy would improve systolic blood pressure (SBP) and non-high-density lipoprotein (HDL) cholesterol level in a diverse population of PWH receiving antiretroviral therapy (ART).

Design, Setting, and Participants

This randomized clinical trial enrolled PWH at 3 academic HIV clinics in the US from September 2019 to January 2022 and conducted follow-up for 12 months until January 2023. Included patients were 18 years or older and had a confirmed HIV diagnosis, an HIV-1 viral load less than 200 copies/mL, and both hypertension and hypercholesterolemia. Participants were stratified by trial site and randomized 1:1 to either the multicomponent EXTRA-CVD (A Nurse-Led Intervention to Extend the HIV Treatment Cascade for Cardiovascular Disease Prevention) intervention group or the control group. Primary analyses were conducted according to the intention-to-treat principle.

Intervention

The EXTRA-CVD group received home BP monitoring guidance and BP and cholesterol management from a dedicated prevention nurse at 4 in-person visits (baseline and 4, 8, and 12 months) and frequent telephone check-ins up to every 2 weeks as needed. The control group received general prevention education sessions from the prevention nurse at each of the 4 in-person visits.

Main Outcomes and Measures

Study-measured SBP was the primary outcome, and non-HDL cholesterol level was the secondary outcome. Measurements were taken over 12 months and assessed by linear mixed models. Prespecified moderators tested were sex at birth, baseline ASCVD risk, and trial site.

Results

A total of 297 PWH were randomized to the EXTRA-CVD arm (n = 149) or control arm (n = 148). Participants had a median (IQR) age of 59.0 (53.0-65.0) years and included 234 males (78.8%). Baseline mean (SD) SBP was 135.0 (18.8) mm Hg and non-HDL cholesterol level was 139.9 (44.6) mg/dL. At 12 months, participants in the EXTRA-CVD arm had a clinically significant 4.2-mm Hg (95% CI, 0.3-8.2 mm Hg; P = .04) lower SBP and 16.9-mg/dL (95% CI, 8.6-25.2 mg/dL; P < .001) lower non-HDL cholesterol level compared with participants in the control arm. There was a clinically meaningful but not statistically significant difference in SBP effect in females compared with males (11.8-mm Hg greater difference at 4 months, 9.6 mm Hg at 8 months, and 5.9 mm Hg at 12 months; overall joint test P = .06).

Conclusions and Relevance

Results of this trial indicate that the EXTRA-CVD strategy effectively reduced BP and cholesterol level over 12 months and should inform future implementation of multifaceted ASCVD prevention programs for PWH.

Trial Registration

ClinicalTrials.gov Identifier: NCT03643705.

Circulating MicroRNA-19 and cardiovascular risk reduction in response to weight-loss diets

OBJECTIVE

MicroRNA-19 (miR-19) plays a critical role in cardiac development and cardiovascular disease (CVD). We examined whether change in circulating miR-19 was associated with change in CVD risk during weight loss.

METHODS

This study included 509 participants with overweight or obesity from the 24-month weight-loss diet intervention study (the POUNDS Lost trial) and with available data on circulating miR-19a-3p and miR-19b-3p at baseline and 6 months. The primary outcome for this analysis was the change in atherosclerotic CVD (ASCVD) risk at 6 and 24 months, which estimates the 10-year probability of hard ASCVD events. Secondary outcomes were the changes in ASCVD risk score components.

RESULTS

Circulating miR-19a-3p and miR-19b-3p levels significantly decreased during the initial 6-month dietary intervention period (P = 0.008, 0.0004, respectively). We found that a greater decrease in miR-19a-3p or miR-19b-3p was related to a greater reduction in ASCVD risk (β[SE] = 0.33 [0.13], P = 0.01 for miR-19a-3p; β[SE] = 0.3 [0.12], P = 0.017 for miR-19b-3p) over 6 months, independent of concurrent weight loss. Moreover, we found significant interactions between change in miR-19 and sleep disturbance on change in ASCVD risk over 24 months of intervention (P interaction = 0.01 and 0.008 for miR-19a-3p and miR-19b-3p, respectively). Participants with a greater decrease in miR-19 without sleep disturbance had a greater reduction of ASCVD risk than those with slight/moderate/great amounts of sleep disturbance. In addition, change in physical activity significantly modified the associations between change in miR-19 and change in ASCVD risk over 24 months (P interaction = 0.006 and 0.004 for miR-19a-3p and miR-19b-3p, respectively). A greater decrease in miR-19 was significantly associated with a greater reduction in ASCVD risk among participants with an increase in physical activity, while non-significant inverse associations were observed among those without an increase in physical activity.

CONCLUSIONS

In conclusion, decreased circulating miR-19 levels during dietary weight-loss interventions were related to a significant reduction in ASCVD risk, and these associations were more evident in people with no sleep disturbance or increase in physical activity.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00072995.

Predictive Utility of Irritability "In Context": Proof-of-Principle for an Early Childhood Mental Health Risk Calculator

OBJECTIVE

We provide proof-of-principle for a mental health risk calculator advancing clinical utility of the irritability construct for identification of young children at high risk for common, early onsetting syndromes.

METHOD

Data were harmonized from two longitudinal early childhood subsamples (total N = 403; 50.1% Male; 66.7% Nonwhite; Mage = 4.3 years). The independent subsamples were clinically enriched via disruptive behavior and violence (Subsample 1) and depression (Subsample 2). In longitudinal models, epidemiologic risk prediction methods for risk calculators were applied to test the utility of the transdiagnostic indicator, early childhood irritability, in the context of other developmental and social-ecological indicators to predict risk of internalizing/externalizing disorders at preadolescence (Mage = 9.9 years). Predictors were retained when they improved model discrimination (area under the receiver operating characteristic curve [AUC] and integrated discrimination index [IDI]) beyond the base demographic model.

RESULTS

Compared to the base model, the addition of early childhood irritability and adverse childhood experiences significantly improved the AUC (0.765) and IDI slope (0.192). Overall, 23% of preschoolers went on to develop a preadolescent internalizing/externalizing disorder. For preschoolers with both elevated irritability and adverse childhood experiences, the likelihood of an internalizing/externalizing disorder was 39-66%.

CONCLUSIONS

Predictive analytic tools enable personalized prediction of psychopathological risk for irritable young children, holding transformative potential for clinical translation.

Effect of Virgin Coconut Oil (VCO) on Cardiometabolic Parameters in Patients with Dyslipidemia: A Randomized, Add-on Placebo-Controlled Clinical Trial

OBJECTIVE

Statin monotherapy for dyslipidemia is limited by adverse effects and limited effectiveness in certain subgroups like metabolic syndrome. Add-on therapy with an agent with a known safety profile may improve clinical outcomes, and virgin coconut oil (VCO) may be the candidate agent for improving the cardiometabolic profile. The present study was conducted to evaluate the effect of add-on VCO with atorvastatin in dyslipidemia in adults.

METHODS

A randomized, double-blind clinical trial was conducted on 150 patients with dyslipidemia who were randomized into control and test groups. The control group received atorvastatin monotherapy, whereas the test group received add-on VCO with atorvastatin for 8 weeks. At baseline, demographic, clinical, and biochemical parameters were assessed and repeated after 8 weeks of therapy. The main outcome measures were lipid profile, cardiovascular risk indices, 10-year cardiovascular risk, body fat compositions, and thiobarbituric acid reactive substances (TBARS).

RESULTS

The increase in HDL in the test group was significantly greater than in the control group (MD: 2.76; 95%CI: 2.43-3.08; p < 0.001). The changes in the atherogenic index (p = 0.003), coronary risk index (p < 0.001), cardiovascular risk index (p = 0.001), and TBARS (p < 0.001) were significantly greater in the test group. The decrease in LDL, total cholesterol and lipoprotein(a), were significantly higher in the control group. There were no significant differences between the groups with respect to the changes in triglyceride, VLDL, and 10-year cardiovascular risk.

CONCLUSIONS

Add-on VCO (1000 mg/day) with atorvastatin (10 mg/day) can achieve a better clinical outcome in patients with dyslipidemia by increasing HDL and improving oxidative stress cardiovascular risk indices.

Familial hypercholesterolaemia in UK primary care: a Clinical Practice Research Datalink study of an under-recognised condition

BACKGROUND

Studies utilising genotyping methods report the prevalence of familial hypercholesterolaemia to be as high as one in 137 of the adult population.

AIM

To estimate the prevalence of familial hypercholesterolaemia measured by clinically coded diagnosis, associated treatments, and lipid measurements observed in UK primary care.

DESIGN AND SETTING

This was a retrospective analysis using the Clinical Practice Research Datalink (CPRD) GOLD database.

METHOD

Patients aged ≥18 years and actively registered on the index date (30 June 2018) formed the study cohort. Point prevalence of familial hypercholesterolaemia for 2018 was estimated overall and for each nation of the UK. Patients with familial hypercholesterolaemia were stratified into primary and secondary prevention groups, defined as those with/without a prior diagnosis of atherosclerotic cardiovascular disease. Prevalence estimates and extrapolations were replicated for these subgroups. Baseline demographic, lipid, and clinical characteristics for the prevalent cohort were presented.

