Cardiovascular Disease Risk Stratification Research Articles

#2647 Assessing atherosclerosis using epicardial adipose tissue in hemodialysis patients: a meta-analysis

Abstract Background and Aims Hemodialysis (HD) patients had higher cardiovascular mortality due to accelerated atherosclerosis in such patients. Epicardial adipose tissue (EAT) thickness is a marker of atherosclerosis and independent predictor of coronary artery disease. The potential use of EAT as an imaging biomarker for cardiovascular disease risk stratification has attracted attention in the recent times. EAT's value in cases of HD hasn't been thoroughly analyzed, though. A meta-analysis of the literature assessing the mean differences in EAT value between HD patients and healthy controls was conducted. Method Pubmed, Google Scholar and Embase databases were searched from inception till 15 January 2024 for studies that measured EAT thickness of adult patients with HD and matched healthy controls. Outcomes included mean difference (MD) and 95% confidence interval (CI) of EAT thickness between the HD patients and the healthy controls. The results were combined using a fixed or random effect model as per heterogeneity among the included studies in Revman 5.4 software. The between-study heterogeneity of effect size was quantified using the Q statistic and I2. The results were represented in forest plots. Statistical significance was determined as P value of less than 0.05. Results Eight studies comprising 757 patients were included in this analysis. EAT thickness were significantly higher in HD patients as compared to healthy controls [MD: 1.88, Confidence Interval (CI): 0.74-3.02, I2 = 98%, P value = 0.001] (Fig. 1). Conclusion This meta-analysis concluded that HD patients are independently associated with higher EAT as compared to healthy controls. The utility of EAT as an imaging biomarker for predicting atherosclerosis in HD patients is promising. EAT represent readily available clinical markers useful in estimating risk of cardiovascular mortality in HD patients.

Association of heavy menstrual bleeding with cardiovascular disease in US female hospitalizations

BackgroundHeavy menstrual bleeding (HMB) is a common menstrual disorder associated with multiple risk factors of cardiovascular disease (CVD) in women. In addition, HMB is often present with irregular menstruation (IM) which is a risk factor for CVD outcomes. However, the relationship between HMB and CVD outcomes is unexplored in the presence or absence of IM. We determined the association of HMB with multiple CVD outcomes using a nationally representative sample of female hospitalizations in the US.MethodsAll hospitalizations of females with HMB diagnosis and normal menstrual cycles from ages of 18 to 70 years were extracted from the National Inpatient Sample Database, 2017. The HMB was defined using the International Classification of Diseases (ICD)-10 for excessive and frequent menstruation bleeding and included any current or history of HMB diagnosis. Outcomes including major adverse cardiovascular events (MACE), coronary heart disease (CHD), stroke, heart failure (HF), atrial fibrillation (AF) or arrhythmia, myocardial infarction (MI), and diabetes (DM) were defined using ICD-10 codes. Adjusted logistic regression and prosperity scores-matched logistic regression analyses were conducted to summarize adjusted associations with an odds ratio (OR) and a 95% confidence interval (CI).ResultsAmong 2,430,851 hospitalizations, HMB was observed in 7762 (0.68%) females with age ≤ 40 years and 11,164 (0.86%) females with age > 40 years. Among hospitalizations with age ≤ 40 years, HMB was significantly associated with increased odds of CVD outcomes including MACE (OR = 1.61; 95% CI: 1.25, 2.08), CHD (OR = 1.72; 95% CI: 1.10, 2.71), stroke (OR = 1.95; 95% CI: 1.12, 3.40), HF (OR = 1.53; 95% CI: 1.15, 2.03), and AF/arrhythmia (OR = 1.84; 95% CI: 1.34, 2.54). These associations were confirmed in multiple sensitivity analyses. In contrast, HMB was not robustly associated with CVD events among hospitalizations of women with age > 40 years. HMB without IM was strongly associated with DM, HF, AF, and MACE outcomes while HMB with IM was strongly associated with CHD and AF outcomes in hospitalizations of young women.ConclusionsHMB is associated with CVD events among US hospitalizations of young women. A routine investigation and screening of menstrual disorders, especially HMB, is useful for CVD risk stratification and management in young women.

