Cardiovascular Disease Risk Score Research Articles

Cardiovascular risk estimation and statin adherence: an historical cohort study protocol.

Adherence to statins for the primary prevention of cardiovascular disease (CVD) is low. There is evidence that some facets of the initiation consultation, or the initiating clinician, are associated with adherence. CVD risk estimation is fundamental to statin initiation and shared decision making (SDM), because the benefits of statins are proportional to CVD risk. Absence of a recorded CVD score before statin initiation therefore indicates SDM is unlikely. To investigate whether SDM, using CVD risk score as a proxy measure, is associated with adherence to statins and CVD outcomes. A retrospective cohort study using a database of English primary care records. The cohort will include statin naïve patients aged 40-84 years initiated on statins for primary prevention between 2017 and 2020, categorised by the presence or absence of a CVD risk score at statin initiation. Statin adherence and persistence will be determined from subsequent statin prescriptions. Multivariable modelling, accounting for potential confounders, will determine the association between a recorded CVD risk score and subsequent statin adherence and with statin persistence. A secondary analysis will investigate the relationship to subsequent CVD outcomes and death. This research uses a record of CVD risk score as a proxy for SDM, to investigate the link between SDM and medication adherence. It will shed light on relationship between how the initiation consultation is performed and subsequent adherence and persistence with treatment.

Cardiovascular wellness in low-resource settings: A mobile app-based risk prediction study among fuel filling station employees in Puducherry district

ABSTRACT Background: India is witnessing a significant increase in the prevalence of non-communicable diseases (NCDs), and addressing this requires a comprehensive and multi-faceted approach. The burden of NCDs puts a strain on the healthcare system, requiring an increased focus on preventive measures, early detection, and management of chronic conditions. Adopting a risk-based approach to cardiovascular diseases (CVDs) in resource-poor settings offers several economic and social advantages. Aims and Objectives: The aim of the study was to assess the prevalence of CVD risk factors among fuel filling station employees in the Puducherry district and the 10-year CVD risk prediction score among the study participants with the World Health Organisation package of essential non-communicable (WHO PEN) app and package for resource-poor settings. Methods: A community-based cross-sectional study was conducted among the fuel filling station employees in Puducherry. A universal sampling method was employed. The data were collected using a pilot-tested, predesigned, structured questionnaire and the WHO PEN app was used to estimate the CVD risk score. The data were collected from February 2021 to January 2022 and analysed using Statistical Package for Social Sciences (SPSS) version 20. Frequency distribution along with the Chi-square test was employed to test statistical significance. Results: Out of 212 subjects, 170 (80.2%) were males, out of which 116 (54.7%) were between 40 and 50 years old. Nearly half the participants (48%) had CVD risk scores ranging from 5 to 20%, with an increased prevalence of CVD risk factors, namely, obesity/overweight (65.5%), physical inactivity (58.5%), hypertension (52%), alcohol consumption (51%) and tobacco consumption in any form (25.5%). Conclusions: This study sheds light on the sedentary nature of the occupation and the increased prevalence of CVD risk factors among the study participants. It is also evident that the participants had higher CVD risk scores for developing CVDs in the future. Recommendations: The use of mobile-based apps can be used as a feasible strategy to save scarce resources in delivering primary health care. We also propose that the nature of occupation be taken into account as one of the parameters for risk prediction. Risk prediction assessment should be made mandatory during the annual examination of employees.

Food consumption patterns and Framingham cardiovascular risk score among shift workers: A NOVA-based approach

ObjectiveTo evaluate the association between dietary quantity and variety, by extent and purpose of processing, and Framingham cardiovascular disease (CVD) risk score among rotating shift workers. MethodsThe cross-sectional study included male shift workers. Dietary intake was assessed using a 24-hour recall method conducted by trained interviewers. Food items were classified using two approaches: the first was based on the amount of food consumed in each food group. Fruits, vegetables, and legumes (FVL) intake, is classified as recommended at 400g per day by WHO guidelines. Ultraprocessed foods (UPFs) were analyzed based on tertiles of daily caloric contribution. The second approach, the NOVA dietary diversity score (DDS-NOVA) assessed the variety of consumed items within each food group, assigning points for each unique item consumed, irrespective of quantity or frequency. The CVD-risk score was evaluated using the Framingham coronary heart disease risk score, categorizing participants as low risk (<5%) or intermediate to high risk (>5%). Descriptive, univariate, and multivariate logistic regression were used, with adjustments made for age, skin color, schooling, duration of shift work, physical activity, BMI and total caloric intake. ResultsThe study involved 213 participants, with an average age of 38.67 years (±6.96), a minimum of 26 and a maximum of 60. The majority (62.4%) were between 30 and 40 years old; 49.3% identified themselves as brown; 56.8% had completed high school; and 79.3% were married. The Framingham CVD-risk score indicated that 56.2% were at low risk (<5%) and 43.7% at intermediate to high risk (≥5%). The average consumption of FVL was 272.32g (±350.43), with 70.4% meeting the recommendation of ≥400g/day. Participants consumed an average of 3.46 fresh food items, 3.74 minimally processed food items, 2.54 processed food items and 3.39 ultra-processed food items. In the multivariate model, consuming ≥400g/day of FVL reduced the likelihood of cardiovascular risk ≥5% by 2.12 times (OR: 0.47; 95%CI: 0.23-0.98). Each additional item of fresh food reduced the risk by 49% (OR: 0.67; 95%CI: 1.01-1.66), while each additional item of ultra-processed food increased the risk by 30% (OR: 1.30; 95%CI: 0.52-0.87). There was no significant association between the calorie intake of ultra-processed foods and cardiovascular risk. ConclusionBoth adequate consumption of FVL quantity and a greater variety of fresh-foods were associated with a lower chance of CVD-risk, while a higher variety of consumption of UPF items increased this chance.

