Cardiovascular Disease Risk Estimation Research Articles

Association between high versus low cardiovascular risk in individuals with corresponding unexpected absent versus severe subclinical coronary atherosclerosis, a nationwide, multicenter study

Abstract Background It remains unclear as to why some individuals at low risk of cardiovascular disease (CVD) develop severe coronary atherosclerosis, while those at high CVD risk may remain free from coronary atherosclerosis. Purpose Using Coronary Computed Tomography Angiography (CCTA), we aimed to identify factors associated with absence and severe coronary atherosclerosis in subjects from the general population with very high and low-moderate CVD risk, respectively. Methods We assessed cross-sectionally a nationwide, multicenter population-based cohort, consisting of 30,154 individuals randomly recruited from the general population (age range 50-64 years, 51.4% women). Coronary calcified plaque burden was estimated by coronary artery calcium score (CACS) assessed by CCTA. Absent coronary atherosclerosis was defined as CACS 0 and severe coronary atherosclerosis was defined as CACS ≥301. We investigated only individuals with low-moderate (<5%) and very high CVD risk (≥10%) according to SCORE2 were included. Individuals with CACS 0 and prevalent CVD were excluded, as well as those with moderate CACS (1-300) or SCORE2 risk 5-9%. Out of 26 722 subjects with complete data on CACS and SCORE2, 13 075 were included. Logistic regression was performed adjusted for age and sex. Results The overall distribution of CACS in relation to SCORE2 CVD risk is illustrated in the Figure. Study characteristics are displayed in Table 1. Severe-extensive CACS in combination with low-moderate CVD risk was present in 2.3% (n=296). A further 2.3% (n=311) had very high CVD risk but CACS 0. Factors associated with CACS 0 despite a very-high estimated CVD risk included: lower age, being female, being born in Sweden, not having hypertension or hyperlipidemia, fewer pack-years of smoking, and lower waist circumference in men. On the contrary, severe-extensive CACS despite a low-moderate estimated CVD risk was associated with higher age, being male, being an ex-smoker, reporting more pack-years of smoking, having higher HbA1c, higher BMI, higher waist circumference, and prevalent hyperlipidemia and hypertension (Table 2). Conclusions We identified extreme cardiovascular risk phenotypes (subgroups) in the general population that either lacked coronary calcifications despite being at very high estimated CVD risk or had severe subclinical coronary atherosclerosis despite being at estimated low-moderate CVD risk. Further studies are warranted to elucidate putative enhancing or protective mechanisms explaining this unexpected phenomenon.

Defining high risk in the cardiovascular-kidney-metabolic syndrome and associated cardiovascular disease outcomes

Abstract Background The American Heart Association (AHA) recently developed the cardiovascular-kidney-metabolic (CKM) syndrome construct with stages 0-4 to comprehensively characterize the spectrum of cardiovascular disease (CVD) risk [1]. CKM Stage 3 is defined by subclinical CVD or high (≥20%) estimated 10-year CVD risk according to the newly-derived PREVENT models [2]. However, within CKM Stage 3, the burden of subclinical atherosclerosis equivalent to a ≥20% estimated CVD risk, and long-term CVD outcomes associated with CKM Stage 3, are not known. Purpose To (1) characterize the distribution of subclinical atherosclerosis by coronary artery calcium (CAC) according to PREVENT estimated CVD risk categories, and (2) quantify long-term CVD risk associated with CKM Stage 3, in two international cohorts of adults without prior CVD. Methods In participants of the Multi-Ethnic Study of Atherosclerosis (MESA, age 45-84 years) and the Rotterdam Study (age ≥55 years), the burden of CAC was calculated across estimated 10-year CVD risk (low, 0 to <5%; borderline 5 to <7.5%; intermediate, 7.5 to <20%; high, ≥20%). Participants were categorized into CKM stages according to CVD risk factors (body mass index, waist circumference, glycemic status, blood pressure, lipids, kidney function), estimated 10-year CVD risk (by AHA PREVENT model), and presence of CAC. The association of CKM syndrome stage with fatal or nonfatal CVD outcomes was evaluated with covariate-adjusted proportional hazards regression. Results Among 6,123 MESA participants (52% female, mean age 61.4 years) and 1,691 Rotterdam Study participants (46% female, mean age 67.1 years), the distribution of CAC across absolute 10-year CVD risk categories is shown in Figure 1. In high (≥20%) CVD risk adults, CAC score ≥100 was present in 50% of MESA participants and 48% of Rotterdam Study participants. Most participants were classified as CKM Stage 3 (53% in MESA, 83% in Rotterdam). Over a median follow-up of 17.5 years in MESA, CVD events occurred in 5% of CKM Stage 0, 6% of Stage 1, 9% of Stage 2, and 26% of Stage 3 participants. Over a median follow-up of 10.2 years in the Rotterdam Study, CVD events occurred in 0% of CKM Stage 0 and 1, 8% of Stage 2, and 17% of Stage 3 participants (Figure 2). The risk of total CVD was significantly higher in CKM Stage 3 participants relative to CKM Stage 0-2 (MESA: adjusted HR 2.74, 95% CI 2.32, 3.23; Rotterdam: adjusted HR 2.18, 95% CI 1.34, 3.54). Conclusions In an international, multi-ethnic sample of middle-aged adults, adults with high (≥20%) absolute 10-year CVD risk by PREVENT had substantial burden of CAC. Adults in CKM Stage 3 had approximately 2.2- to 2.7-times higher risk for CVD, compared with adults in lower CKM stages. Accounting for estimated CVD risk and burden of cardiovascular, kidney, and metabolic risk factors informs prevention of subclinical and clinical CVD.