RESULTS

In total, 4048 patients with familial hypercholesterolaemia formed the study cohort. The estimated familial hypercholesterolaemia prevalence for the UK was 16.4 per 10 000 (95% confidence interval [CI] = 16.0 to 16.9). Of these, 2646 (65.4%) patients with familial hypercholesterolaemia had a recent prescription for lipid-lowering therapy. Mean lipid levels were lower for those treated with lipid-lowering therapy compared with those untreated: 5.34 mmol/L (SD 1.50) versus 6.25 mmol/L (SD 1.55) for total cholesterol and 3.15 mmol/L (SD 1.34) versus 3.96 mmol/L (SD 1.36) for low-level density lipoprotein cholesterol.

CONCLUSION

The estimated prevalence of familial hypercholesterolaemia was one in 608 of the population, less than expected from other studies, which may indicate that familial hypercholesterolaemia is under-recognised in UK primary care. Over one-third of diagnosed patients were undertreated and many did not achieve target goals, placing them at risk of cardiovascular events.

Atherosclerotic cardiovascular disease events among adults with high predicted risk without established risk factors

Objective

Age is the strongest contributor to 10-year predicted atherosclerotic cardiovascular disease (ASCVD) risk. Some older adults have a predicted ASCVD risk ≥7.5 %, without established risk factors. We sought to compare ASCVD incidence among adults with predicted ASCVD risk ≥7.5 %, with and without established ASCVD risk factors, to adults with predicted risk <7.5 %.

Methods

We analyzed data from REasons for Geographic and Racial Differences in Stroke study participants, 45-79 years old, without ASCVD or diabetes, not taking statins and with low-density lipoprotein cholesterol 70-189 mg/dL. Participants were categorized into 3 groups based on their 10-year predicted ASCVD risk and presence of established risk factors: <7.5 %, ≥7.5 % with established risk factors and ≥7.5 % without established risk factors. Established risk factors included smoking, systolic blood pressure ≥130 mmHg or antihypertensive medication use, total cholesterol ≥200 mg/dL, or high-density lipoprotein cholesterol <50 mg/dL for women (<40 mg/dL for men). Participants were followed for ASCVD events.

Results

Among 11,115 participants, 911 incident ASCVD events occurred over a median of 11.1 years. ASCVD incidence rates were 3.6, 12.8, and 9.8 per 1,000 person-years for participants with predicted risk <7.5 %, predicted risk ≥7.5 % with established risk factors and predicted risk ≥7.5 % without established risk factors, respectively. Compared to adults with predicted risk <7.5 %, hazard ratios for incident ASCVD in participants with risk ≥7.5 % with and without established risk factors were 3.58 (95 %CI 3.03 - 4.21) and 2.72 (95 %CI 1.91-3.88), respectively.

Conclusions

Adults with a 10-year predicted ASCVD risk ≥7.5 % but without established risk factors had a high ASCVD incidence.

Emerging Trends in Atherosclerosis: Time to Address Atherosclerosis From a Younger Age

Over the past two decades, research efforts into cardiovascular disease (CVD) have uncovered findings that fundamentally challenge our understanding of CVD, particularly atherosclerosis. Atherosclerosis was primarily attributed to the well-described abnormal lipid accumulation theory, involving plaque growth with subsequent plaque hemorrhage resulting in acute vessel thrombosis that may or may not rupture. This perspective has now evolved to encompass more complex pathways, wherein the accumulation of abnormal products of oxidation and inflammation is the most likely factor mediating atherosclerotic plaque growth. Furthermore, atherosclerosis was traditionally thought of as a disease in patients aged 40 and older. However, mounting evidence has demonstrated that significant atherosclerosis and CVD events are more prevalent in younger patients than previously realized and accelerating in incidence. With this alarming trend among younger individuals, our review sought to explore why this trend may be happening and what can be done about this developing problem.

Association of cardiovascular health and educational status in a screening cohort

INTRODUCTION

The global burden of chronic diseases, including cardiovascular disease, remains a significant public health challenge. The Life's Simple 7 (LS7) score was developed as a tool to evaluate cardiovascular health behaviours and habits and identify high-risk individuals. The present study aimed to assess the distribution of LS7 scores among educational strata.

METHODS

The study population consisted of 3,383 asymptomatic individuals screened for colorectal cancer at a single centre in Austria. We split patients into lower (n = 1,055), medium (n = 1,997), and higher (n = 331) education, based on the International Standard Classification of Education (ISCED). Cox regression models were utilized to determine the association between education and mortality over a median follow-up period of 7 years.

RESULTS

Individuals with higher educational status had a significantly higher prevalence of ideal cardiovascular health metrics, as defined by the LS7 score, compared to those with medium and lower educational status: n = 94 (28%) vs. n = 347 (17%) and n = 84 (8%), respectively, (p < 0.001). In the Cox regression analysis, both medium (HR = 0.61, 95% CI: 0.43-0.84, p < 0.001) and higher educational status (HR = 0.44, 95% CI: 0.19-1.01, p = 0.06) were associated with all-cause mortality, as was the LS7.

CONCLUSION

Our findings highlight a significant association between lower educational status and poorer cardiovascular health, as assessed by LS7, which persisted even after multivariable adjustment. Additionally, both educational status and LS7 were associated with increased mortality, underscoring the significance of our results. These findings have important implications for public health, as screening and prevention strategies may need to be tailored to meet the diverse educational backgrounds of individuals, given the higher prevalence of unhealthy lifestyle behaviours among those with lower educational status.

Beyond symptoms: Unlocking the potential of coronary calcium scoring in the prevention and treatment of coronary artery disease

Coronary Artery Disease (CAD) represents a persistent global health menace, particularly prevalent in Eastern European nations. Often asymptomatic until its advanced stages, CAD can precipitate life-threatening events like myocardial infarction or stroke. While conventional risk factors provide some insight into CAD risk, their predictive accuracy is suboptimal. Amidst this, Coronary Calcium Scoring (CCS), facilitated by non-invasive computed tomography (CT), emerges as a superior diagnostic modality. By quantifying calcium deposits in coronary arteries, CCS serves as a robust indicator of atherosclerotic burden, thus refining risk stratification and guiding therapeutic interventions. Despite certain limitations, CCS stands as an instrumental tool in CAD management and in thwarting adverse cardiovascular incidents. This review delves into the pivotal role of CCS in CAD diagnosis and treatment, elucidates the involvement of calcium in atherosclerotic plaque formation, and outlines the principles and indications of utilizing CCS for predicting major cardiovascular events.

Comparative efficacy of anthropometric indices in predicting 10-year ASCVD risk: insights from NHANES data

Background

Cardiovascular diseases remain a leading cause of morbidity and mortality worldwide. Accurately predicting the 10-year risk of Atherosclerotic Cardiovascular Disease (ASCVD) is crucial for timely intervention and management. This study aimed to evaluate the predictive performance of six anthropometric indices in assessing the 10-year ASCVD risk.

Methods

Utilizing data from the National Health and Nutrition Examination Survey (NHANES) database (1999-2018), the study involved 11,863 participants after applying exclusion criteria. Six anthropometric indices-waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and waist-to-height0.5 ratio (WHT.5R)-were calculated. The 10-year ASCVD risk was assessed using the 2013 ACC/AHA guidelines & pooled cohort equations model. Participants were divided into two groups based on an ASCVD risk threshold of 7.5%. Statistical analysis included chi-square tests, odds ratios, and receiver operating characteristic (ROC) curves.

Results

The study found significant differences in baseline characteristics between participants with ASCVD risk less than 7.5% and those with a risk greater than or equal to 7.5%, stratified by gender. In both male and female groups, individuals with higher ASCVD risk exhibited higher age, waist circumference, BMI, and a higher prevalence of health-compromising behaviors. ABSI emerged as the most accurate predictor of ASCVD risk, with the highest area under the curve (AUC) values in both genders. The optimal cut-off values for ABSI was established for effective risk stratification (cut-off value = 0.08).

Conclusion

The study underscores the importance of anthropometric indices, particularly ABSI, in predicting the 10-year risk of ASCVD. These findings suggest that ABSI, along with other indices, can be instrumental in identifying individuals at higher risk for ASCVD, thereby aiding in early intervention and prevention strategies.

Major Limitations of Cardiovascular Risk Scores

Background. Epidemiological studies conducted in extensive population cohorts have led to the creation of numerous cardiovascular risk predictor models. However, these tools have certain limitations that restrict its applicability. The aim behind the following work is to summarize today's best-known limitations of cardiovascular risk assessment models through presenting the critical analyses conducted in this area, with the intention of offering practitioners a comprehensive understanding of these restrictions. Critical analyses revealed that these scales exhibit numerous limitations that could impact their performance. Most of these models evaluate cardiovascular risk based on classic risk factors and other restrictions, thereby negatively affecting their sensitivity. Scientists have made significant advancements in improving cardiovascular risk models, tailoring them to accommodate a wide range of populations and devising scales for estimating cardiovascular risks that can account for all prevailing restrictions. Better understanding these limitations could improve the cardiovascular risk stratification.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Evaluation of GPT-4 for 10-year cardiovascular risk prediction: Insights from the UK Biobank and KoGES data

Cardiovascular disease (CVD) remains a pressing global health concern. While traditional risk prediction methods such as the Framingham and American College of Cardiology/American Heart Association (ACC/AHA) risk scores have been widely used in the practice, artificial intelligence (AI), especially GPT-4, offers new opportunities. Utilizing large scale of multi-center data from 47,468 UK Biobank participants and 5,718 KoGES participants, this study quantitatively evaluated the predictive capabilities of GPT-4 in comparison with traditional models. Our results suggest that the GPT-based score showed commendably comparable performance in CVD prediction when compared to traditional models (AUROC on UKB: 0.725 for GPT-4, 0.733 for ACC/AHA, 0.728 for Framingham; KoGES: 0.664 for GPT-4, 0.674 for ACC/AHA, 0.675 for Framingham). Even with omission of certain variables, GPT-4's performance was robust, demonstrating its adaptability to data-scarce situations. In conclusion, this study emphasizes the promising role of GPT-4 in predicting CVD risks across varied ethnic datasets, pointing toward its expansive future applications in the medical practice.