Reducing Cardiovascular Risk in HIV: The Unseen Impact of Visceral Fat

While modern antiretroviral therapy (ART) for people with HIV (PWH) increases life expectancy, there is still an increased risk of developing cardiovascular disease (CVD) in this population. As one factor associated with this increased risk is excess visceral abdominal fat (EVAF), the Visceral Adiposity Measurement and Observations Study (VAMOS) aimed to assess the impact of EVAF on CVD risk in PWH taking modern ART. Participants were grouped according to visceral adipose tissue (VAT) surface area &lt;130 cm2 (non-EVAF group) or ≥130 cm2 (EVAF group), quantified by CT scan. Findings presented at IDWeek 2024 revealed significant differences between EVAF and non-EVAF groups in 10-year atherosclerotic CVD (ASCVD) risk score, as well as many of their individual components. VAMOS also showed correlations between increasing VAT surface area and increasing 10-year ASCVD risk score and insulin resistance measures. Accordingly, VAT may represent a targetable factor to reduce ASCVD risk. Also shown was an inverse relationship between growth hormone (GH) levels and VAT surface area. As GH reductions related to obesity are associated with elevated CVD risk, increasing GH levels may consequently reduce ASCVD risk score. Analysis of two Phase III trials of the GH-releasing hormone (GHRH) analogue tesamorelin, which can significantly reduce VAT in PWH, was also presented at IDWeek 2024. A significant overall trend in 10-year ASCVD risk score reduction was shown in tesamorelin-treated participants, around half of which were already taking lipid lowering therapies. This suggests a benefit of targeting and reducing EVAF to further impact ASCVD risk.

Abstract 4138519: A Scoping Review Exploring Cardiovascular Risk and Health Metrics and Cancer Prediction

Introduction: Cardiovascular disease (CVD) and cancer are leading causes of morbidity and mortality. Since they share risk factors, it is plausible that CVD risk scores and cardiovascular health (CVH) metrics could also be used to predict cancer. Research Question: What is the relationship between established CVD risk scores and CVH metrics and the incidence of cancer? Methods: A librarian searched four databases (Embase, PubMed, Scopus, Web of Science: Core) in February 2024 without language restriction. Using Covidence, two reviewers independently screened the titles, abstracts, and full texts of the retrieved articles based on the inclusion criteria (prospective observational studies, adults aged ≥18 years, reported incidence of any type of cancer as an outcome, and used at least one CVD risk score or CVH metric as an exposure). A third reviewer resolved conflicts. The characteristics of the studies retained after screening and the summary estimates of the associations were extracted using Excel. Results: Of the 4,165 records screened, 13 studies (reporting 14 CVD or CVH metrics) were included. The heterogeneity in the scales (comparison group) precluded a meta-analysis. Four studies evaluated CVD risk scores (Atherosclerotic Cardiovascular Disease [ASCVD], Framingham Risk Score, Systematic Coronary Risk Evaluation), and 10 reported CVH metrics (American Heart Association [AHA] Life’s Simple 7, AHA Life’s Essential 8). Sample size ranged from 1,880 to 342,226, with median follow-up from 8.1 to 29.6 years. Most of the studies included more women than men (61.5%) and mean age ranged from 44.8 to 72 years. The majority of studies included all cancer types (71.4%), including breast, lung, colorectal, and prostate cancer subtypes, and the total number of cancer events ranged from 387 to 11,643. Studies utilizing CVD risk scores consistently reported that individuals with a higher CVD risk, developed any type of cancer, with hazard ratios (HRs) ranging from 1.02 to 3.71, and studies employing CVH metrics generally indicated an ideal CVH is associated with a lower cancer risk, with HRs ranging from 0.49 to 0.95. Conclusion: Despite heterogeneity in CVD risk metrics and cancer subtypes, most studies reported that higher CVD risk scores or worse CVH metrics may increase future cancer risk. More rigorous studies are needed focusing on specific CVD risk metrics and cancer types of cancer to produce evidence suitable for a meta-analysis.