Comparison of cardiovascular disease risk assessment tools in primary prevention patients with raised lipoprotein(a)

Abstract Background Genetically inherited lipoprotein (a) (lp(a)) is an independent cardiac risk factor. The approach to cardiovascular disease (CVD) risk modification is, however, uncertain. Current CVD risk calculators do not take lp(a) into account and guidance suggests binary treatment decisions based on presentation of lp(a) without considering other risk factors. A new CVD risk assessment tool has been developed which includes lp(a) concentration, Lp(a) Clinical Guidance (lpaclinicalguidance.com). Purpose The aim was to compare the CVD risk estimations and management impact, over both 10 years and lifetime, using the HEART UK consensus statement, QRISK3, Lp(a) Score, Score-2, Score-2 OP, and LIFE-CVD assessment tools in 20 primary prevention patients with raised lp(a). Methods This was a retrospective analysis from an existing database, recruited through lipid and cardiology outpatient services, with raised lp(a), and no history of CVD. A random selection with a broad range of lp(a) concentrations were chosen. The 10-year risk threshold to treat was based on current NICE guidance at 10% and, in the absence of consensus, a lifetime risk threshold of 25%. Lp(a) was measured by a reference clinical laboratory using a Roche platform (Denka Seiken reagent, isoform insensitive). Results The subset (n=20) included patients with lp(a) ranging from 64 nmol/L to >720 nmol/L, aged 20 to 78 (12 females). Risk assessment tool age restrictions prohibited risk estimation in all patients (explaining the variation in denominator below). Figure 1 shows a comparison of 10-year risk assessment tools, figure 2 lifetime risk. HEART UK guidance would indicate 90% of patients (18/20) were eligible to commence lipid lowering therapy, however, all patients would have treatment indicated based on Lp(a) Score (16/16). Using Score-2, no patients would have treatment indicated (0/6). Only 25% of patients (1/4) would have treatment indicated using Score-2 OP despite a minimum age criterion that alone introduces a major CVD risk factor. Of the remaining risk estimation tools: LIFE-CVD, QRISK3 lifetime risk, and QRISK3 10-year risk indicated 85% (11/13), 50% (8/16), and 38% (6/16) of patients, respectively, would have treatment indicated. Conclusions In primary prevention patients with raised lp(a), CVD risk estimation and decision-making is impaired by discrepancies in risk assessment tools. There may be underestimation in CVD risk, and subsequently under-treatment, with principal use of QRISK3 10-year risk to guide lipid lowering therapy. Lifetime CVD risk may be underestimated by QRISK and LIFE-CVD proportionally to the degree of elevation of lp(a). Risk assessment is imperfect; population data can only provide limited information when applied to an individual and the wide discrepancy found here calls into question the validity of risk estimation formulae in this population, or alternatively provides a range of tools for clinicians to select to suit the question asked.