Predictive value of lung function measures for cardiovascular risk: a large prospective cohort study

INTRODUCTION

Although lung function measures are associated with cardiovascular disease (CVD), the added predictive values of these measures remain unclear.

METHODS

From the UK Biobank, 308 415 participants free of CVD with spirometry parameters were included. The CVD outcomes included were defined by QRISK3, the American College of Cardiology/American Heart Association (ACC/AHA) and the European Systematic Coronary Risk Evaluation (SCORE) prediction models, respectively. Cox proportional hazard models were used to estimate the associations of lung function measures with CVD outcomes. The predictive capability was determined by the decision curve analyses.

RESULTS

Over a median follow-up of 12.5 years, 21 885 QRISK3 events, 12 843 ACC/AHA events and 2987 SCORE events were recorded. The associations of spirometry parameters with CVD outcomes were L-shaped. Restrictive and obstructive impairments were associated with adjusted HRs of 1.84 (95% CI: 1.65 to 2.06) and 1.72 (95% CI: 1.55 to 1.90) for SCORE CVD, respectively, compared with normal spirometry. Similar associations were seen for QRISK3 CVD (restrictive vs normal, adjusted HR: 1.30, 95% CI: 1.25 to 1.36; obstructive vs normal, adjusted HR: 1.20, 95% CI: 1.15 to 1.25) and ACC/AHA CVD (restrictive vs normal, adjusted HR: 1.39, 95% CI: 1.31 to 1.47; obstructive vs normal, adjusted HR: 1.26, 95% CI: 1.19 to 1.33). Using models that integrated non-linear forced expiratory volume in 1 s led to additional 10-year net benefits per 100 000 persons of 25, 43 and 5 for QRISK3 CVD at the threshold of 10%, ACC/AHA CVD at 7.5% and SCORE CVD at 5.0%, respectively.

CONCLUSION

Clinicians could consider spirometry indicators in CVD risk assessment. Cost-effectiveness studies and clinical trials are needed to put new CVD risk assessment into practice.

Integration of risk factor polygenic risk score with disease polygenic risk score for disease prediction

Polygenic risk score (PRS) is useful for capturing an individual's genetic susceptibility. However, previous studies have not fully exploited the potential of the risk factor PRS (RFPRS) for disease prediction. We explored the potential of integrating disease-related RFPRSs with disease PRS to enhance disease prediction performance. We constructed 112 RFPRSs and analyzed the association of RFPRSs with diseases to identify disease-related RFPRSs in 700 diseases, using the UK Biobank dataset. We uncovered 6157 statistically significant associations between 247 diseases and 109 RFPRSs. We estimated the disease PRSs of 70 diseases that exhibited statistically significant heritability, to generate RFDiseasemetaPRS-a combined PRS integrating RFPRSs and disease PRS-and compare the prediction performance metrics between RFDiseasemetaPRS and disease PRS. RFDiseasemetaPRS showed better performance for Nagelkerke's pseudo-R2, odds ratio (OR) per 1 SD, net reclassification improvement (NRI) values and difference of R2 considered by variance of R2 in 31 out of 70 diseases. Additionally, we assessed risk classification between two models by examining OR between the top 10% and remaining 90% individuals for the 31 diseases; RFDiseasemetaPRS exhibited better R2, NRI and OR than disease PRS. These findings highlight the importance of utilizing RFDiseasemetaPRS, which can provide personalized healthcare and tailored prevention strategies.

Trajectories of Sleep Over Midlife and Incident Cardiovascular Disease Events in the Study of Women's Health Across the Nation

BACKGROUND

Up to 50% of women report sleep problems in midlife, and cardiovascular disease (CVD) is the leading cause of death in women. How chronic poor sleep exposure over decades of midlife is related to CVD risk in women is poorly understood. We tested whether trajectories of insomnia symptoms or sleep duration over midlife were related to subsequent CVD events among SWAN (Study of Women's Health Across the Nation) participants, whose sleep was assessed up to 16 times over 22 years.

METHODS

At baseline, SWAN participants (n=2964) were 42 to 52 years of age, premenopausal or early perimenopausal, not using hormone therapy, and free of CVD. They completed up to 16 visits, including questionnaires assessing insomnia symptoms (trouble falling asleep, waking up several times a night, or waking earlier than planned ≥3 times/week classified as insomnia), typical daily sleep duration, vasomotor symptoms, and depressive symptoms; anthropometric measurements; phlebotomy; and CVD event ascertainment (ie, fatal or nonfatal myocardial infarction, stroke, heart failure, revascularization). Sleep trajectories (ie, insomnia, sleep duration) were determined by means of group-based trajectory modeling. Sleep trajectories were tested in relation to CVD in Cox proportional hazards models (multivariable models: site, age, race and ethnicity, education, CVD risk factors averaged over visits; additional covariates: vasomotor symptoms, snoring, depression).

RESULTS

Four trajectories of insomnia symptoms emerged: low insomnia symptoms (n=1142 [39% of women]), moderate insomnia symptoms decreasing over time (n=564 [19%]), low insomnia symptoms increasing over time (n=590 [20%]), and high insomnia symptoms that persisted (n=668 [23%]). Women with persistently high insomnia symptoms had higher CVD risk (hazard ratio, 1.71 [95% CI, 1.19, 2.46], P=0.004, versus low insomnia; multivariable). Three trajectories of sleep duration emerged: persistently short (~5 hours: n=363 [14%]), moderate (~6 hours: n=1394 [55%]), and moderate to long (~8 hours: n=760 [30%]). Women with persistent short sleep had marginally higher CVD risk (hazard ratio, 1.51 [95% CI, 0.98, 2.33], P=0.06, versus moderate; multivariable). Women who had both persistent high insomnia and short sleep had significantly elevated CVD risk (hazard ratio, 1.75 [95% CI, 1.03, 2.98], P=0.04, versus low insomnia and moderate or moderate to long sleep duration; multivariable). Relations of insomnia to CVD persisted when adjusting for vasomotor symptoms, snoring, or depression.

CONCLUSIONS

Insomnia symptoms, when persistent over midlife or occurring with short sleep, are associated with higher CVD risk among women.

StepTest4all: Improving the Prediction of Cardiovascular Capacity Assessment in Young Adults

Cardiovascular capacity, expressed as maximal oxygen uptake (VO2max), is a strong predictor of health and fitness and is considered a key measure of physiological function in the healthy adult population. The aim of this study was to investigate the influence of the physical activity levels (PAlevel) of participants in the StepTest4all (validated protocol for the estimation of VO2max in adults). The sample consisted of 69 participants, including 27 women (age 21.7 ± 3.6 years; body mass = 63.5 ± 14.8 kg; height = 1.64 ± 0.06 m; body mass index = 23.7 ± 5.3 kg/m2) and 42 men (aged 21.7 ± 3.4 years; body mass = 72.0 ± 7.3 kg; height = 1.77 ± 0.07 m; body mass index = 23.1 ± 2.1 kg/m2). The participants were assigned to one of the two groups: (i) the VO2max prediction group and (ii) the prediction model validation group. In the multiple linear regression, the following predictors of VO2max remained significant: sex (p < 0.001), physical activity level (p = 0.014), and HRR60 (p = 0.020). The prediction equation (R2 = 74.0%, SEE = 4.78) showed a close and strong relationship between the measurements and can be expressed as follows: VO2max = 17.105 + 0.260·(HRR60) + 8.563·(sex) + 4.097·(PAlevel), in which HRR60 is the magnitude of the HR decrease (bpm) in one minute immediately after stopping the step, and sex: men = 1, women = 0, and PAlevel is level 1 (low), level 2 (moderate), and level 3 (high). The StepTest4all was shown to be a suitable method for estimating cardiovascular capacity, expressed as VO2max, in young adults. Retaining PAlevel as a significant predictor allows us to better individualize the participants' VO2max.

Development and Validation of the American Heart Association's PREVENT Equations

BACKGROUND

Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD.

METHODS

The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets.

RESULTS

Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01).