Abstract 4133654: External Validation of the Guha-Stabellini CVD Prostate Cancer-Specific Calculator in Short-Term Follow-Up

Introduction: Conventional cardiovascular disease (CVD) risk scores are inaccurate for prostate cancer patients (PC); the Guha-Stabellini machine learning (GS-ML) score shows promise but lacks external validation. Hypothesis: The GS-ML score is superior to conventional CVD scores in patients with PC. Aim(s): To conduct external validation of the GS-ML score in patients diagnosed with PC. Methods: The validation used holdout data from Seidman Cancer Center’s CAISIS platform (internal validation cohort) and RADICAL PC1 (external validation cohort; a prospective study of men diagnosed with PC within 1 year or starting ADT within 1 month of enrollment), matching covariates with the GS-ML score. With limited follow-up, short-term CVD (2,000 days from PC diagnosis) was the outcome. Performance was assessed via area under the receiver operating characteristic curve (AUC) with assistance from Youden statistic cutoff, comparing metrics with ACC/AHA pooled cohort equations (PCE), SCORE-2, and AHA-PREVENT scores. Atherosclerotic cardiovascular disease (ASCVD) included non-fatal ischemic stroke and myocardial infarction. CVD included ASCVD and heart failure. Results: We included 2,495 patients from RADICAL PC1 and 1,506 from the internal validation cohort ( Table 1 ). In the internal validation cohort, the CVD AUCs were 0.58, 0.49, 0.65, 0,73, and 0.75 for PCE, SCORE2, PREVENT simple, PREVENT enhanced, and GS-ML score, respectively. In RADICAL PC1, the AUCs for CVD were 0.60, 0.43, 0.67, and 0.64 for PCE, SCORE2, PREVENT simple and GS-ML score, respectively. For ASCVD, internal validation cohorts’ AUCs were 0.63, 0.62, 0.66, 0.73, and 0.67 for PCE, SCORE2, PREVENT simple, PREVENT enhanced, and Guha-Stabellini, respectively. The RADICAL PC1 ASCVD AUCs were 0.64, 0.46, 0.65, and 0.61, for PCE, SCORE2, PREVENT simple and GS-ML scores, respectively, Conclusion(s): The GS-ML score was validated for PC patients, showing superior performance to PCE and SCORE2, and similar performance to AHA-PREVENT in predicting CVD. The European Cardio-Oncology guidelines should reconsider using SCORE2 for PC patients. Further improvement and validation with nationally representative datasets are needed to corroborate these findings and enhance the generalizability of the GS-ML score.

Machine-learning-based prediction of cardiovascular events for hyperlipidemia population with lipid variability and remnant cholesterol as biomarkers.

Dyslipidemia poses a significant risk for the progression to cardiovascular diseases. Despite the identification of numerous risk factors and the proposal of various risk scales, there is still an urgent need for effective predictive models for the onset of cardiovascular diseases in the hyperlipidemic population, which are essential for the prevention of CVD. We carried out a retrospective cohort study with 23,548 hyperlipidemia patients in Shenzhen Health Information Big Data Platform, including 11,723 CVD onset cases in a 3-year follow-up. The population was randomly divided into 70% as an independent training dataset and remaining 30% as test set. Four distinct machine-learning algorithms were implemented on the training dataset with the aim of developing highly accurate predictive models, and their performance was subsequently benchmarked against conventional risk assessment scales. An ablation study was also carried out to analyze the impact of individual risk factors to model performance. The non-linear algorithm, LightGBM, excelled in forecasting the incidence of cardiovascular disease within 3years, achieving an area under the 'receiver operating characteristic curve' (AUROC) of 0.883. This performance surpassed that of the conventional logistic regression model, which had an AUROC of 0.725, on identical datasets. Concurrently, in direct comparative analyses, machine-learning approaches have notably outperformed the three traditional risk assessment methods within their respective applicable populations. These include the Framingham cardiovascular disease risk score, 2019 ESC/EAS guidelines for the management of dyslipidemia and the 2016 Chinese recommendations for the management of dyslipidemia in adults. Further analysis of risk factors showed that the variability of blood lipid levels and remnant cholesterol played an important role in indicating an increased risk of CVD. We have shown that the application of machine-learning techniques significantly enhances the precision of cardiovascular risk forecasting among hyperlipidemic patients, addressing the critical issue of disease prediction's heterogeneity and non-linearity. Furthermore, some recently-suggested biomarkers, including blood lipid variability and remnant cholesterol are also important predictors of cardiovascular events, suggesting the importance of continuous lipid monitoring and healthcare profiling through big data platforms.