Estimation of individual lifetime cardiovascular disease risk and treatment benefit in patients with established atherosclerotic cardiovascular disease: the updated SMART-REACH2 model

Abstract Background The 2021 ESC Guidelines on Cardiovascular Disease (CVD) Prevention in Clinical Practice recommend using (lifetime) risk to guide preventive treatment intensification. Purpose Updating and systematically recalibrating the SMART-REACH lifetime prediction model for the estimation of lifetime risk of recurrent CVD in patients with established atherosclerotic CVD (ASCVD) to various European and international risk regions. Methods The updated SMART-REACH (i.e., SMART-REACH2) model was derived using data from 9,477 individuals between 40-90 years with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms included in the UCC-SMART cohort in whom 2,090 ASCVD events were observed during a median follow-up of 8.9 years (interquartile range 4.5–14.1). Coefficients for type of CVD, estimated glomerular filtration rate, non-high density lipoprotein cholesterol, systolic blood pressure, duration of CVD, C-reactive protein, current smoking, and presence of diabetes were derived using sex-stratified cause-specific Cox models with age as the time axis, adjusted for the competing risk of non-CVD mortality. Lifetables were used to estimate 10-year and lifetime CVD-risk and CVD-free life expectancy. The SMART-REACH2 model was externally validated in 121,701 patients from the NOR-COR, Nor-COAST, HUNT3, SWEDEHEART, Bialystok PLUS/Polaspire, REACH-EU, and REACH non-EU (Asia, Japan, Latin America, North America) covering 43 countries. The model was recalibrated to specific risk regions based on the expected-observed ratios from representative cohorts. Performance was assessed by calibration of predicted and observed risk and Harrel’s C-statistic for discrimination. Results 16,689ASCVD events were observed in the external validation cohorts. The model was visually well calibrated for the various risk regions. The pooled C-statistic across risk regions was 0.665 [95% confidence interval 0.640-0.691], with adequate performance in the separate regions (Figure 1). Using SMART-REACH2 to estimate potential gain in CVD-free life expectancy upon treatment initiation showed varying projections. For example, two comparable 55-year-old males from the low-risk region and very high-risk region would gain an estimated 2.2 and 3.9 CVD-free life years as a result of smoking cessation (Figure 2). Conclusion(s) By using larger and more contemporary data sources, considering geographical differences, and extending the age range, the updated SMART-REACH2 model provides an improved algorithm for the estimation of lifetime risk and CVD-free life expectancy for individuals with established ASCVD, facilitating shared decision-making for cardiovascular prevention as recommended by the 2021 ESC Prevention of CVD guidelines.C-statistics across global risk regionsCase vignette

Discrimination and calibration are insensitive metrics for comparing the performance of cardiovascular risk prediction models

Abstract Background/Introduction Accurate cardiovascular disease (CVD) risk prediction models can facilitate the identification and cost-effective treatment of high-risk individuals. Discrimination and calibration are the most commonly recommended metrics for evaluating model performance. However, both are population-level measures, and it remains unclear whether these metrics are sufficiently sensitive to assess the performance of models designed for use with individual patients. Purpose Using a real-world dataset, we aimed to compare CVD risk estimates for example individuals (individual-level measures) and discrimination and calibration metrics (population-level measures) from two CVD risk prediction models; one with "age" as the only predictor and one with multiple predictors. Methods We constructed a cohort of almost all New Zealanders without CVD or heart failure, alive and aged 30–79 years in 2014, with follow-up linkage to hospitalisations and mortality until 2018 (N = 2,098,359). We derived two sets of sex-specific Cox regression models to predict 5-year CVD risk. The age-only models included "age" as the only predictor, and the full models used nine pre-defined routinely available CVD risk predictors with interaction terms. We calculated and compared individuals’ 5-year CVD risk from the age-only and full models and assessed model performance using Harrell’s C-statistics and calibration plots. Results Risk estimates for individuals using the two models showed substantial differences. A 65-year-old woman had predicted 5-year risks of 4.9% with the age-only model but 16.1% with the full model; a 74-year-old man had predicted risks of 15.2% and 9.2%, respectively, with age-only and full models (Figure 1). However, the models had similar discrimination and calibration (Figure 2). Age-only models had good discrimination with C-statistics of 0.773 (95% CI: 0.771–0.775) in women and 0.740 (0.738–0.742) in men, and calibrated well in both sexes. The full models had slightly better discrimination (C-statistics: 0.814 [0.812–0.816] in women and 0.769 [0.767–0.771] in men), and very similar calibration to the age-only models in both sexes. Conclusions Age-only models showed good discrimination and were well calibrated, but predicted very different risks in individual case studies compared to models with multiple predictors. This study calls into question the use of discrimination and calibration metrics as the main measures for comparing the performance of different CVD risk prediction models. We recommend that examples of predicted risk for individuals and an assessment of the magnitude and prevalence of cardiovascular predictors should also be considered when comparing the performance of prognostic models.