CONCLUSIONS

PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

Tenecteplase versus alteplase in treatment of acute ST-segment elevation myocardial infarction: A randomized non-inferiority trial

BACKGROUND

A phase II trial on recombinant human tenecteplase tissue-type plasminogen activator (rhTNK-tPA) has previously shown its preliminary efficacy in ST elevation myocardial infarction (STEMI) patients. This study was designed as a pivotal postmarketing trial to compare its efficacy and safety with rrecombinant human tissue-type plasminogen activator alteplase (rt-PA) in Chinese patients with STEMI.

METHODS

In this multicenter, randomized, open-label, non-inferiority trial, patients with acute STEMI were randomly assigned (1:1) to receive an intravenous bolus of 16 mg rhTNK-tPA or an intravenous bolus of 8 mg rt-PA followed by an infusion of 42 mg in 90 min. The primary endpoint was recanalization defined by thrombolysis in myocardial infarction (TIMI) flow grade 2 or 3. The secondary endpoint was clinically justified recanalization. Other endpoints included 30-day major adverse cardiovascular and cerebrovascular events (MACCEs) and safety endpoints.

RESULTS

From July 2016 to September 2019, 767 eligible patients were randomly assigned to receive rhTNK-tPA ( n = 384) or rt-PA ( n = 383). Among them, 369 patients had coronary angiography data on TIMI flow, and 711 patients had data on clinically justified recanalization. Both used a -15% difference as the non-inferiority efficacy margin. In comparison to rt-PA, both the proportion of patients with TIMI grade 2 or 3 flow (78.3% [148/189] vs. 81.7% [147/180]; differences: -3.4%; 95% confidence interval [CI]: -11.5%, 4.8%) and clinically justified recanalization (85.4% [305/357] vs. 85.9% [304/354]; difference: -0.5%; 95% CI: -5.6%, 4.7%) in the rhTNK-tPA group were non-inferior. The occurrence of 30-day MACCEs (10.2% [39/384] vs. 11.0% [42/383]; hazard ratio: 0.96; 95% CI: 0.61, 1.50) did not differ significantly between groups. No safety outcomes significantly differed between groups.

CONCLUSION

rhTNK-tPA was non-inferior to rt-PA in the effect of improving recanalization of the infarct-related artery, a validated surrogate of clinical outcomes, among Chinese patients with acute STEMI.

TRIAL REGISTRATION

www.ClinicalTrials.gov (No. NCT02835534).

Tracking of apolipoprotein B levels measured in childhood and adolescence: systematic review and meta-analysis

To quantify the tracking of apolipoprotein B (apoB) levels from childhood and adolescence and compare the tracking of apoB with low-density lipoprotein (LDL) cholesterol, a systematic search of MEDLINE, Embase, Web of Science, and Google Scholar was performed in October 2023 (PROSPERO protocol: CRD42022298663). Cohort studies that measured tracking of apoB from childhood/adolescence (< 19 years) with a minimum follow-up of 1 year, using tracking estimates such as correlation coefficients or tracking coefficients, were eligible. Pooled correlations were estimated using random-effects meta-analysis. Risk of bias was assessed with a review-specific tool. Ten studies of eight unique cohorts involving 4677 participants met the inclusion criteria. Tracking of apoB was observed (pooled r = 0.63; 95% confidence interval [CI] = 0.53-0.71; I2 = 96%) with no significant sources of heterogeneity identified. Data from five cohorts with tracking data for both lipids showed the degree of tracking was similar for apoB (pooled r = 0.59; 95% CI = 0.55-0.63) and LDL cholesterol (pooled r = 0.58; 95% CI = 0.47-0.68). Study risk of bias was moderate, mostly due to attrition and insufficient reporting.

CONCLUSION

ApoB levels track strongly from childhood, but do not surpass LDL cholesterol in this regard. While there is strong evidence that apoB is more effective at predicting ASCVD risk than LDL cholesterol in adults, there is currently insufficient evidence to support its increased utility in pediatric settings. This also applies to tracking data, where more comprehensive data are required.

WHAT IS KNOWN

• Apolipoprotein B is a known cause of atherosclerotic cardiovascular disease. • Apolipoprotein B levels are not typically measured in pediatric settings, where low-density lipoprotein cholesterol remains the primary lipid screening measure.

WHAT IS NEW

• This meta-analysis of 10 studies showed apolipoprotein B levels tracked strongly from childhood but did not exceed low-density lipoprotein cholesterol in this regard. • More comprehensive tracking data are needed to provide sufficient evidence for increased utility of apolipoprotein B in pediatric settings.

Cumulative Diastolic Blood Pressure Burden in Normal Systolic Blood Pressure and Cardiovascular Disease

BACKGROUND

The clinical significance of isolated diastolic hypertension defined by the 2017 American College of Cardiology/American Heart Association blood pressure (BP) guidelines remains inconsistent. We examined whether long-term diastolic burden predicts the first major adverse cardiovascular event in participants with sustained and untreated normal systolic BP.

METHODS

The Mass General Brigham Biobank is a New England health care-based cohort recruited between 2010 and 2021. A total of 15 979 participants aged 18 to 64 years and without prior cardiovascular disease, antihypertensives, or high systolic BP were studied. The cumulative diastolic burden was determined as the area under the curve for diastolic BP (DBP) ≥80 mm Hg over 5 years before enrollment. Major adverse cardiovascular event was defined as a composite of first incident ischemic heart disease, stroke, heart failure, or all-cause death.

RESULTS

Of the 15 979 participants, mean (SD) age at enrollment was 47.6 (14.3) years, 11 950 (74.8%) were women, and the mean (SD) systolic BP and DBP were 118.0 (12.9) and 72.2 (9.3) mm Hg, respectively. Over a median (interquartile range) follow-up of 3.5 (1.8-5.4) years, 2467 (15.4%) major adverse cardiovascular events occurred. Using Cox proportional hazards regression, each SD increase in cumulative DBP was independently associated with a hazard ratio (95% CI) of 1.06 (1.02-1.10) without effect modification by sex (P=0.65), age (P=0.46), or race/ethnicity (P=0.24). In addition to traditional risk factors, cumulative DBP modestly improved the discrimination C index (95% CI) from 0.74 (0.72-0.75) to 0.75 (0.74-0.76; likelihood ratio test, P=0.037).

CONCLUSIONS

Among individuals with normal systolic BP, cumulative DBP may augment cardiovascular disease risk stratification beyond a single DBP measure and traditional risk factors.

New horizons in frailty identification via electronic frailty indices: early implementation lessons from experiences in England and the United States

Frailty represents an integrative prognostic marker of risk that associates with a myriad of age-related adverse outcomes in older adults. As a concept, frailty can help to target scarce resources and identify subgroups of vulnerable older adults that may benefit from interventions or changes in medical management, such as pursing less aggressive glycaemic targets for frail older adults with diabetes. In practice, however, there are several operational challenges to implementing frailty screening outside the confines of geriatric medicine. Electronic frailty indices (eFIs) based on the theory of deficit accumulation, derived from routine data housed in the electronic health record, have emerged as a rapid, feasible and valid approach to screen for frailty at scale. The goal of this paper is to describe the early experience of three diverse groups in developing, implementing and adopting eFIs (The English National Health Service, US Department of Veterans Affairs and Atrium Health-Wake Forest Baptist). These groups span different countries and organisational complexity, using eFIs for both research and clinical care, and represent different levels of progress with clinical implementation. Using an implementation science framework, we describe common elements of successful implementation in these settings and set an agenda for future research and expansion of eFI-informed initiatives.

Effect of repeatedly applied cold water immersion on subclinical atherosclerosis, inflammation, fat accumulation and lipid profile parameters of volunteers

Significant acute cardiovascular, metabolic, and endocrine changes have been traced to short-lasting cold water immersion (CWI); however, the long-term impact of recurrent CWI on atherogenesis, lipid parameters, and fat distribution has not yet been studied. The goal of this study was to investigate the alleged protective effect. A total of 35 healthy volunteers were monitored for a period of 5 months during which the CWI was performed under standardized conditions (three times per week for 7-10 min, without neoprene equipment). Volunteers with measured weight or muscle mass increases of more than 5% were ineligible. An analogous control group (N = 30) was included. At the onset and completion of the study, blood samples were obtained, and clinical assessments took place. PCSK9 and hsCRP levels were measured together with other lipid-related and non-lipid-related indicators. Carotid intima-media thickness test (cIMT) and echo-tracking for the identification of arterial stiffness (PWV, AI, and β) were used to identify early vascular alterations. Hepatorenal index (HRI) calculations served to quantify liver steatosis, while changes in subcutaneous and visceral fat thickness were used to quantify fat distribution. The given protocol was successfully completed by 28 volunteers. Long-term repeated CWI resulted in a significant decline in cIMT (p = 0.0001), AI (p = 0.0002), Beta (p = 0.0001), and PWV (p = 0.0001). PCSK9 (p = 0.01) and hsCRP (p = 0.01) showed a significant decrease when compared to initial values. In comparison to the starting values, liver fat accumulation decreased by 11% on average (HRI p = 0.001). LDL, TC, TG, and VLDL levels all significantly decreased as well. We suggest that repeated CWI may have beneficial impact on lipid, non-lipid, and lipid-related indices, as well as atherogenesis and liver fat storage.