Waist-to-hip ratio as a contributor associated with higher atherosclerotic cardiovascular disease risk assessment in patients with diabetes: a cross-sectional study

IntroductionThis study aimed to identify the factors most strongly associated with an increased atherosclerotic cardiovascular disease (ASCVD) risk score in patients with type 2 diabetes (T2D).MethodsThis cross-sectional study included 4698 patients with T2D over an 11-year period (2010–2021). Patients were categorized into four groups based on their 10-year ASCVD risk score (< 5%, 5–7.5%, 7.5–20%, and > 20%). Multinominal regression analysis was used to evaluate the association between various modifiable and non-modifiable risk factors and the ASCVD risk score.ResultsOf the patients, 35.9% had a 10-year ASCVD risk score below 5%, 12.6% had a score between 5% and 7.5%, 30.8% had a score between 7.5% and 20%, and 19.7% had a score above 20%. Higher ASCVD risk scores were significantly associated with elevated waist-to-hip ratio (WHR > 0.93), pulse pressure, uric acid, triglycerides, and decreased glomerular filtration rate (all p-values < 0.05). WHR demonstrated the strongest association with higher ASCVD risk scores (OR: 4.55, 95% CI: 2.94–7.03, p < 0.001) when comparing patients with ASCVD scores > 5% to those with scores < 5%.ConclusionWHR was independently associated with higher ASCVD risk scores in patients with T2D. Incorporating WHR, along with traditional risk factors, could improve ASCVD risk assessments in this population.

10-Year Atherosclerotic Cardiovascular Disease (ASCVD) Risk Score Calculation in Out-Patient Department

Objective: To calculate 10-year Atherosclerotic Cardiovascular Disease risk score in outdoor department of a tertiary care hospital and identify individuals at high risk of cardiovascular disease. Study Design: Cross-sectional study. Place and Duration of Study: Combined Military Hospital, Malir, Pakistan, from Oct 2020 to Mar 2021. Methodology: 116 patients presenting to Out-Patient Department of General Medicine of CMH, Malir, Pakistan, without previous evidence of cardiovascular disease were included. Previous history of diabetes, smoking, use of anti-hypertensives, Aspirin and statins was recorded. Systolic and diastolic blood pressures, waist circumference, HbA1c, fasting blood sugar, fasting LDL, HDL and total cholesterol were tested for each patient. 10-year ASCVD risk score was calculated using online ASCVD Risk Estimator calculator. Results: Mean age of the patients was 58.6±9.92 years with 62.1% being males and 37.9% being females. Mean 10-year ASCVD risk score was 13.37±7.1, of which 21 patients (18.1%) had Very High, 66(56.9%) had Intermediate and 29(25%) had Low 10-year ASCVD risk score. Among Very High cases, 80.9% were males, all were in age group 50-79 years, 61.9% were diabetic, 33.3% were smokers and 66.7% were obese. Conclusion: A very high percentage of study group had Intermediate or Very High 10-year ASCVD risk score. Identifying those individuals at high risk early and controlling the modifiable risk factors can help lessen the morbidity and mortality associated with cardiovascular diseases.

Long-term validation of AtherosSlerosis CardioVascular Disease (ASCVD) risk score and the role of aspirin for primary Cardiovascular prevention in Korean patients with over ASCVD 20% risk score

Abstract Background Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death worldwide. The ASCVD risk score can be a great tool for preventing ASCVD in the future. There is a mediation recommendation depending on calculated risk called United States Prevention Services Task Force (USPSTF) aspirin (ASA) recommendation. However, the validation studies of long-term clinical outcomes in Korean population using the ASCVD risk score and of the effect of ASA in Korean patients using USPSTF recommendation are limited. Methods A total of 7,249 patients with any chest pain who underwent coronary spasm provocation tests between January 2004 and December 2021 were enrolled. Patients were divided into four groups, based on the ASCVD risk score: &amp;lt; 5% group (Low Risk, n = 2,534), 5 - 10% group (Borderline Risk, n=1,681), 10 - 20% group (Intermediate Risk, n = 1,896) and ≥ 20% group (High Risk, n = 1,138). The primary endpoint was Major Adverse Cerebral and Cardiovascular Event (MACCE1), including stroke and MACE. The secondary endpoint was MACCE 2, defined as composite of MACE and recurrent angina requiring follow-up coronary angiography (CAG). The third endpoint was the effect of aspirin in patients who have over 20% ASCVD risk. Results Long term (10-year) ASCVD risk score was well-validated from the "Low Risk" group to the "High Risk" group by 1.87%, 7.44%, 14.09%, and 30.61%, respectively (P &amp;lt; 0.001). In baseline characteristics, the calculation factors of ASCVD risk score is also well-stratified, showing the more adverse clinical profiles in the "High Risk" group than the "Low Risk" group. In 10-year clinical outcomes, although MACCE1 and MACCE2 showed an increasing trend numerically, stroke was observed to significantly increase according to ASCVD risk score. There was no effect of ASA prescribed in accordance with USPSTF recommendation. The group with the highest rate of 20% or more failed to show the aspirin prevent effect on the occurrence of CV events, but also increased the incidence (MACCE1; HR: 1.647, P-Value: 0.283, 95% CI: 0.662 - 4.100, MACCE2; HR: 1.819, P-Value: 0.025, 95% CI: 1.078 - 3.068). Conclusion Long term ASCVD risk score was associated with higher risk of stroke. However, MACCE1 and MACCE2 only showed an increasing trend numerically. Furthermore, the effect of ASA prescribed based on the USPSTF ASA use recommendation statement were not observed in Korean population. Consequently, additional research is needed to ensure the utility of ASCVD risk score and the effect of ASA in high-risk patients to prevent future CV events in Korean population.