Proteomics in low CVD risk black women living with HIV: H-ART to Heart Study

Abstract Background 39 million people worldwide are living with HIV (human immunodeficiency virus), acquired immune deficiency syndrome (AIDS)-related deaths have reduced by 51% since the peak in 2004. BWLWH represent 42% of those infected but only 9% are represented in clinical trials. HIV/AIDS has been shown to be associated with the development of heart failure, pulmonary hypertension and myocarditis. Previous studies in asymptomatic PLWH have revealed a high burden of underlying CVD and subclinical disease. The H-ART to Heart study is designed to examine potential signals and pathways of cardiovascular disease (CVD) in asymptomatic BWLWH with no traditional CV risk factors compared to HIV negative controls (-). Methods A cross-sectional study comparing asymptomatic BWLWH aged 35-55yrs (diagnosed >10 yrs, with undetectable viral loads) to HIV negative controls. Black African/Caribbean women without known CV risk factors (hypertension, hyperlipidaemia, diabetes, smoking, inflammatory arthritis, depression, severe mental illness) or hepatitis co-infection were included. Assessment included blood pressure (BP), 10yr CVD risk calculation % (Q-Risk 3), bloods including lipids. A targeted discovery proteomics approach was used to evaluate 92 unique proteins using the O-link Target 96 Cardiovascular II panel. Results 48 participants were recruited (23 BWLWH; 25 controls), mean duration of HIV was 17.6 years, mean duration of ART was 11.5 years, demographic details - Age 47.7± 44.7±; p=0.06, BP 125/77 v 123/79 ; p=0.89; BMI (kg/m²) 30.1±5.1 v 28.51±4.27 p=0.25; cLDL 3.49±1.22 v 2.42±0.74 p<0.02; Total Chol:HDL ratio 3.01±0.98 v 2.77±0.56 p=0.353; Q-Risk 3 1.92%±1.27 v 1.49%±1.12 p=0.219; There were no significant differences in baseline data apart from higher mean cLDL in BWLWH. Of the 92 proteins tested, 9 were significant in BWLWH (Figure 1). As demonstrated by the Heat map. Conclusion Data from our study of asymptomatic low risk BWLWH with no CVD risk factors indicates several pathways (Figure 2.) for further investigation in this previously under investigated vulnerable patient sub group. Whether this finding is of importance in CV risk assessment of BWLWH remains to be seen.

The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review.

Supporting and understanding the health of patients with chronic diseases and cardiovascular disease (CVD) risk is often a major challenge. Health data are often used in providing feedback to patients, and visualization plays an important role in facilitating the interpretation and understanding of data and, thus, influencing patients' behavior. Visual analytics enable efficient analysis and understanding of large datasets in real time. Digital health technologies can promote healthy lifestyle choices and assist in estimating CVD risk. This review aims to present the most-used visualization techniques to estimate CVD risk. In this scoping review, we followed the Joanna Briggs Institute PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The search strategy involved searching databases, including PubMed, CINAHL Ultimate, MEDLINE, and Web of Science, and gray literature from Google Scholar. This review included English-language articles on digital health, mobile health, mobile apps, images, charts, and decision support systems for estimating CVD risk, as well as empirical studies, excluding irrelevant studies and commentaries, editorials, and systematic reviews. We found 774 articles and screened them against the inclusion and exclusion criteria. The final scoping review included 17 studies that used different methodologies, including descriptive, quantitative, and population-based studies. Some prognostic models, such as the Framingham Risk Profile, World Health Organization and International Society of Hypertension risk prediction charts, Cardiovascular Risk Score, and a simplified Persian atherosclerotic CVD risk stratification, were simpler and did not require laboratory tests, whereas others, including the Joint British Societies recommendations on the prevention of CVD, Systematic Coronary Risk Evaluation, and Framingham-Registre Gironí del COR, were more complex and required laboratory testing-related results. The most frequently used prognostic risk factors were age, sex, and blood pressure (16/17, 94% of the studies); smoking status (14/17, 82%); diabetes status (11/17, 65%); family history (10/17, 59%); high-density lipoprotein and total cholesterol (9/17, 53%); and triglycerides and low-density lipoprotein cholesterol (6/17, 35%). The most frequently used visualization techniques in the studies were visual cues (10/17, 59%), followed by bar charts (5/17, 29%) and graphs (4/17, 24%). On the basis of the scoping review, we found that visualization is very rarely included in the prognostic models themselves even though technology-based interventions improve health care worker performance, knowledge, motivation, and compliance by integrating machine learning and visual analytics into applications to identify and respond to estimation of CVD risk. Visualization aids in understanding risk factors and disease outcomes, improving bioinformatics and biomedicine. However, evidence on mobile health's effectiveness in improving CVD outcomes is limited.