The potential interaction between chemosensitivity and the development of cardiovascular disease in obstructive sleep apnea

OBJECTIVES

Chemosensitivity is an essential part of the pathophysiological mechanisms of obstructive sleep apnea (OSA). Not only does OSA have a certain relationship with the comorbidity of cardiovascular disease (CVD) but also chemosensitivity plays a crucial role in the development of CVD. This study aims to investigate the potential interaction between chemosensitivity and the development of CVD in OSA.

METHODS

A total of 169 participants with suspected OSA were included. Data were gathered on the parameters of polysomnography and baseline clinical features. Peripheral chemosensitivity was evaluated by employing the rebreathing test. The lifetime CVD risk was computed using the China-PAR (Prediction for atherosclerotic CVD Risk in China) risk equation.

RESULTS

After controlling for covariates, participants with chemosensitivity levels in the second and fifth quantiles tended to hold an increased proportion of high lifetime CVD risk (OR 10.90, 95%CI [2.81-42.28]; OR 6.78, 95%CI [1.70-27.05], respectively). The diagnosis of OSA would significantly increase the 10-year and lifetime CVD risks in participants with low chemosensitivity, while no such differences were found in participants with high chemosensitivity.

CONCLUSION

Higher lifetime CVD risk was associated with participants who had greater peripheral chemosensitivity. In terms of the CVD outcomes, adult patients with a relatively low level of chemosensitivity may be primarily related to their diagnosis of OSA, whereas adult patients with a relatively high level of chemosensitivity may be more strongly associated with their elevated levels of chemosensitivity rather than OSA.

Performance of the pooled cohort equations in cancer survivors: the Atherosclerosis Risk in Communities study

BACKGROUND

Cancer survivors may have elevated atherosclerotic cardiovascular disease (ASCVD) risk. Therefore, we tested how accurately the American College of Cardiology/American Heart Association 2013 pooled cohort equations (PCEs) predict 10-year ASCVD risk in cancer survivors.

OBJECTIVES

To estimate the calibration and discrimination of the PCEs in cancer survivors compared to non-cancer participants in the Atherosclerosis Risk in Communities (ARIC) study.

METHODS

We evaluated the PCEs' performance among 1244 cancer survivors and 3849 cancer-free participants who were free of ASCVD at the start of follow-up. Each cancer survivor was incidence-density matched with up to five controls by age, race, sex, and study center. Follow-up began at the first study visit at least 1 year after the diagnosis date of the cancer survivor and finished at the ASCVD event, death, or end of follow-up. Calibration and discrimination were assessed and compared between cancer survivors and cancer-free participants.

RESULTS

Cancer survivors had higher PCE-predicted risk, at 26.1%, compared with 23.1% for cancer-free participants. There were 110 ASCVD events in cancer survivors and 332 ASCVD events in cancer-free participants. The PCEs overestimated ASCVD risk in cancer survivors and cancer-free participants by 45.6% and 47.4%, respectively, with poor discrimination in both groups (C-statistic for cancer survivors = 0.623; for cancer-free participants, C = 0.671).

CONCLUSIONS

The PCEs overestimated ASCVD risk in all participants. The performance of the PCEs was similar in cancer survivors and cancer-free participants.

IMPLICATIONS FOR CANCER SURVIVORS

Our findings suggest that ASCVD risk prediction tools tailored to survivors of adult cancers may not be needed.

The Association of Early Menopause with Increased Risk of Acute Myocardial Infarction: The INTERHEART China Study

Background and Aim: Little is known about whether early menopause in Chinese ethnicity is associated with acute myocardial infarction (AMI). We aimed to determine whether self-reported early menopause (either surgical or natural menopause at an age <50 year) was associated with first AMI in Chinese women. Methods: The study population was from the INTERHEART China Study, part of the INTERHEART global study. INTERHEART global study was a standardized case-control study that was designed to evaluate the risk factors for first AMI among 52 countries. Data for demographic factors, education, income, and cardiovascular risk factors were obtained by structured questionnaires. A standard set of questions that inquired about menstrual history was included in the interview. Results: Of the 1,771 Chinese women, 1,563 (88.3%) reported either natural or surgical menopause. In univariate logistic regression model, women with early menopause had higher risk of AMI (odds ratio [OR]: 1.51; 95% confidence interval [CI]: 1.23-1.87). After controlling for age, birth control measures, type of menopause, and other traditional risk factors (including waist/hip ratio, lifestyle factors, history of hypertension and diabetes, psychosocial factors, and apolipoprotein B [ApoB]/A1 [ApoA1]), the risk for AMI remained (OR: 1.36; 95% CI: 1.03-1.79). The population attributable risk for AMI in women with early menopause at <50 years was 10.1% (95% CI: 4.0-20.0) compared with women who had menopause at ≥50 years. Conclusion: Early menopause is associated with increased risk of AMI in Chinese women, independent of other traditional coronary heart disease risk factors.

The implications of competing risks and direct treatment disutility in cardiovascular disease and osteoporotic fracture: risk prediction and cost effectiveness analysis

Background

Clinical guidelines commonly recommend preventative treatments for people above a risk threshold. Therefore, decision-makers must have faith in risk prediction tools and model-based cost-effectiveness analyses for people at different levels of risk. Two problems that arise are inadequate handling of competing risks of death and failing to account for direct treatment disutility (i.e. the hassle of taking treatments). We explored these issues using two case studies: primary prevention of cardiovascular disease using statins and osteoporotic fracture using bisphosphonates.

Objectives

Externally validate three risk prediction tools [QRISK®3, QRISK®-Lifetime, QFracture-2012 (ClinRisk Ltd, Leeds, UK)]; derive and internally validate new risk prediction tools for cardiovascular disease [competing mortality risk model with Charlson Comorbidity Index (CRISK-CCI)] and fracture (CFracture), accounting for competing-cause death; quantify direct treatment disutility for statins and bisphosphonates; and examine the effect of competing risks and direct treatment disutility on the cost-effectiveness of preventative treatments.

Design, participants, main outcome measures, data sources

Discrimination and calibration of risk prediction models (Clinical Practice Research Datalink participants: aged 25-84 years for cardiovascular disease and aged 30-99 years for fractures); direct treatment disutility was elicited in online stated-preference surveys (people with/people without experience of statins/bisphosphonates); costs and quality-adjusted life-years were determined from decision-analytic modelling (updated models used in National Institute for Health and Care Excellence decision-making).

Results

CRISK-CCI has excellent discrimination, similar to that of QRISK3 (Harrell's c = 0.864 vs. 0.865, respectively, for women; and 0.819 vs. 0.834, respectively, for men). CRISK-CCI has systematically better calibration, although both models overpredict in high-risk subgroups. People recommended for treatment (10-year risk of ≥ 10%) are younger when using QRISK-Lifetime than when using QRISK3, and have fewer observed events in a 10-year follow-up (4.0% vs. 11.9%, respectively, for women; and 4.3% vs. 10.8%, respectively, for men). QFracture-2012 underpredicts fractures, owing to under-ascertainment of events in its derivation. However, there is major overprediction among people aged 85-99 years and/or with multiple long-term conditions. CFracture is better calibrated, although it also overpredicts among older people. In a time trade-off exercise (n = 879), statins exhibited direct treatment disutility of 0.034; for bisphosphonates, it was greater, at 0.067. Inconvenience also influenced preferences in best-worst scaling (n = 631). Updated cost-effectiveness analysis generates more quality-adjusted life-years among people with below-average cardiovascular risk and fewer among people with above-average risk. If people experience disutility when taking statins, the cardiovascular risk threshold at which benefits outweigh harms rises with age (≥ 8% 10-year risk at 40 years of age; ≥ 38% 10-year risk at 80 years of age). Assuming that everyone experiences population-average direct treatment disutility with oral bisphosphonates, treatment is net harmful at all levels of risk.

Limitations

Treating data as missing at random is a strong assumption in risk prediction model derivation. Disentangling the effect of statins from secular trends in cardiovascular disease in the previous two decades is challenging. Validating lifetime risk prediction is impossible without using very historical data. Respondents to our stated-preference survey may not be representative of the population. There is no consensus on which direct treatment disutilities should be used for cost-effectiveness analyses. Not all the inputs to the cost-effectiveness models could be updated.

Conclusions

Ignoring competing mortality in risk prediction overestimates the risk of cardiovascular events and fracture, especially among older people and those with multimorbidity. Adjustment for competing risk does not meaningfully alter cost-effectiveness of these preventative interventions, but direct treatment disutility is measurable and has the potential to alter the balance of benefits and harms. We argue that this is best addressed in individual-level shared decision-making.

Study registration

This study is registered as PROSPERO CRD42021249959.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 15/12/22) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information.

AI-integrated ocular imaging for predicting cardiovascular disease: advancements and future outlook

Cardiovascular disease (CVD) remains the leading cause of death worldwide. Assessing of CVD risk plays an essential role in identifying individuals at higher risk and enables the implementation of targeted intervention strategies, leading to improved CVD prevalence reduction and patient survival rates. The ocular vasculature, particularly the retinal vasculature, has emerged as a potential means for CVD risk stratification due to its anatomical similarities and physiological characteristics shared with other vital organs, such as the brain and heart. The integration of artificial intelligence (AI) into ocular imaging has the potential to overcome limitations associated with traditional semi-automated image analysis, including inefficiency and manual measurement errors. Furthermore, AI techniques may uncover novel and subtle features that contribute to the identification of ocular biomarkers associated with CVD. This review provides a comprehensive overview of advancements made in AI-based ocular image analysis for predicting CVD, including the prediction of CVD risk factors, the replacement of traditional CVD biomarkers (e.g., CT-scan measured coronary artery calcium score), and the prediction of symptomatic CVD events. The review covers a range of ocular imaging modalities, including colour fundus photography, optical coherence tomography, and optical coherence tomography angiography, and other types of images like external eye images. Additionally, the review addresses the current limitations of AI research in this field and discusses the challenges associated with translating AI algorithms into clinical practice.