#299 The association between body fat distribution, albuminuria, and mortality in relatively healthy adults

Abstract Background and Aims Albuminuria is a risk factor for kidney disease progression and cardiovascular disease (CVD). Metabolic syndrome has been associated with incident albuminuria. We aimed to understand which measures of adiposity are associated with albuminuria and mortality in relatively healthy adults. Method We included 8,215 adults in the National Health and Nutrition Examination Survey (years 2003-6 and 2011-2016) without prior CVD, estimated glomerular filtration rate <60 ml/min/1.73 m2 (eGFR), diabetes, hypertension, or prior dialysis. We used multivariable adjusted linear regression modelling to evaluate sex-stratified relationships between urine albumin excretion and multiple measures of adiposity, controlling for urine creatinine. We then performed sex-stratified multivariable adjusted Cox regression models of the association between adiposity and all-cause mortality. Measures of adiposity included android fat mass index (FMI), gynoid FMI, android-to-gynoid ratio, subcutaneous FMI, abdominal FMI, visceral FMI, body mass index (BMI), and waist circumference. Models were adjusted for age, race or ethnicity, education, food insecurity, health insurance, survey year, physical activity, eGFR, total cholesterol, systolic blood pressure, hemoglobin A1c, and urine albumin:creatinine ratio (UACR), and menopausal status (among women). Models were subsequently adjusted for BMI and waist circumference. Results The sample was 52.3% women, the mean (standard deviation, SD) BMI was 27.1 kg/m2 (SD 6.7), and the median UACR was 5.4 mg/g [3.8, 8.6]. Over a median follow up of 7.8 years [IQR 5.3-14.3], there were 128 deaths among men and 89 deaths among women. Among men, a 1-SD increase in android fat mass index (FMI) was associated with 13.1% (95% CI 4.5, 22.5) higher albuminuria. Similarly, a 1-SD increase in visceral FMI was associated with 8.3% (95% CI 1.3, 15.7) higher albuminuria. BMI was non-linearly associated with albuminuria among men. Among women, a 1-unit increase in android to gynoid ratio was associated with 47.7% lower albuminuria (% change = −47.7 (95% CI −61.4, −29.3). A 5 kg/m2 increase in BMI was associated with 11.0% lower albuminuria (% change = −11.0 (95% CI −15.0, −6.7) and a 3 cm increase in waist circumference was associated with 1.6% (95% CI 0.03, 3.0) higher albuminuria. Among men, a 1-SD increase in abdominal FMI was associated with 2.09-fold higher risk of all-cause mortality (HR 2.09 [95% CI 1.16-3.74]), independent of BMI and waist circumference. Among women, a 1-SD increase in gynoid FMI was associated with 56% decreased risk of all-cause mortality (HR 0.44 [95% CI 0.20-0.88]), independent of BMI and waist circumference. Conclusion Adiposity is differently associated with albuminuria and mortality in relatively healthy men and women. Sex-specific patterns of adipose deposition may inform CVD risk stratification.

Joint association of TyG index and high sensitivity C-reactive protein with cardiovascular disease: a national cohort study

BackgroundBoth the triglyceride-glucose (TyG) index, as a surrogate marker of insulin resistance, and systemic inflammation are predictors of cardiovascular diseases; however, little is known about the coexposures and relative contributions of TyG index and inflammation to cardiovascular diseases. Using the nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), we conducted longitudinal analyses to evaluate the joint and mutual associations of the TyG index and high-sensitivity C-reactive protein (hsCRP) with cardiovascular events in middle-aged and older Chinese population.MethodsThis study comprised 8 658 participants aged at least 45 years from the CHARLS 2011 who are free of cardiovascular diseases at baseline. The TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Cardiovascular events were defined as the presence of physician-diagnosed heart disease and/or stroke followed until 2018.We performed adjusted Cox proportional hazards regression and mediation analyses.ResultsThe mean age of the participants was 58.6 ± 9.0 years, and 3988 (46.1%) were females. During a maximum follow-up of 7.0 years, 2606 (30.1%) people developed cardiovascular diseases, including 2012 (23.2%) cases of heart diseases and 848 (9.8%) cases of stroke. Compared with people with a lower TyG index (< 8.6 [median level]) and hsCRP < 1 mg/L, those concurrently with a higher TyG and hsCRP had the highest risk of overall cardiovascular disease (adjusted hazard ratio [aHR], 1.300; 95% CI 1.155–1.462), coronary heart disease (aHR, 1.294; 95% CI 1.130–1.481) and stroke (aHR, 1.333; 95% CI 1.093–1.628), which were predominant among those aged 70 years or below. High hsCRP significantly mediated 13.4% of the association between the TyG index and cardiovascular disease, while TyG simultaneously mediated 7.9% of the association between hsCRP and cardiovascular risk.ConclusionsThe findings highlight the coexposure effects and mutual mediation between the TyG index and hsCRP on cardiovascular diseases. Joint assessments of the TyG index and hsCRP should be underlined for the residual risk stratification and primary prevention of cardiovascular diseases, especially for middle-aged adults.