From Calculation to Communication: Using Risk Score Calculators to Inform Clinical Decision Making and Facilitate Patient Engagement.

Risk score calculators are a widely developed tool to support clinicians in identifying and managing risk for certain diseases. However, little is known about physicians' applied experiences with risk score calculators and the role of risk score estimates in clinical decision making and patient communication. Physicians providing care in outpatient community-based clinical settings (N = 20) were recruited to participate in semi-structured individual interviews to assess their use of risk score calculators in practice. Two study team members conducted an inductive thematic analysis using a consensus-based coding approach. Participants referenced at least 20 risk score calculators, the most common being the Atherosclerotic Cardiovascular Disease Risk Calculator. Ecological factors related to the clinical system (e.g., time), patient (e.g., receptivity), and physician (e.g., experience) influenced conditions and patterns of risk score calculator use. For example, compared with attending physicians, residents tended to use a greater variety of risk score calculators and with higher frequency. Risk score estimates were generally used in clinical decision making to improve or validate clinical judgment and in patient communication to serve as a motivational tool. The degree to which risk score estimates influenced physician decision making and whether and how these scores were communicated to patients varied, reflecting a nuanced role of risk score calculator use in clinical practice. The theory of planned behavior can help explain how attitudes, beliefs, and norms shape the use of risk score estimates in clinical decision making and patient communication. Additional research is needed to evaluate best practices in the use of risk score calculators and risk score estimates. The risk score calculators and estimates that participants referenced in this study represented a range of conditions (e.g., heart disease, anxiety), levels of model complexity (e.g., probability calculations, scales of severity), and output formats (e.g., point estimates, risk intervals).Risk score calculators that are easily accessed, have simple inputs, and are trusted by physicians appear more likely to be used.Risk score estimates were generally used in clinical decision making to improve or validate clinical judgment and in patient communication to serve as a motivational tool.Risk score estimates helped participants manage the uncertainty and complexity of various clinical situations, yet consideration of the limitations of these estimates was relatively minimal.Developers of risk score calculators should consider the patient- (e.g., response to risk score estimates) and physician- (e.g., training status) related characteristics that influence risk score calculator use in addition that of the clinical system.

Level of Cardiovascular Disease Risk and Associated Factors among Clients on Highly Active Antiretroviral Therapy in Vihiga County, Kenya

Context: HIV/AIDS is still a public health concern globally, especially in sub-Saharan Africa and Kenya. HIV-positive clients are initiated on highly active antiretroviral therapy (HAART) to reduce the multiplication of HIV and improve their immunity. These clients are at an increased cardiovascular disease risk due to a complex interplay of factors, including traditional cardiovascular risk factors such as smoking cigarettes, obesity due to inactivity, and diabetes. Aim: This study sought to determine the level of cardiovascular disease (CVD) risk factors among people living with HIV (PLHIV) on highly active antiretroviral therapy (HAART) in Vihiga County, Kenya. Methods: The study employed a cross-sectional survey design to report baseline survey data for an interventional study on the level of CVD risk factors. The study involved a systematic sample of 211 patients on HAART in six health facilities purposively selected from Vihiga County. Data was collected using the WHO STEPWISE questionnaire from six comprehensive care clinics in Vihiga County from March to July 2022. The World Health Organization-International Society of Hypertension (WHO-ISH) tool AFRI E CHART was used to estimate the cardiovascular risk. Results: The majority (96.68%) of PLWHIV on HAART in Vihiga county had low overall cardiovascular risk as predicted WHO/ISH score. Age (OR = 1.199, 95% CI [1.031, 1.394], p = 0.018) and smoking status (OR = 0.115, 95% CI [0.024, 0.558], p = 0.007) exhibited a significant association with the level of cardiovascular risk. Conclusion: The majority of PLHIV have a low estimated CVD risk. There is a need to prioritize weight management in HIV care, integrating healthy lifestyle behaviors and nutritional support while conducting regular cardiovascular risk assessments, focusing on modifiable factors like smoking. Age-specific interventions can also help mitigate the risk across the different age groups.