Association of obesity with cardiovascular disease in the absence of traditional risk factors

BACKGROUND

The association between obesity and cardiovascular disease (CVD) in people without traditional CVD risk factors is unclear. This study aimed to investigate the association of obesity with CVD and its subtypes in people without traditional CVD risk factors.

METHODS

Based on the Kailuan cohort study, the included participants were divided into different groups according to levels of body mass index (BMI) and waist height ratio (WHtR), respectively. Multivariate Cox proportional hazard models were used to evaluate the associations.

RESULTS

This study included 31,955 participants [men 63.99%; mean age (48.14 ± 3.33) years]. During a median follow-up period of 12.97 (interquartile range: 12.68-13.17) years, 1298 cases of CVD were observed. Compared with the normal BMI group, the hazard ratios (HRs) for CVD, stroke, and myocardial infarction (MI) in the BMI obese group were 1.31 (95% confidence interval [CI] 1.11-1.55), 1.21 (95%CI 1.01-1.46), 1.62 (95%CI 1.13-2.33), respectively. Compared with the WHtR non-obese group, the HRs for CVD, stroke, and MI in the obese group were 1.25(95%CI 1.11-1.41), 1.18 (95%CI 1.03-1.34), 1.57 (95%CI 1.18-2.09), respectively. There was an interaction between age and WHtR (P for interaction was 0.043). The association between WHtR and CVD was stronger in people under 60 years old, with a HR of 1.44 (95%CI 1.24-1.67).

CONCLUSION

We found that obesity increased the risk of CVD in people without traditional CVD risk factors. The association of WHtR with CVD was stronger in people under 60 years old.

Primary prevention of cardiovascular disease in women

Ischemic heart disease is the primary cause of cardiovascular disease (CVD) mortality in both men and women. Strategies targeting traditional modifiable risk factors are essential - including hypertension, smoking, dyslipidemia and diabetes mellitus - particularly for atherosclerosis, but additionally for stroke, heart failure and some arrhythmias. However, challenges related to education, screening and equitable access to effective preventative therapies persist, and are particularly problematic for women around the globe and those from lower socioeconomic groups. The association of female-specific risk factors (e.g. premature menopause, gestational hypertension, small for gestational age births) with CVD provides a potential window for targeted prevention strategies. However, further evidence for specific effective screening and interventions is urgently required. In addition to population-level factors involved in increasing the risk of suffering a CVD event, efforts are leveraging the enormous potential of blood-based 'omics', improved imaging biomarkers and increasingly complex bioinformatic analytic approaches to strive toward more personalized early disease detection and personalized preventative therapies. These novel tactics may be particularly relevant for women in whom traditional risk factors perform poorly. Here we discuss established and emerging approaches for improving risk assessment, early disease detection and effective preventative strategies to reduce the mammoth burden of CVD in women.

High-density lipoprotein functionality, cardiovascular health, and patterns of alcohol consumption: new insights and future perspectives

PURPOSE OF REVIEW

Cardiovascular diseases (CVD) pose a significant public health challenge, contributing to 422 million disability-adjusted life years in 2021. The role of high-density lipoproteins (HDL) and alcohol consumption, one of their major modifiable determinants, remains controversial. The objective of this review is to provide a comprehensive narrative overview of HDL functionality and its predictive value for CVD in relation to patterns of alcohol consumption.

RECENT FINDINGS

HDL phenotypes beyond HDL-cholesterol (HDL-c) such as distribution of HDL subspecies, HDL particle abundance, and reverse cholesterol transport capacity are promising indicators of atherosclerotic CVD risk. Low-to-moderate alcohol consumption seems to improve HDL functionality and reduce the incidence of CVD among primarily middle-aged men and postmenopausal women. Advancements in our understanding of HDL biogenesis, structure, and function hold promise for improving HDL-related measures and their predictive value for cardiovascular health.

SUMMARY

Low-to-moderate alcohol consumption appears to not only increase HDL-c concentration found in the HDL fraction of plasma but also enhance HDL functionality, providing insights into the underlying mechanisms linking alcohol exposure and cardiovascular health benefits. However, rigorous, well designed intervention trials of alcohol consumption on hard cardiovascular outcomes are needed to identify robust causal associations of HDL phenotypes and alcohol consumption with cardiovascular risk.

Metabolic disease and the liver: A review

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common liver disease worldwide, with an estimated prevalence of 31% in Latin America. The presence of metabolic comorbidities coexisting with liver disease varies substantially among populations. It is acknowledged that obesity is boosting the type 2 diabetes mellitus "epidemic," and both conditions are significant contributors to the increasing number of patients with MASLD. Non-alcoholic steatohepatitis represents a condition of chronic liver inflammation and is considered the most severe form of MASLD. MASLD diagnosis is based on the presence of steatosis, noninvasive scores and altered liver tests. Noninvasive scores of liver fibrosis, such as serum biomarkers, which should be used in primary care to rule out advanced fibrosis, are simple, inexpensive, and widely available. Currently, guidelines from international hepatology societies recommend using noninvasive strategies to simplify case finding and management of high-risk patients with MASLD in clinical practice. Unfortunately, there is no definite pharmacological treatment for the condition. Creating public health policies to treat patients with risk factors for MASLD prevention is essential.

A Comparative Study on the Quality of Life of Survivors of Stroke and Acute Myocardial Infarction

BACKGROUND

Worldwide, cardiovascular diseases, particularly acute myocardial infarction and strokes, lead to significant fatalities. Survivors often experience profound impacts on various aspects of their lives, making the assessment of their Quality of Life crucial for understanding their condition and adaptation to the illness.

METHODS

A community-based, descriptive cross-sectional study was conducted to compare how survivors of stroke and acute myocardial infarction perceive their Quality of Life. The Portuguese version of the World Health Organization Quality of life instrument was administered to 204 acute myocardial infarction and stroke survivors. Clinical and sociodemographic variables were also compared.

RESULTS

Statistically significant differences (p < 0.05) were noted in overall, physical, and psychological aspects of Quality of Life between the two groups, with stroke survivors consistently showing lower values in these dimensions.

CONCLUSIONS

The Quality-of-Life perception of stroke and acute myocardial infarction survivors may be affected by several sociodemographic and clinical factors, and the results support the idea that the vascular event conditions the person's Quality of Life, particularly in variables related to the person's physical condition, functionality, and autonomy.

Does Elevated High-Density Lipoprotein Cholesterol Protect Against Cardiovascular Disease?

High-density lipoprotein (HDL) contributes to reverse cholesterol transport, which is 1 of the main explanations for the described inverse association between HDL-cholesterol (HDL-C) and atherosclerotic cardiovascular disease (ASCVD) risk. However, efforts to therapeutically raise HDL-C levels with niacin, fibrates, or cholesteryl ester transfer protein inhibitors have not demonstrated a reduction in ASCVD events when compared with placebo among individuals treated with statins. Furthermore, mendelian randomization studies suggest that HDL-C is unlikely to be a direct biologic variable impacting ASCVD risk. More recently, observations from well-conducted epidemiologic studies have indicated a nonlinear U-shaped relationship between HDL-C and subclinical atherosclerosis, and that very high HDL-C (≥80 mg/dL in men, ≥100 mg/dL in women) is paradoxically associated with higher all-cause and ASCVD-related mortality. These observations suggest that HDL-C is not a universal protective factor for atherosclerosis. Thus, there are several opportunities for reframing the contribution of HDL-C to ASCVD risk and related clinical calculators. Here, we examine our growing understanding of HDL-C and its role in ASCVD risk assessment, treatment, and prevention. We discuss the biological functions of HDL-C and its normative values in relation to demographics and lifestyle markers. We then summarize original studies that observed a protective association between HDL-C and ASCVD risk and more recent evidence indicating an elevated ASCVD risk at very high HDL-C levels. Through this process, we advance the discussion regarding the future role of HDL-C in ASCVD risk assessment and identify knowledge gaps pertaining to the precise role of HDL-C in atherosclerosis and clinical ASCVD.

A machine learning-based prediction model for postoperative delirium in cardiac valve surgery using electronic health records

BACKGROUND

Previous models for predicting delirium after cardiac surgery remained inadequate. This study aimed to develop and validate a machine learning-based prediction model for postoperative delirium (POD) in cardiac valve surgery patients.