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.

Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis. This review aims to provide essential knowledge on the AI-based techniques currently applied to CACS, setting the stage for a holistic analysis of the use of these techniques in coronary artery calcium imaging. While the focus of the review will be detailing the evidence, strengths, and limitations of end-to-end CACS algorithms in electrocardiography-gated and non-gated scans, the current role of deep-learning image reconstructions, segmentation techniques, and combined applications such as simultaneous coronary artery calcium and pulmonary nodule segmentation, will also be discussed.

ASSESSMENT OF CARDIOVASCULAR RISK IN PATIENTS WITH RHEUMATOID ARTHRITIS ACCORDING TO CURRENT HYPERTENSION GUIDELINES

Objective: Patients with rheumatoid arthritis (RA) are at increased risk of cardiovascular disease (CVD) by as much as 50% compared to the general population. Considering that disease-specific calculators have failed to provide more accurate CVD risk stratification in RA, CVD risk calculation in RA patients is challenging, especially for those who are not by definition at high risk based on concomitant established CVD or its equivalents. The presence of an immune-mediated inflammatory disease (e.g., RA) has been considered as a CVD risk modifier by the previous 2018 European Society of Hypertension/European Society of Cardiology (ESH/ESC) guidelines. Nevertheless, current 2023 ESH/ESC guidelines recommend assessment in RA using general CVD risk calculators. Design and method: We aimed to calculate CVD risk in RA patients using the most frequently applied CVD risk calculators in the general population. We only stratified patients free from established CVD (heart disease, stroke) or its equivalents (diabetes mellitus, chronic kidney disease) aged 40-74 years. The following algorithms were applied: (i) SCORE2 (Systemic Coronary Risk Estimation-2), (ii) Framingham Risk Score-Adult Treatment Panel (FRS-ATP) CVD risk calculator, and (iii) the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Equation. We further correlated the estimated CVD risk by each algorithm with surrogate CVD markers, i.e. arterial stiffness and carotid atherosclerosis. For this purpose, carotid-femoral pulse wave velocity (cfPWV) was measured using applanation tonometry (Sphygmocor ®), and carotid intima-media thickness (cIMT) was estimated using carotid ultrasound. Results: A total of 91 patients aged 60.3±8.1 years were included (78% females). Using the FRS-ATP algorithm, more patients were classified as high risk and fewer as low risk compared to the other calculators (Table 1). Moreover, CVD risk calculated with FRS-ATP correlated stronger with both cfPWV and cIMT, compared to CVD risk calculated with the other algorithms (Table 2). Conclusions: In RA patients without established CVD, diabetes, or chronic kidney disease, the FRS-ATP algorithm may be applied as a useful tool for CVD risk stratification. Prospective, large-scale studies are warranted to determine the most reliable CVD risk prediction model for patients with RA.