Risk prediction of cardiovascular disease in the Asia-Pacific region: the SCORE2 Asia-Pacific model.

To improve upon the estimation of 10-year cardiovascular disease (CVD) event risk for individuals without prior CVD or diabetes mellitus in the Asia-Pacific region by systematic recalibration of the SCORE2 risk algorithm. The sex-specific and competing risk-adjusted SCORE2 algorithms were systematically recalibrated to reflect CVD incidence observed in four Asia-Pacific risk regions, defined according to country-level World Health Organization age- and sex-standardized CVD mortality rates. Using the same approach as applied for the original SCORE2 models, recalibration to each risk region was completed using expected CVD incidence and risk factor distributions from each region. Risk region-specific CVD incidence was estimated using CVD mortality and incidence data on 8,405,574 individuals (556,421 CVD events). For external validation, data from 9,560,266 individuals without previous CVD or diabetes were analysed in 13 prospective studies from 12 countries (350,550 incident CVD events). The pooled C-index of the SCORE2 Asia-Pacific algorithms in the external validation data sets was 0.710 (95% confidence interval [CI] 0.677-0.745). Cohort-specific C-indices ranged from 0.605 (95% CI 0.597-0.613) to 0.840 (95% CI 0.771-0.909). Estimated CVD risk varied several-fold across Asia-Pacific risk regions. For example, the estimated 10-year CVD risk for a 50-year-old non-smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/L, and high-density lipoprotein-cholesterol of 1.3 mmol/L, ranged from 7% for men in low-risk countries to 14% for men in very-high-risk countries, and from 3% for women in low-risk countries to 13% for women in very-high-risk countries. The SCORE2 Asia-Pacific algorithms have been calibrated to estimate 10-year risk of CVD for apparently healthy people in Asia and Oceania, thereby enhancing the identification of individuals at higher risk of developing CVD across the Asia-Pacific region.

General practitioner support needs to implement cardiovascular disease risk assessment and management guidelines: Qualitative interviews.

Previous research identified numerous barriers to general practitioner (GP) use of cardiovascular disease (CVD) risk guidelines, and it is unclear whether these issues have been resolved. This study explored recent GP experiences. Interviews with 18 GPs in an Australian state with relatively few COVID-19 cases in 2021 were transcribed and coded using a framework analysis approach, with data mapped to five previously identified CVD risk assessment strategies: absolute risk focused, absolute risk adjusted, clinical judgement, passive disregard and active disregard. GPs used various CVD risk calculators to inform clinical decision making, but there were concerns about accuracy, the role of extra risk factors and less 'personalised' assessment. GPs addressed these concerns by requesting additional tests, subjectively adjusting the CVD risk assessment to account for extra risk factors and focusing on individual risk factors. Many barriers to CVD risk assessment guidelines remain. GP support is needed to implement revised guidelines.

Short-term impact of cardiovascular screening by traditional risk assessment or coronary artery calcium score on health-related quality of life: the ROBINSCA trial.

Evidence on the impact of screening for cardiovascular diseases (CVDs) on health-related quality of life (HRQoL) is important for policy decisions about screening implementation and to uncover teachable moments to motivate healthy lifestyle choices. It is unknown whether screening by cardiac computed tomography (CT) scan has a stronger impact on HRQoL than screening by traditional risk prediction models. The study aims to investigate differences in HRQoL across the screening process between participants who were randomized to CVD risk estimation by coronary artery calcium score or Systematic COronary Risk Evaluation. A subset of 2687 ROBINSCA participants filled in questionnaires at (T0) randomization, (T1) invitation, (T2) 1-3 days before screening, (T3) 1-3 days after, and (T4) screening result. Generic HRQoL (SF-12; EQ-5D) and anxiety (STAI-6) were measured. We investigated the differences in changes in HRQoL across the screening process with linear mixed models. We found comparable levels of HRQoL at all screening moments for the two intervention groups. Mental health scores were worse at invitation and randomization than at the later time points, irrespective of screening group (all P < 0.001). A result indicating a heightened CVD risk was associated with increased anxiety in the CT screening group. Computed tomography screening for CVD risk has no detrimental impact on HRQoL and anxiety levels compared to screening by traditional risk assessment. Receiving an invitation to screenning or a result implying increased CVD risk could function as teachable moments for high-risk individuals. ROBINSCA trial registration number: NTR6471 in Dutch Trial Register (NTR).