METHODS

The electronic medical information of the cardiac surgical intensive care unit (CSICU) was extracted from a tertiary and major referral hospital in southern China over 1 year, from June 2019 to June 2020. A total of 507 patients admitted to the CSICU after cardiac valve surgery were included in this study. Seven classical machine learning algorithms (Random Forest Classifier, Logistic Regression, Support Vector Machine Classifier, K-nearest Neighbors Classifier, Gaussian Naive Bayes, Gradient Boosting Decision Tree, and Perceptron.) were used to develop delirium prediction models under full (q = 31) and selected (q = 19) feature sets, respectively.

RESULT

The Random Forest classifier performs exceptionally well in both feature datasets, with an Area Under the Curve (AUC) of 0.92 for the full feature dataset and an AUC of 0.86 for the selected feature dataset. Additionally, it achieves a relatively lower Expected Calibration Error (ECE) and the highest Average Precision (AP), with an AP of 0.80 for the full feature dataset and an AP of 0.73 for the selected feature dataset. To further evaluate the best-performing Random Forest classifier, SHAP (Shapley Additive Explanations) was used, and the importance matrix plot, scatter plots, and summary plots were generated.

CONCLUSIONS

We established machine learning-based prediction models to predict POD in patients undergoing cardiac valve surgery. The random forest model has the best predictive performance in prediction and can help improve the prognosis of patients with POD.

Influence of Socioeconomic Status on the Presence of Obstructive Coronary Artery Disease and Cardiovascular Outcomes in Patients Undergoing Invasive Coronary Angiography

This retrospective study investigated the impact of socioeconomic status (SES) on patients at high risk of cardiovascular disease, focusing on obstructive coronary artery disease (CAD) presence and long-term cardiovascular outcomes in individuals undergoing invasive coronary angiography (ICA). Analyzing data from 9530 patients categorized by health insurance type (medical aid beneficiaries (MABs) as the low SES group; national health insurance beneficiaries (NHIBs) as the high SES group), this research explores the relationship between SES and outcomes. Despite a higher prevalence of cardiovascular risk factors, the MAB group exhibited similar rates of obstructive CAD compared to the NHIB group. However, over a median 3.5-year follow-up, the MAB group experienced a higher incidence of composite cardiovascular events, including cardiac death, acute myocardial infarction, coronary revascularization, and ischemic stroke, compared with the NHIB group (20.2% vs. 16.2%, p < 0.001). Multivariable Cox regression analysis, adjusting for potential confounders, revealed independently worse clinical outcomes for the MAB group (adjusted odds ratio 1.28; 95% confidence interval 1.07-1.54; p = 0.006). Despite comparable CAD rates, this study underscores the fact that individuals with low SES encounter an elevated risk of composite cardiovascular events, emphasizing the association between socioeconomic disadvantage and heightened susceptibility to cardiovascular disease, even among those already at high risk.

Joint Association of Polygenic Risk and Social Determinants of Health with Coronary Heart Disease in the United States

Background

The joint effects of polygenic risk and social determinants of health (SDOH) on coronary heart disease (CHD) in the United States are unknown.

Methods

In 67,256 All of Us (AoU) participants with available SDOH data, we ascertained self-reported race/ethnicity and calculated a polygenic risk score for CHD (PRS CHD ). We used 90 SDOH survey questions to develop an SDOH score for CHD (SDOH CHD ). We assessed the distribution of SDOH CHD across self-reported races and US states. We tested the joint association of SDOH CHD and PRS CHD with CHD in regression models that included clinical risk factors.

Results

SDOH CHD was highest in self-reported black and Hispanic people. Self-reporting as black was associated with higher odds of CHD but not after adjustment for SDOH CHD . Median SDOH CHD values varied by US state and were associated with heart disease mortality. A 1-SD increase in SDOH CHD was associated with CHD (OR=1.36; 95% CI, 1.29 to 1.46) and incident CHD (HR=1.73; 95% CI, 1.27 to 2.35) in models that included PRS CHD and clinical risk factors. Among people in the top 20% of PRS CHD , CHD prevalence was 4.8% and 7.8% in the bottom and top 20% of SDOH CHD , respectively.

Conclusions

Increased odds of CHD in self-reported black people are likely due to higher SDOH burden. SDOH and PRS were independently associated with CHD in the US. Our findings emphasize the need to consider both PRS and SDOH for equitable disease risk assessment.

Machine learning-based prediction of composite risk of cardiovascular events in patients with stable angina pectoris combined with coronary heart disease: development and validation of a clinical prediction model for Chinese patients

Objective: To develop a risk score model for the occurrence of composite cardiovascular events (CVE) in patients with stable angina pectoris (SA) combined with coronary heart disease (CHD) by comparing the modeling effects of various machine learning (ML) algorithms. Methods: In this prospective study, 690 patients with SA combined with CHD attending the Department of Integrative Cardiology, China-Japan Friendship Hospital, from October 2020 to October 2021 were included. The data set was randomly divided into a training group and a testing group in a 7:3 ratio in the per-protocol set (PPS). Model variables were screened using the least absolute shrinkage selection operator (LASSO) regression, univariate analysis, and multifactor logistic regression. Then, nine ML algorithms are integrated to build the model and compare the model effects. Individualized risk assessment was performed using the SHapley Additive exPlanation (SHAP) and nomograms, respectively. The model discrimination was evaluated by receiver operating characteristic curve (ROC), the calibration ability of the model was evaluated by calibration plot, and the clinical applicability of the model was evaluated by decision curve analysis (DCA). This study was approved by the Clinical Research Ethics Committee of China-Japan Friendship Hospital (2020-114-K73). Results: 690 patients were eligible to finish the complete follow-up in the PPS. After LASSO screening and multifactorial logistic regression analysis, physical activity level, taking antiplatelets, Traditional Chinese medicine treatment, Gensini score, Seattle Angina Questionnaire (SAQ)-exercise capacity score, and SAQ-anginal stability score were found to be predictors of the occurrence of CVE. The above predictors are modeled, and a comprehensive comparison of the modeling effectiveness of multiple ML algorithms is performed. The results show that the Light Gradient Boosting Machine (LightGBM) model is the best model, with an area under the curve (AUC) of 0.95 (95% CI = 0.91-1.00) for the test set, Accuracy: 0.90, Sensitivity: 0.87, and Specificity: 0.96. Interpretation of the model using SHAP highlighted the Gensini score as the most important predictor. Based on the multifactorial logistic regression modeling, a nomogram, and online calculators have been developed for clinical applications. Conclusion: We developed the LightGBM optimization model and the multifactor logistic regression model, respectively. The model is interpreted using SHAP and nomogram. This provides an option for early prediction of CVE in patients with SA combined with CHD.

Recommendations for statin management in primary prevention: disparities among international risk scores

BACKGROUND AND AIMS

Statin recommendations in primary prevention depend upon risk algorithms. Moreover, with intermediate risk, risk enhancers and de-enhancers are advocated to aid decisions. The aim of this study was to compare algorithms used in North America and Europe for the identification of patients warranting statin or consideration of risk enhancers and de-enhancers.

METHODS

A simulated population (n = 7680) equal in males and females, with/without smoking, aged 45-70 years, total cholesterol 3.5-7.0 mmol/L, high-density lipoprotein cholesterol 0.6-2.2 mmol/L, and systolic blood pressure 100-170 mmHg, was evaluated. High, intermediate, and low risks were determined using the Framingham Risk Score (FRS), Pooled Cohort Equation (PCE), four versions of Systematic Coronary Risk Evaluation 2 (SCORE2), and Multi-Ethnic Study of Atherosclerosis (MESA) algorithm (0-1000 Agatston Units).

RESULTS

Concordance for the three levels of risk varied from 19% to 85%. Both sexes might be considered to have low, intermediate, or high risk depending on the algorithm applied, even with the same burden of risk factors. Only SCORE2 (High Risk and Very High Risk versions) identified equal proportions of males and females with high risk. Excluding MESA, the proportion with moderate risk was 25% (SCORE2, Very High Risk Region), 32% (FRS), 39% (PCE), and 45% (SCORE2, Low Risk Region).

CONCLUSION

Risk algorithms differ substantially in their estimation of risk, recommendations for statin treatment, and use of ancillary testing, even in identical patients. These results highlight the limitations of currently used risk-based approaches for addressing lipid-specific risk in primary prevention.