Chinese visceral adiposity index and its transition patterns: impact on cardiovascular and cerebrovascular diseases in a national cohort study

BackgroundObesity affects approximately 800 million people worldwide and may contribute to various diseases, especially cardiovascular and cerebrovascular conditions. Fat distribution and content represent two related yet distinct axes determining the impact of adipose tissue on health. Unlike traditional fat measurement indices, which often overlook fat distribution, the Chinese visceral adiposity index (CVAI) is a novel metric used to assess visceral fat accumulation and associated health risks. Our objective is to evaluate its association with the risk of cardiovascular and cerebrovascular diseases.MethodsA nationwide longitudinal study spanning 9 years was conducted to investigate both the effects of baseline CVAI levels (classified as low and high) and dynamic changes in CVAI over time, including maintenance of low CVAI, transition from low to high, transition from high to low, and maintenance of high CVAI. Continuous scales (restricted cubic spline curves) and categorical scales (Kaplan-Meier curves and multivariable Cox regression analyses) were utilized to evaluate the relationship between CVAI and cardiovascular and cerebrovascular diseases. Furthermore, subgroup analyses were conducted to investigate potential variations.ResultsTotally 1761 individuals (22.82%) experienced primary outcomes among 7717 participants. In the fully adjusted model, for each standard deviation increase in CVAI, there was a significant increase in the risk of primary outcomes [1.20 (95%CI: 1.14–1.27)], particularly pronounced in the high CVAI group [1.38 (95%CI: 1.25–1.54)] compared to low CVAI group. Regarding transition patterns, individuals who consistently maintained high CVAI demonstrated the highest risk ratio compared to those who consistently maintained low CVAI [1.51 (95%CI: 1.31–1.74)], followed by individuals transitioning from low to high CVAI [1.22 (95% CI: 1.01–1.47)]. Analysis of restricted cubic spline curves indicated a positive dose-response relationship between CVAI and risk of primary outcomes (p for non-linear = 0.596). Subgroup analyses results suggest that middle-aged individuals with high CVAI face a notably greater risk of cardiovascular and cerebrovascular diseases in contrast to elderly individuals [1.75 (95% CI: 1.53–1.99)].ConclusionThis study validates a significant association between baseline levels of CVAI and its dynamic changes with the risk of cardiovascular and cerebrovascular diseases. Vigilant monitoring and effective management of CVAI significantly contribute to early prevention and risk stratification of cardiovascular and cerebrovascular diseases.

Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort.

The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascular (CV) events using deep learning (DL) and compare against the machine learning (ML) paradigm. The participants in this study consisted of 459 individuals who had undergone coronary angiography, contrast-enhanced ultrasonography, and focused carotid B-mode ultrasound. Each patient was tracked for thirty days. The measurements on these patients consisted of maximum plaque height (MPH), total plaque area (TPA), carotid intima-media thickness (cIMT), and intraplaque neovascularization (IPN). CAD risk and CV event stratification were performed by applying eight types of DL-based models. Univariate and multivariate analysis was also conducted to predict the most significant risk predictors. The DL's model effectiveness was evaluated by the area-under-the-curve measurement while the CV event prediction was evaluated using the Cox proportional hazard model (CPHM) and compared against the DL-based concordance index (c-index). IPN showed a substantial ability to predict CV events (p < 0.0001). The best DL system improved by 21% (0.929 vs. 0.762) over the best ML system. DL-based CV event prediction showed a ~ 17% increase in DL-based c-index compared to the CPHM (0.86 vs. 0.73). CAD and CV incidents were linked to IPN and carotid imaging characteristics. For survival analysis and CAD prediction, the DL-based system performs superior to ML-based models.

Diagnostic Ability of Manual Calcification Length Assessment on Non-Electrocardiographically Gated Computed Tomography for Estimating the Presence of Coronary Artery Disease.