Symptoms and ASCVD score fail to identify majority of the patients at risk of first myocardial infarction

Abstract Background Cardiovascular disease screening has long relied on the presence of symptoms like chest pain or on the Atherosclerotic Cardiovascular Disease (ASCVD) risk score, which is typically initiated at age 40. However, current research suggests that the ASCVD risk score may not incorporate a comprehensive range of factors and should be started earlier. Furthermore, the absence of symptoms such as angina in some patients prior to acute coronary syndrome (ACS) casts doubt on the reliability of symptom-based screening methods. Purpose This study aimed to evaluate the effectiveness of the ASCVD risk score and chest pain as predictors for ACS. Methods We retrospectively analyzed the data of all patients of 65 or younger who presented with their first ACS event in a single US center from January 2020 to January 2024. We collected the demographic and clinical data, including age, sex, lipid panel, blood pressure, medical history, onset of symptoms, and calculated their individual ASCVD risk score. We explored whether these patients, if assessed one week before their ACS event, would have been identified as at risk and thus prescribed lipid lowering or recommended for further diagnostic tests. Results Among 166 patients presenting with ACS, 64 (39%) were considered low risk with an ASCVD risk score of &amp;lt;5 or too low to calculate. 20 (12%) patients were assessed as borderline risk with an estimated risk score of 5-7.5%. In the intermediate risk category, 20 patients (12%) had a score of 7.5% -10% and 42 patients (25%) were estimated to have a score of &amp;gt;10 to &amp;lt;20%. 14 patients (8%) fell in the high-risk category, and lastly 6 patients had an LDL that was above 190 mg/dl. Regarding symptoms of chest pain or shortness of breath, 14 patients (8%) did not experience any symptoms prior to their presentation, 98 (59%) patients experienced their first episode of symptoms within 48 hours, 19 patients (11%) within 2 days to a week, 10 patients (6%) had CP leading up to their event from a week to a month, 6 patients (4%) in the range of a month to 3 months and 19 patients (11%) had symptoms longer than 3 months prior to their presentation. To summarize if there were seen 1 week prior to their first ACS events, 51% of them were not recommended for statin therapy based on their ASCVD risk score and 67% of patients either had no chest pain until the event or chest pain within 48hrs of onset of their ACS and consequently would not have been routinely screened for coronary artery disease (CAD) by any anatomical or functional methods. Conclusion(s) ASCVD risk score and symptoms fail to identify majority of patient below 65 years of age with their first MI. Given high prevalence of CAD and associated mortality, improved screening tools, in addition to symptomatology or risk scores, would be more effective in identifying individuals at risk.

Validation of digital cardiovascular risk score (DiCAVA) in the United States All of Us dataset

Abstract Introduction The cardiovascular disease (CVD) risk score DiCAVA was developed in 2021 using UK Biobank data with the aim to be used for population health screening by deriving its predictions only from variables readily available to every individual, omitting difficult-to-obtain measurements such as blood pressure and invasive blood tests for metrics like cholesterol or HbA1c, which are commonly used in clinical CVD risk assessment tools. The original set of variables was reduced to 30 in the DiCAVA Lite score to further improve usability in a digital solution accessible to the general population, while maintaining its discrimination ability. Purpose Like many countries, the US has a large burden of CVD and would benefit from easily accessible screening tools. However, to ensure generalisability of the UK-developed score, it is necessary to evaluate its performance in a population where the score is intended to be used. Methods Data from a large real-world modern observational study in the US, All of Us, was used to evaluate discrimination and calibration metrics of the risk score. Participants with pre-existing CVD and without available electronic health records were excluded from the study. Variables from the All of Us dataset were matched to the original variables and any missing values were imputed using multiple imputation. Results 216,985 participants with a median follow-up time of 3.44 years were included in the study. The median age was 51 years and 63% of the population were female. Discrimination ability in the All of Us dataset (C-index 0.76) slightly surpassed the discrimination achieved at training with UK Biobank (C-index 0.73), and that of Framingham risk score calculated for the All of Us population (C-index 0.72), demonstrating the score’s usability in the US. The score showed very good discrimination in both males (C-index 0.74) and females (C-index 0.77), all ethnic groups and age groups, with the exception of the population over 65 years of age, where the C-index dropped to 0.65 as expected (similar to that observed in the UK Biobank). Calibration of the original model was assessed at 3 years and showed under-estimation of the predicted risk (calibration-in-the-large of 2.37%). Following re-calibration, the algorithm demonstrated excellent results with the average predicted 3-year risk showing 0.59% difference from the observed CVD rate (calibration plot in Figure). Conclusions Overall, the DiCAVA Lite score has shown very good discrimination in the US, showing its generalisability in different demographic populations. Its re-calibrated form is now validated for use in the US population and because of its ability to be utilised outside clinical settings, it can be deployed widely in the general population as an initial screening tool and potentially boost awareness of cardiovascular health in an effort to drive preventative care of CVD.Re-calibration of the DiCAVA Lite score