Optimizing Cardiovascular Health: A Comprehensive Review of Risk Assessment Strategies for Primary Prevention.

Cardiovascular disease (CVD) is a leading global health concern, and effective primary prevention strategies are essential to mitigate its impact. This comprehensive review examines current risk assessment strategies for primary prevention of CVD, emphasizing the importance of early identification and intervention to reduce disease incidence. Traditional risk factors such as hypertension, hyperlipidemia, smoking, and lifestyle choices are discussed alongside emerging factors, including genetic predispositions and biomarkers. The review evaluates various risk assessment tools and models, such as the Framingham risk score, atherosclerotic CVD risk calculator, QRISK, and Reynolds risk score, highlighting their methodologies, strengths, and limitations. Additionally, the review explores lifestyle modifications, including dietary changes, physical activity, weight management, smoking cessation, and pharmacological interventions like statins and antihypertensives. Special considerations for different populations, including the elderly, women, and those with a family history of CVD, are addressed. Future directions in cardiovascular risk assessment are also discussed, focusing on technological advancements and personalized medicine. This review aims to enhance the implementation of effective primary prevention measures and improve cardiovascular health outcomes by providing a thorough analysis of risk assessment strategies.

Comparison of Patients Classified as High-Risk between International Cardiovascular Disease Primary Prevention Guidelines.

Background: Cardiovascular disease (CVD) primary prevention guidelines classify people at high risk and recommended for pharmacological treatment based on clinical criteria and absolute CVD risk estimation. Despite relying on similar evidence, recommendations vary between international guidelines, which may impact who is recommended to receive treatment for CVD prevention. Objective: To determine the agreement in treatment recommendations according to guidelines from Australia, England and the United States. Methods: Cross-sectional analysis of the National Health and Nutrition Examination Survey (n = 2647). Adults ≥ 40 years were classified as high-risk and recommended for treatment according to Australia, England and United States CVD prevention guidelines. Agreement in high-risk classification and recommendation for treatment was assessed by Kappa statistic. Results: Participants were middle aged, 49% were male and 38% were white. The proportion recommended for treatment was highest using the United States guidelines (n = 1318, 49.8%) followed by the English guidelines (n = 1276, 48.2%). In comparison, only 26.6% (n = 705) of participants were classified as recommended for treatment according to the Australian guidelines. There was moderate agreement in the recommendation for treatment between the English and United States guidelines (κ = 0.69 [0.64-0.74]). In comparison, agreement in recommendation for treatment was minimal between the Australian and United States guidelines (κ = 0.47 [0.43-0.52]) and weak between the Australian and English guidelines (κ = 0.50 [0.45-0.55]). Conclusions: Despite similar evidence underpinning guidelines, there is little agreement between guidelines regarding the people recommended to receive treatment for CVD prevention. These findings suggest greater consistency in high-risk classification between CVD prevention guidelines may be required.

Perirenal fat thickness contributes to the estimated 10-year risk of cardiovascular disease and atherosclerotic cardiovascular disease in type 2 diabetes mellitus.