Background: Coronary artery calcification score (CACS) on electrocardiography (ECG)-gated computed tomography (CT) is used for risk stratification of atherosclerotic cardiovascular disease, which requires dedicated analytic software. In this study, we evaluated the diagnostic ability of manual calcification length assessment on non-ECG-gated CT for epicardial coronary artery disease (CAD). Methods: A total of 100 patients undergoing both non-ECG-gated plain CT scans with a slice interval of 1.25 mm and invasive coronary angiography were retrospectively included. We manually measured the length of the longest calcified lesions of coronary arteries on each branch. The relationship between the number of coronary arteries with the length of coronary calcium > 5, 10, or 15 mm and the presence of epicardial CAD on invasive angiography was evaluated. Standard CACS was also evaluated using established software. Results: Of 100 patients, 49 (49.0%) had significant epicardial CAD on angiography. The median standard CACS was 346 [7, 1965]. In both manual calcium assessment and standard CACS, the increase in calcium burden was progressively associated with the presence of epicardial CAD on angiography. The receiver operating characteristic curve analysis showed similar diagnostic abilities of the two diagnostic methods. The best cut-off values for CAD were 2, 1, and 1 for the number of vessels with calcium > 5, 10, and 15 mm, respectively. Overall, the diagnostic ability of manual calcium assessment was similar to that of standard CACS > 400. Conclusions: Manual assessment of coronary calcium length on non-ECG-gated plain CT provided similar diagnostic ability for the presence of significant epicardial CAD on invasive angiography, as compared to standard CACS.

Role of Triglyceride to High Density Lipoprotein (TG/HDL) Ratio as A Marker of Insulin Resistance in Adults of Central India: A Narrative Review

One of the main risk factors for the onset of type 2 diabetes mellitus (T2DM) and cardiovascular diseases (CVD) is insulin resistance (IR). But because there aren't many easy-to-use and trustworthy biomarkers or tests, the entity is frequently under diagnosed. The present review was performed with an aim to provide the available data regarding the role or efficacy of TG/HDL ratio as an indicator of IR in adults of central India, a region popular for high prevalence of T2DM and CVD. An extensive search of all materials related to the topic was carried out in the PubMed search engine. Relevant research articles focusing on use of TG/HDL as a marker of insulin resistance published in the period 2002 to 2023 were included in the review. A total of 33 articles were selected based upon their suitability with the current review objectives and analyzed. The review concludes that TG/HDL ratio is a simple, affordable, and feasible marker of IR that can be used in economically poor regions of the India or world for screening IR and risk stratification of T2DM and CVD in adults. However, more studies are needed in India and all over the world to validate this marker and its cut-off values.

Evaluating cardiovascular disease risk stratification using multiple-polygenic risk scores and pooled cohort equations: insights from a 17-year longitudinal Korean cohort study.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, caused by a complex interplay of genetic and environmental factors. This study aimed to evaluate the combined efficacy of multi-polygenic risk scores and pooled cohort equations (PCE) for predicting future CVD risks in the Korean population. In this longitudinal study, 7,612 individuals from the Ansan and Ansung cohorts were analyzed over a 17-year follow-up period. The participants were genotyped using the Korea Biobank Array, and quality-controlled genetic data were subjected to imputation analysis. The weighted sum of the PRSs (wPRSsum) was calculated using PRS-CS with summary statistics from myocardial infarction, ischemic stroke, coronary artery disease, and hypertension genome-wide association studies. The recalibrated PCE was used to assess clinical risk, and the participants were stratified into risk groups based on the wPRSsum and PCE. Associations between these risk scores and incident CVD were evaluated using Cox proportional hazards models and Kaplan-Meier analysis. The wPRSsum approach showed a significant association with incident CVD (HR = 1.15, p = 7.49 × 10-5), and the top 20% high-risk genetic group had an HR of 1.50 (p = 5.04 × 10-4). The recalibrated PCE effectively differentiated between the low and high 10-year CVD risk groups, with a marked difference in survival rates. The predictive models constructed using the wPRSsum and PCE demonstrated a slight improvement in prediction accuracy, particularly among males aged <55 years (C-index = 0.640). We demonstrated that while the integration of wPRSsum with PCE did not significantly outperform the PCE-only model (C-index: 0.703 for combined and 0.704 for PCE-only), it provided enhanced stratification of CVD risk. The highest risk group, identified through the combination of high wPRSsum and PCE scores, exhibited an HR of 4.99 for incident CVD (p = 1.45 × 10-15). These findings highlight the potential of integrating genetic risk assessments with traditional clinical tools for effective CVD risk stratification. Although the addition of wPRSsum to the PCE provided a marginal predictive improvement, it proved valuable in identifying high-risk individuals and supporting personalized treatment strategies. This study reinforces the utility of multi-PRS in conjunction with clinical risk assessment tools, paving the way for more tailored approaches for CVD prevention and management in diverse populations.