Do Personalized Nutrition Interventions Improve Dietary Intake and Risk Factors in Adults With Elevated Cardiovascular Disease Risk Factors? A Systematic Review and Meta-analysis of Randomized Controlled Trials.

Dietary modifications can improve cardiovascular disease (CVD) risk factors. Personalized nutrition (PN) refers to individualized nutrition care based on genetic, phenotypic, medical, behavioral, and/or lifestyle characteristics. PN may be beneficial in improving CVD risk factors, including diet. However, this has not been reviewed previously. The aim was to evaluate the effectiveness of PN interventions on CVD risk factors and diet in adults at elevated CVD risk. Six databases were searched for randomized controlled trials published between 2000 and 2023 that tested the impact of PN interventions on CVD risk factors in people at elevated risk. Risk of bias was assessed using the Academy of Nutrition and Dietetics Quality Criteria checklist. Data synthesis of eligible articles included participant characteristics, intervention details, and change in primary CVD risk factor outcomes, including blood pressure (BP), plasma lipids, and CVD risk score, and secondary risk factors, including anthropometric outcomes and diet quality. Random-effects meta-analyses were conducted to explore weighted mean differences (WMDs) in change or final mean values for studies with comparable data (studies with dietary counseling interventions) for outcomes including BP, blood lipids, and anthropometric measurements. Of 7676 identified articles, 16 articles representing 15 studies met the inclusion criteria. Studies included between 40 and 563 participants and reported outcomes for CVD risk factors, including hyperlipidemia (n = 5), elevated BP (n = 3), overweight/obesity (n = 1), and multiple risk factors (n = 6). Risk of bias was low. Results suggested potential benefit of PN on systolic BP (WMD: -1.91; 95% CI: -3.51, -0.31 mmHg) and diastolic BP (WMD: -1.49; 95% CI: -2.39, -0.58 mmHg) and dietary intake in individuals at high CVD risk. Results were inconsistent for plasma lipid and anthropometric outcomes. Results were promising for PN interventions that used dietary counseling on CVD risk factors in at-risk individuals. However, further evidence for other personalization methods is required, including improving methodological quality and longer study duration in future PN interventions. OpenScience Framework (https://doi.org/10.17605/OSF.IO/SHVWP).

Visceral Obesity and Its Association with Severe Coronary Artery Calcification in Patients with Metabolic Dysfunction-Associated Steatotic Liver Disease.

Background/Objectives: The role of body composition parameters in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) with presence and severity of coronary artery calcification (CAC) is still not fully elucidated. We aimed to evaluate the impact of computed tomography (CT)-based body composition parameters in patients with MASLD with CAC severity. Methods: In this multicenter study, 1870 individuals underwent cardiac CT for the detection of CAC as well as ultrasonography for the diagnosis of hepatic steatosis. The presence of CAC was defined by a CAC score threshold of >0, while severe CAC was defined by a threshold of >300. Using the abdominal cross-sectional CT images at the L3 vertebra level, we analyzed the skeletal muscle index, visceral to subcutaneous adipose tissue ratio, and muscle density using the Hounsfield unit. Results: Of 648 patients with MASLD, the proportions of presence of CAC and severe CAC were 45.2% and 9.9%, respectively. Visceral obesity was not associated with the presence of CAC after adjustment for age, sex, smoking, statin therapy, type 2 diabetes, and advanced fibrosis (adjusted odds ratio (aOR), 1.38; 95% confidence interval (CI), 0.86-2.23; p = 0.180). However, visceral obesity was independently associated with severe CAC after adjustment for several metabolic risk factors (aOR, 3.54; 95% CI, 1.25-14.90; p = 0.039), and adjustment for atherosclerotic cardiovascular disease risk scores (aOR, 3.74; 95% CI, 1.31-15.79; p = 0.032). Conclusions: Visceral obesity may serve as a novel prognostic CT-based radiological biomarker for patients with MASLD with severe CAC.