A cross-sectional analysis of zinc and copper levels and their relationship to cardiovascular disease risk markers in Qatar biobank participants

Cardiovascular diseases (CVD) are the leading cause of mortality and morbidity worldwide. Dietary intake, particularly zinc (Zn) and copper (Cu) has been strongly associated with CVD. These trace elements play a crucial role in human enzyme activity, suppressing inflammation, catalyzing lipid metabolism enzymes, reducing oxidative stress, and regulating glucose metabolism. However, imbalances in these elements are linked to cardiovascular disturbances. Thus, this study aimed to investigate the association between circulating levels of Zn, Cu, and Zn/Cu ratio with CVD risk factors in the Qatari population. Bivariate logistic regression, adjusted for age, nationality, gender, and education was performed to examine the impact of Zn, Cu, and Zn/Cu ratio (as independent variables) on major CVD risk markers (as dependent variables). Participants in the highest Zn tertiles (T2 and T3) were at greater odds ratio (OR) of unfavorable metabolic functions such as elevated HbA1C [OR = 2.5, p = 0.015 (T2) and OR = 3.2, p = 0.002 (T3)], triglycerides [OR = 2.17, p = 0.015 (T2), and TyG index [OR = 2.21, p = 0.004 (T2), and OR = 2.67, p < 0.001 (T3)] compared to T1. Conversely, they had significantly lower ORs for prolonged prothrombin time [OR = 0.37, p = 0.001 (T3)]. Higher levels of Cu (T2 and T3) had higher OR for elevated HDL-C levels [OR = 1.69, p = 0.046 (T2), and OR = 2.27, p = 0.002 (T3)] and lower OR for elevated levels of triglycerides (OR = 0.4, p = 0.009, T3), diastolic blood pressure [OR = 0.41, p = 0.024 (T2), and OR = 0.47, p = 0.049 (T3)], and creatinine kinase (OR = 0.27, p = 0.014, T3) compared to T1. Higher levels of Cu (T2 and T3) were associated with a higher risk for elevated fibrinogen levels [OR = 3.1, p = 0.035 (T2), and OR = 5.04, p = 0.002 (T3)]. Additionally, higher Zn/Cu ratio (T2 and T3) were associated with lower ORs for elevated fibrinogen levels [OR = 0.3, p = 0.005 (T2), and OR = 0.27, p = 0.005 (T3)] compared to T1, indicating a lower risk of developing CVD. The study reveals a link between Zn, Cu, and the Zn/Cu ratio and cardiovascular disease risk. A higher Zn/Cu ratio may protect against CVD, while elevated Cu levels are linked to obesity, fibrinogen levels, and HbA1C. Maintaining optimal levels of these trace elements, either through diet or supplementation, may help reduce CVD risk.

Development and Validation of a Bayesian Network-Based Model for Predicting Coronary Heart Disease Risk From Electronic Health Records

BACKGROUND

Traditional risk evaluation models have been applied to guide public health and clinical practice in various studies. However, the application of existing methods to data sets with missing and censored data, as is often the case in electronic health records, requires additional considerations. We aimed to develop and validate a predictive model that exhibits high performance with data sets that contain missing and censored data.

METHODS AND RESULTS

This is a retrospective cohort study of coronary heart disease at Weihai Municipal Hospital on unique patients aged 18 to 96 years between 2013 and 2021. A total of 169 692 participants formed our study population, of which 10 895 participants were diagnosed with coronary heart disease. Models were built for the risk of coronary heart disease based on demographic, laboratory, and medical history variables. All complete samples were assigned to the training set (n=110 325), whereas the remaining samples were assigned to the validation set (n=59 367). The area under the receiver operating characteristic curve value was 0.800 (95% CI, 0.794-0.805), and the C statistic was 0.796 (95% CI, 0.791-0.801) in the derivation cohort, and the corresponding values were 0.837 (95% CI, 0.821-0.853) and 0.838 (95% CI, 0.822-0.854) in the validation cohort. The calibration curve demonstrated its good calibration ability, and decision curve analysis showed its clinical usefulness.

CONCLUSIONS

Our proposed risk prediction model has demonstrated significant effectiveness in handling the complexities of electronic health record data, which often involve extensive missing data and censoring. This approach may offer potential assistance in the use of electronic health records to enhance patient outcomes.

Time-weighted blood pressure with cardiovascular risk among patients with or without diabetes

BACKGROUND

Usual measures of blood pressure (BP) do not account for both the magnitude and duration of exposure to elevated BP over time. We aimed to demonstrate the effect of a novel time-weighted BP on cardiovascular outcomes using a post hoc analysis of two published randomized trials.

HYPOTHESIS

Time-weighted blood pressure is associated with cardiovascular risk among patients with or without diabetes.

METHODS

The limited-access ACCORD and SPRINT data sets were used for the current study. Time-weighted BP is obtained by dividing cumulative BP by the total follow-up time. Time-weighted BP burden above a threshold is also determined after deriving the time-weighted BP by re-zeroing the interpolated pressure values at two different hypertension thresholds (>140/90 and >130/80 mmHg).

RESULTS

Eighteen thousand five hundred forty-one patients from the two clinical trials were enrolled in this study. A J-curve relation was observed between time-weighted BP and major cardiovascular events (MACE). The systolic blood pressure (SBP) burden independently predicted MACE across the two trials at different thresholds (ACCORD: SBP > 130 mmHg, HR = 1.05 [1.03-1.06]; SBP > 140 mmHg, HR = 1.06 [1.04-1.08]; SPRINT: SBP > 130 mmHg, HR = 1.04 [1.03-1.05]; SBP > 140 mmHg, HR = 1.05 [1.04-1.07]). Consistent results were found for diastolic blood pressure (DBP) burden (ACCORD: DBP > 80 mmHg, HR = 1.10 [1.06-1.15]; DBP > 90 mmHg, HR = 1.20 [1.11-1.30].

SPRINT

DBP > 80 mmHg, HR = 1.06 [1.02-1.09]; DBP > 90 mmHg, HR = 1.12 [1.06-1.18]). Significant associations were also observed for stroke, myocardial infarction, cardiovascular death, and all-cause mortality.

CONCLUSION

Both time-weighted SBP and DBP independently influenced the risk of adverse cardiovascular events among patients with and without diabetes, regardless of the definition of hypertension (130/80 or <140/90 mmHg).

Educational Attainment and Lifetime Risk of Cardiovascular Disease

Importance

Education is a social determinant of health. Quantifying its association with lifetime cardiovascular disease (CVD) risk has public health importance.

Objective

To calculate lifetime risk estimates of incident CVD and CVD subtypes and estimate years lived with and without CVD by education.

Design, Setting, and Participants

Included community-based cohort studies with adjudicated cardiovascular events used pooled individual-level data from 1985 to 2015 of 6 prospective cohort studies. The study team assessed the association between education and lifetime CVD risk with modified Kaplan-Meier and Cox models accounting for competing risk of noncardiovascular death. The study team estimated years lived with and without CVD by education with the Irwin restricted mean and the utility of adding educational attainment to CVD risk assessment. Participants (baseline 40 to 59 years old and 60 to 79 years old) were without CVD at baseline and had complete education, cardiovascular risk factors, and prospective CVD outcomes data. Data were analyzed from January 2022 to September 2022.

Exposures

Educational attainment (less than high school, high school completion, some college, or college graduate).

Main outcome and measures

Cardiovascular events (fatal and nonfatal coronary heart disease, heart failure, and stroke; CVD-related deaths; and total CVD encompassing any of these events).

Results

There were 40 998 participants (23 305 female [56.2%]) with a mean (SD) age of 58.1 (9.7) years for males and 58.3 (9.9) years for females. Compared with college graduates, those with less than high school or high school completion had higher lifetime CVD risks. Among middle-aged men, the competing hazard ratios (HRs) for a CVD event were 1.58 (95% CI, 1.38-1.80), 1.30 (95% CI, 1.10-1.46), and 1.16 (95% CI, 1.00-1.34) in those with less than high school, high school, and some college, respectively, compared with those with college completion. Among women, these competing HRs were 1.70 (95% CI, 1.49-1.95), 1.19 (95% CI, 1.05-1.35), and 0.98 (95% CI, 0.83-1.15). Individuals with higher education had longer duration of life prior to incident CVD. Education provided limited contribution toward enhancing CVD risk prediction.

Conclusions and relevance

Lower education was associated with lifetime CVD risk across adulthood; higher education translated to healthy longevity. Educational policy initiatives may associate with long-term health benefits.

Societal health and economic burden of cardiovascular diseases in the population with type 2 diabetes in Qatar. A 10-year forecasting model

AIMS

To predict the future health and economic burden of cardiovascular disease (CVD) in type 2 diabetes (T2D) in Qatar.

MATERIALS AND METHODS

A dynamic multistate model was designed to simulate the progression of fatal and non-fatal CVD events among people with T2D in Qatar aged 40-79 years. First CVD events [i.e. myocardial infarction (MI) and stroke] were calculated via the 2013 Pooled Cohort Equation, while recurrent CVD events were sourced from the REACH registry. Key model outcomes were fatal and non-fatal MI and stroke, years of life lived, quality-adjusted life years, total direct medical costs and total productivity loss costs. Utility and cost model inputs were drawn from published sources. The model adopted a Qatari societal perspective. Sensitivity analyses were performed to test the robustness of estimates.

RESULTS

Over 10 years among people with T2D, model estimates 108 195 [95% uncertainty interval (UI) 104 249-112 172] non-fatal MIs, 62 366 (95% UI 60 283-65 520) non-fatal strokes and 14 612 (95% UI 14 472-14 744) CVD deaths. The T2D population accrued 4 786 605 (95% UI 4 743 454, 4 858 705) total years of life lived and 3 781 833 (95% UI 3 724 718-3 830 669) total quality-adjusted life years. Direct costs accounted for 57.85% of the total costs, with a projection of QAR41.60 billion (US$11.40 billion) [95% UI 7.53-147.40 billion (US$2.06-40.38 billion)], while the total indirect costs were expected to exceed QAR30.31 billion (US$8.30 billion) [95% UI 1.07-162.60 billion (US$292.05 million-44.55 billion)].

CONCLUSIONS

The findings suggest a significant economic and health burden of CVD among people with T2D in Qatar and highlight the need for more enhanced preventive strategies targeting this population group.