Abstract P513: Coronary Artery Calcium Burden in Rural Alabama: Initial Findings From the Risk Underlying Rural Areas Longitudinal Cohort Study

Introduction: Individuals living in rural areas have a disproportionately high rate of cardiovascular disease (CVD) mortality. Coronary artery calcium (CAC) scanning may inform CVD risk stratification. However, the prevalence of CAC in rural areas is unknown. Research Question: What is the prevalence of CAC according to age, sex, and self-reported race (Black, White) in two rural counties in Alabama? Aims: To determine the prevalence of a CAC score &gt;0, a CAC score ≥100, and premature CAC among rural persons without clinical CVD and the extent to which they differ by demographic group. Methods: We studied 789 participants between the age of 25 and 64 years in the Risk Underlying Rural Areas Longitudinal (RURAL) Cohort Study sample in Alabama who underwent CAC scoring on non-contrast cardiac computed tomography. Premature CAC was defined as CAC &gt;0 for men &lt;45 years old, and women &lt;55 years old. Multivariable logistic regression (including age, sex, race) estimated adjusted odds ratios (aOR) for CAC &gt;0 and CAC ≥100. Results: The median age was 51 years, 70% were women, and 80% were Black. Among the were 37% with CAC &gt;0 the median CAC score was 64, while 14% had CAC ≥100 and 12% had premature CAC. Significant differences in all three CAC categories were consistently observed across age and sex, but not race ( Figure ). After adjusting for age and race, women had an approximate 70% lower odds of CAC &gt;0 (aOR=0.29, 95% CI: 0.19-0.44) and CAC ≥100 (aOR=0.28, 95% CI: 0.18-0.43) compared to men. There were no significant differences in CAC &gt;0 (aOR=0.70, 95% CI: 0.43-1.12) or CAC ≥100 (aOR=0.76, 95% CI: 0.46-1.25) for Black versus White persons independent of age and sex. Conclusion(s): In a Southern rural cohort of young and middle-aged persons, approximately one in three had prevalent CAC and one in eight had premature CAC. In contrast to previously published urban cohorts, rural Black adults had a similar CAC burden to their White counterparts. There is a need to explore the factors implicated in the high CAC burden within Southern rural communities.

Association of serum concentrations of remnant cholesterol with incident cardiovascular disease in patients with rheumatoid arthritis: A real-world data from 2001 to 2022

BackgroundRemnant cholesterol (RC) promotes cardiovascular disease (CVD) in the general population, but its role among rheumatoid arthritis (RA) patients remains unknown. We aimed to investigate circulating RC levels associated with incident CVD among Chinese patients with RA. MethodsA total of 1018 RA patients free of baseline CVD were included and followed up in a prospective RA CVD cohort from 2001 to 2022. Fasting serum levels of triglycerides, total cholesterol (TC), low-density (LDL-C), and high-density lipoprotein cholesterol (HDL-C) were measured, while RC and Non-HDL-C levels were calculated. The primary exposure was RC levels. A LASSO Cox model was used to select covariates. The Fine-Gray competing risk model was used to estimate hazard ratios (HRs). ResultsRA patients had a mean age of 53.9 years, and 802 (78.8%) were females. After a median follow-up of 5.54 years, 131 patients developed CVD with an incidence rate of 21.6 per 1000 person-years. Continuous and quartile-categorized RC levels were associated with incident CVD before and after multivariate adjustment and Bonferroni correction (all P < 0.001). There were no robust associations of other lipids with incident CVD. The fully adjusted HRs for RC were 2.30 (95% CI 1.58–3.35) per 1 mmol/L increase, and 2.40 (1.36–4.25) and 2.81 (1.60–4.94) for patients in the 3rd and 4th versus the 1st quartile, respectively. ConclusionsCirculating RC levels are positively associated with incident CVD among Chinese RA patients independent of known risk factors, implying its clinically preferable use for improving the stratification of CVD risk in RA patients.