Predictive role of peak VO2 for short- and long-term major adverse cardiac events in patients with high cardiovascular risk.

The objective of this study was to assess the accuracy of VO2 measurements in predicting long-term major adverse cardiac events (MACEs) in patients with high cardiovascular risk. Based on a10-year atherosclerotic cardiovascular disease risk score, 333 patients with high cardiovascular risk were included in this retrospective analysis. The study endpoint was MACEs, comprising all-cause mortality, cardiovascular mortality, non-fatal myocardial infarction or stroke, and coronary revascularization. The study cohort was divided into two groups according to the frequency of MACE occurrence. Measurements of VO2 were assessed for the prediction of MACEs. The best predictive accuracy for 1‑year MACEs was determined to be aVO2 max value of ≥ 20.3 mL/kg/min, with 60% specificity and 60% sensitivity (area under the curve [AUC]: 0.61; 95% confidence interval [CI]: 0.51-0.71; p < 0.001), and for 5‑year MACEs it was ≥ 19.9 mL/kg/min, with 69% specificity and 64% sensitivity (AUC: 0.69; 95% CI: 0.62-0.76; p < 0.001). Multivariable Cox regression analysis, after adjusting for univariable factors, showed that VO2 max was independently associated with both short- and long-term MACEs in patients at high cardiovascular risk (hazard ratio [HR]: 0.900, 95% CI: 0.858-0.943, p < 0.001). According to the results of this pilot study, VO2 max can predict both short- and long-term MACEs in patients at high cardiovascular risk.

Impact of provision of abdominal aortic calcification results on fruit and vegetable intake: 12-week randomized phase 2 controlled trial

Provision of non-invasive vascular imaging results to individuals has been shown to improve cardiovascular disease risk factor control: its impact on diet remains uncertain. In this two-arm, single-blind, parallel, 12-week randomized controlled trial, 240 participants, 57.5% females aged 60–80 y had abdominal aortic calcification and clinical assessments performed at a hospital clinic. Participants were randomized 1:1 to receive (intervention n = 121) or not (control n = 119) their calcification results. Both groups received educational resources on cardiovascular disease risk control and were unblinded to the intervention. Outcome measures were performed at baseline and 12 weeks. The primary outcomes of the study were changes in fruit and vegetable intake measures over 12 weeks assessed using plasma carotenoid concentrations (biomarkers of FV intake) and a food frequency questionnaire. Secondary outcomes included 12-week changes in other aspects of the diet, physical activity, body weight, blood pressure, heart rate, lipid profile, glucose concentrations, estimated cardiovascular disease risk score, and medication use. Between-group differences were tested using linear mixed-effects regression. There were no between-group differences in the primary outcomes at 12 weeks: plasma carotenoids (mean difference +0.03 µg/mL [95%CI −0.06, 0.13]) and fruit and vegetable intakes (+18 g/d [−37, 72]). However, the provision of calcification results led to between-group differences in serum total (−0.22 mmol/L [−0.41, −0.04]) and non-HDL (−0.19 mmol/L [−0.35, −0.03]) cholesterol, and estimated cardiovascular disease risk score (−0.24% [−0.47, −0.02]). No between-group differences were seen for other secondary outcomes. In this work, providing vascular imaging results did not improve diet but did improve some cardiovascular disease risk factors (Australian and New Zealand Clinical Trials Registry ACTRN12618001087246).

Effect of air pollution, genetic susceptibility on the risk of all-cause mortality and cardiovascular outcomes among atrial fibrillation patients