Proposal to improve the patient journey for women's cardiovascular prevention

The relevance of gender medicine in cardiovascular prevention is still underestimated, and there is a lack of viable women-specific preventive, diagnostic, and therapeutic strategies. To ensure women have equal access to cardiovascular prevention, cardiovascular disease risk stratification needs to consider gender-specific factors related to women reproductive cycle phases together with the different impact that traditional risk factors have on men and women. The aim of this document is to improve the patient journey for cardiovascular risk prevention in women, enhancing the importance of a multidisciplinary approach and the role of the various professional figures involved, starting with the general practitioner, as the main actor of the first risk stratification. The goal of the proposed patient journey is to ensure effective risk assessment of cardiovascular disease in women, by raising attention on the risk factors related to different hormonal phases and to bridge the sex and gender gap in cardiovascular prevention. We hope that this journey can be implemented as uniformly as possible in clinical practice throughout Italy.

Achieving Better Understanding of Obstructive Sleep Apnea Treatment Effects on Cardiovascular Disease Outcomes through Machine Learning Approaches: A Narrative Review.

Obstructive sleep apnea (OSA) affects almost a billion people worldwide and is associated with a myriad of adverse health outcomes. Among the most prevalent and morbid are cardiovascular diseases (CVDs). Nonetheless, randomized controlled trials (RCTs) of OSA treatment have failed to show improvements in CVD outcomes. A major limitation in our field is the lack of precision in defining OSA and specifically subgroups with the potential to benefit from therapy. Further, this has called into question the validity of using the time-honored apnea-hypopnea index as the ultimate defining criteria for OSA. Recent applications of advanced statistical methods and machine learning have brought to light a variety of OSA endotypes and phenotypes. These methods also provide an opportunity to understand the interaction between OSA and comorbid diseases for better CVD risk stratification. Lastly, machine learning and specifically heterogeneous treatment effects modeling can help uncover subgroups with differential outcomes after treatment initiation. In an era of data sharing and big data, these techniques will be at the forefront of OSA research. Advanced data science methods, such as machine-learning analyses and artificial intelligence, will improve our ability to determine the unique influence of OSA on CVD outcomes and ultimately allow us to better determine precision medicine approaches in OSA patients for CVD risk reduction. In this narrative review, we will highlight how team science via machine learning and artificial intelligence applied to existing clinical data, polysomnography, proteomics, and imaging can do just that.

Update on sex specific risk factors in cardiovascular disease.

Cardiovascular disease (CVD) is the leading cause of death worldwide and accounts for roughly 1 in 5 deaths in the United States. Women in particular face significant disparities in their cardiovascular care when compared to men, both in the diagnosis and treatment of CVD. Sex differences exist in the prevalence and effect of cardiovascular risk factors. For example, women with history of traditional cardiovascular risk factors including hypertension, tobacco use, and diabetes carry a higher risk of major cardiovascular events and mortality when compared to men. These discrepancies in terms of the relative risk of CVD when traditional risk factors are present appear to explain some, but not all, of the observed differences among men and women. Sex-specific cardiovascular disease research-from identification, risk stratification, and treatment-has received increasing recognition in recent years, highlighting the current underestimated association between CVD and a woman's obstetric and reproductive history. In this comprehensive review, sex-specific risk factors unique to women including adverse pregnancy outcomes (APO), such as hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus, preterm delivery, and newborn size for gestational age, as well as premature menarche, menopause and vasomotor symptoms, polycystic ovarian syndrome (PCOS), and infertility will be discussed in full detail and their association with CVD risk. Additional entities including spontaneous coronary artery dissection (SCAD), coronary microvascular disease (CMD), systemic autoimmune disorders, and mental and behavioral health will also be discussed in terms of their prevalence among women and their association with CVD. In this comprehensive review, we will also provide clinicians with a guide to address current knowledge gaps including implementation of a sex-specific patient questionnaire to allow for appropriate risk assessment, stratification, and prevention of CVD in women.

Lipoprotein(a) testing in lipid clinics across the UK: Results of a national survey

Lipoprotein(a) is an independent risk factor for cardiovascular disease and its use is recommended in national and international guidelines for cardiovascular disease risk stratification. We undertook a survey to understand the availability and application of lipoprotein(a) measurement across UK lipid clinics. Fifty-three out of an estimated 200 lipid clinics (27%) provided responses. 81% of fifty-three clinics had access to lipoprotein(a) measurement. 27 clinics disclosed the number of lipoprotein(a) tests ordered annually with approximately half of the clinics (52%) requesting 0-250 tests per year. 60% measured lipoprotein(a) once per patient and the leading indication was a personal or family history of premature history of cardiovascular disease in those <60 years old. 63% of clinics that provided comments with lipoprotein(a) results graded cardiovascular risk as per the HEART UK consensus statement. 60% of clinics performed family cascade testing on lipoprotein(a) results ≥200nmol/L. Lipoprotein(a) was reported in nmol/L, mg/dL or mg/L by 48%, 24% and 28% of responding clinics, respectively. National effort is required to provide universal access to Lipoprotein(a) measurement and to harmonise the clinical application of this data.

Common carotid artery diameter and the risk of cardiovascular disease mortality: a prospective cohort study in northeast China.

The association between the common carotid artery (CCA) diameter and cardiovascular disease (CVD) is recognized, but the precise nature of this link remains elusive. This study aimed to investigate the potential relationship between CCA diameter and the risk of CVD mortality in a large population in northeast China. The current study included 5668 participants (mean age 58.9 ± 10.1years) from a population-based study conducted in rural areas of northeast China between September 2017 and May 2018. Information on death was collected from baseline until July 31, 2022. The CCA inter-adventitial diameter was measured using ultrasound. Cox proportional-hazard models were employed to explore the relationship between the common carotid artery diameter and cardiovascular mortality. At baseline, the mean CCA diameter (mm) of subjects was 7.30 ± 0.99 and increased significantly with age, ranging from 6.65 ± 0.71 among people 40-49years to 7.99 ± 1.04 among people ≥ 80years. CCA diameter was significantly larger in males compared to females (7.51 ± 1.03 versus vs. 7.16 ± 0.94; P < 0.001). A total of 185 participants died of CVD during a median follow-up of 4.48years. CCA diameters were divided into quartiles, and the highest quartile of carotid diameter (≥ 8.06mm) had a 2.29 (95% confidence interval [CI]: 1.24, 4.22) times higher risk of CVD mortality than the lowest quartile (≤ 6.65mm) (P < 0.01) in the fully adjusted model. Each increase in the diameter of the common carotid artery (per SD) raised the risk of cardiovascular death by 36% (hazard ratio [HR]: 1.36; 95% CI: 1.18, 1.57). The subgroup analysis results demonstrated that a per SD increase was associated with a 42% increased risk of CVD mortality in participants aged ≥ 64years in the fully adjusted model (HR: 1.42; 95%CI: 1.21, 1.66). Our study indicates the possible incremental value of CCA diameter in optimizing the risk stratification of cardiovascular disease and provides essential insights into reducing the burden of cardiovascular disease.

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis.

Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Cardiovascular multimodality imaging in women: a scientific statement of the European Association of Cardiovascular Imaging of the European Society of Cardiology.

Cardiovascular diseases (CVD) represent an important cause of mortality and morbidity in women. It is now recognized that there are sex differences regarding the prevalence and the clinical significance of the traditional cardiovascular (CV) risk factors as well as the pathology underlying a range of CVDs. Unfortunately, women have been under-represented in most CVD imaging studies and trials regarding diagnosis, prognosis, and therapeutics. There is therefore a clear need for further investigation of how CVD affects women along their life span. Multimodality CV imaging plays a key role in the diagnosis of CVD in women as well as in prognosis, decision-making, and monitoring of therapeutics and interventions. However, multimodality imaging in women requires specific consideration given the differences in CVD between the sexes. These differences relate to physiological changes that only women experience (e.g. pregnancy and menopause) as well as variation in the underlying pathophysiology of CVD and also differences in the prevalence of certain conditions such as connective tissue disorders, Takotsubo, and spontaneous coronary artery dissection, which are all more common in women. This scientific statement on CV multimodality in women, an initiative of the European Association of Cardiovascular Imaging of the European Society of Cardiology, reviews the role of multimodality CV imaging in the diagnosis, management, and risk stratification of CVD, as well as highlights important gaps in our knowledge that require further investigation.