Objective: To analyze the association between air pollution, genetic susceptibility, and the risk of all-cause mortality and cardiovascular outcomes in patients with atrial fibrillation (AF). Methods: AF patients aged between 40-69 years old registered in the United Kingdom Biobank from 2006 to 2010 were included. After excluding those lost to follow-up or with incomplete data during follow-up, 5 814 subjects were analyzed. Long-term exposure to air pollution was estimated at the geocoded residential address of each participant. Genetic risk scores for all-cause mortality, cardiovascular disease, heart failure, myocardial infarction, and stroke were constructed separately for each object to assess the corresponding genetic susceptibility. The Cox proportional hazards model was used to analyze the association between air pollution, genetic susceptibility, and the risk of all-cause mortality and cardiovascular outcomes in AF patients. Results: During a median follow-up of 12.4 years, there were 929 of all-cause mortality (15.98%) and 1 772 of cardiovascular events (30.48%). Multivariable-adjusted analyses revealed that higher exposure to PM2.5, PM10, NOx, and NO2 was associated with an increased risk of cardiovascular disease mortality, heart failure, myocardial infarction, and stroke, with hazard ratios (HRs) ranging from 1.26 to 1.48. Specifically, for each interquartile range (IQR) increase in PM2.5 exposure, the HRs for the outcomes mentioned above were 1.33 (95%CI: 1.14-1.54), 1.42 (95%CI: 1.31-1.54), 1.46 (95%CI: 1.30-1.64), and 1.43 (95%CI: 1.27-1.61), respectively. Both NOx and NO2 exposures were associated with a 9% increased risk of all-cause mortality per IQR increment, with corresponding HRs of 1.09 (95%CI: 1.02-1.17) and 1.09 (95%CI: 1.01-1.17), respectively. Individuals with high genetic susceptibility to AF had a higher risk of myocardial infarction and stroke compared to those with low genetic susceptibility, with corresponding HRs of 1.39 (95%CI: 1.04-1.87) and 1.46 (95%CI: 1.09-1.95), respectively. Compared to AF patients with low air pollution exposure, those with high air pollution exposure have adjusted population attributable fractions of up to 33.57% (95%CI: 17.87%-46.26%) for cardiovascular mortality, 28.61% (95%CI: 20.67%-35.75%) for heart failure, 33.35% (95%CI: 20.97%-43.79%) for myocardial infarction, and 42.29% (95%CI: 30.05%-52.71%) for stroke. Furthermore, there was an additive interaction between PM2.5, NOx, and NO2 exposure and high genetic susceptibility on the incidence of myocardial infarction. An additive interaction was also observed between NOx, NO2 exposure, and high genetic susceptibility on the incidence of heart failure (all P<0.05). Conclusions: Both air pollution and genetic susceptibility increase the risk of all-cause mortality and cardiovascular outcomes in AF patients.

Hormones, Stress, and Heart Disease in Transgender Women with HIV in LITE Plus

Cardiovascular disease (CVD) is a leading cause of death among transgender women and people with HIV. Exogenous estrogen and psychosocial stressors are known risk factors for CVD. Yet, few studies have used biomarkers to examine the role of stress in CVD risk among transgender women with HIV (TWHIV). This analysis examined whether stress moderates relationships between gender-affirming hormone therapy (GAHT) duration and CVD risk among TWHIV. This cross-sectional analysis of baseline data from an observational cohort of 108 Black and Latina TWHIV in Boston, New York, and Washington, DC, enrolled December 2020 to June 2022, measured sociodemographics, medical diagnoses, medications, smoking history, and perceived stress via interviewer-administered surveys. Physiological stress was measured with 14 biomarkers to calculate allostatic load indices (ALI). Forty participants provided saliva samples used to calculate cortisol awakening response and cortisol daily decline. The 2018 American College of Cardiology Revised Pooled Cohort Equation estimated 10-year CVD risk. Data were analyzed in 2024. GAHT duration was positively associated with CVD risk scores in bivariate regression. In multivariable linear regression models (adjusting for age, income, education), only age and ALI remained significantly associated with CVD risk scores (β 1.13, CI: 1.05, 1.21). No stress measure significantly interacted with GAHT duration to affect CVD risk scores. In visual plots, GAHT duration increased CVD risk scores only for TWHIV experiencing the highest ALI. Stress plays an important role in CVD in TWHIV. More research is needed on non-GAHT factors, which influence CVD health among transgender women.

Association between coexisting hypertension, dyslipidaemia and elevated C reactive protein with cardiovascular disease and mortality: a cross-sectional and longitudinal analysis in a representative cohort of older US adults

ObjectiveHypertension and dyslipidaemia are established risk factors for cardiovascular disease (CVD) but they are often insufficient on their own to predict CVD. Inflammation also contributes to CVD, but research on...

ASSIGN score and cancer risk in the Scottish Heart Health Extended Cohort (SHHEC) study

BackgroundThe aim of this work was to determine whether the ASSIGN cardiovascular disease (CVD) score, a 10-year CVD risk score used in primary care in Scotland, could additionally detect cancer risk.Methods18,107 participants were recruited to the Scottish Heart Health Extended Cohort (SHHEC) study between 1982 and 1995. Information on health and lifestyle were collected, along with blood and urine, and participants were followed up via record linkage to 2017. Cox proportional hazards were used to estimate HRs (95% CIs) for time to cancer diagnosis.ResultsA total of 5046 cases of cancer were reported during the follow up period. ASSIGN was significantly associated with a diagnosis of cancer, with a 2.3–3.4% increase in risk of cancer per 1-point increase of ASSIGN. The components of ASSIGN predominantly associated with the risk of cancer were age (HR 1.52; 95% CI 1.48–1.56, cholesterol level (HR 1.11; 95% CI 1.08–1.13), diabetes status (HR 1.24; 95% CI 1.01–1.53), and systolic blood pressure (HR 1.16; 95% CI 1.13–1.19).ConclusionASSIGN could be used not only to predict CVD, but also to predict cancer risk in patients. This needs to be validated in further cohorts.