Perirenal adipose tissue (PAT) has emerged as a potential therapeutic target for cardiovascular disease (CVD). However, the relationship between increased perirenal fat thickness (PrFT) and CVD risks in individuals with type 2 diabetes mellitus (T2DM) remains uncertain. This study aimed to evaluate the association between PrFT and the estimated 10-year risk of CVD and atherosclerotic cardiovascular disease (ASCVD) in T2DM. The final analysis included 704 participants. PrFT was quantified using non-enhanced computed tomography scans, while the estimated 10-year CVD and ASCVD risk assessments were based on the Framingham and China-PAR equation risk scores, respectively. Multiple regression analysis was employed to analyze the correlation between PrFT and these risk scores. Higher quartiles of PrFT displayed elevated Framingham and China-PAR equation risk scores (P<0.001). After adjusting for cardiometabolic risk factors and visceral fat area, PrFT remained significantly correlated with Framingham equation risk scores in men (β=0.098, P=0.036) and women (β=0.099, P=0.032). Similar correlations were observed between PrFT and China-PAR equation risk scores in men (β=0.106, P=0.009) and women (β=0.108, P=0.007). Moreover, PrFT emerged as an independent variable associated with a high estimated 10-year risk of CVD and ASCVD, with odds ratios (ORs) of 1.14 (95% CI: 1.04-1.25, P=0.016) in men and 1.20 (95% CI: 1.11-1.31, P<0.001) in women for high estimated CVD risk, and ORs of 1.22 (95% CI: 1.08-1.41, P=0.009) in men and 1.34 (95% CI: 1.12-1.60, P<0.001) in women for high estimated 10-year ASCVD risk. Furthermore, restricted cubic spline analyses confirmed a nonlinear relationship between PrFT and high estimated CVD and ASCVD risk in both genders (P for nonlinearity and overall < 0.05). PrFT contributed as an independent variable to the estimated 10-year risk of CVD and ASCVD in T2DM.

Evaluation and management of cardiovascular disease and metabolic syndrome in pediatric-adolescent patients with psoriasis

Psoriasis is strongly associated with cardiovascular disease (CVD) and metabolic syndrome, with pediatric and adolescent patients having an increased risk of each compared to the general population. This increased risk is based on shared underlying genetic and cytokine profiles, as well as similar environmental risks. Many screening guidelines do not address the development of CVD and metabolic syndrome in these predisposed patients, particularly in the adolescent population. These deficits are evidenced by the absence of validated 10-year CVD risk calculators for pediatric and adolescent patients with chronic inflammatory diseases, as well as insufficient screening guidelines for insulin resistance in patients with psoriasis. This manuscript aims to contribute literature regarding allopathic and lifestyle recommendations to the most recent 2017 consensus guideline for the pediatric/adolescent population with psoriasis. PubMed, COCHRANE Database of Systematic Reviews and Google Scholar were reviewed by a panel of clinicians with clinical and research expertise in psoriasis and pediatric subspecialties. The patient-centered Strength of Recommendation Taxonomy (SORT) method was utilized to grade the quality of the evidence available. Updates in management surrounding the role of lipoprotein(a) in lipid panels, recommendations for exercise and weight management to decrease insulin resistance, as well as guidance for heart rate and blood pressure management were discussed. Screening and managing pediatric and adolescent patients with psoriasis for the associated comorbidities of CVD and metabolic syndrome is imperative. Future high-quality studies are needed to strengthen the evidence provided throughout this review, which acts as a framework for clinical practice. Key words: Psoriasis, Comorbidity, Exercise, Treatment, Coronary heart disease

Impact of baseline cardiovascular risk on the outcomes of intensive blood pressure intervention: a post hoc analysis of the China rural hypertension control project

BackgroundThe 2018/2023 ESC/ESH Guidelines underlined a gap how baseline cardiovascular disease (CVD) risk predicted blood pressure (BP) lowering benefits. Further, 2017 ACC/AHA Guideline and 2021 WHO Guideline recommended implementation studies about intensive BP control. Now, to bridge these guideline gaps, we conducted a post hoc analysis to validate whether the baseline CVD risk influences the effectiveness of the intensive BP control strategy, which was designed by China Rural Hypertension Control Project (CRHCP).MethodsThis is a post hoc analysis of CRHCP, among which participants were enrolled except those having CVD history, over 80 years old, or missing data. Subjects were stratified into quartiles by baseline estimated CVD risk and then grouped into intervention and usual care group according to original assignment in CRHCP. Participants in the intervention group received an integrated, multi-faceted treatment strategy, executed by trained non-physician community health-care providers, aiming to achieve a BP target of < 130/80 mmHg. Cox proportional-hazards models were used to estimate the hazard ratios of outcomes for intervention in each quartile, while interaction effect between intervention and estimated CVD risk quartiles was additionally assessed. The primary outcome comprised myocardial infarction, stroke, hospitalization for heart failure, or CVD deaths.ResultsSignificant lower rates of primary outcomes for intervention group compared with usual care for each estimated CVD risk quartile were reported. The hazard ratios (95% confidence interval) in the four quartiles (from Q1 to Q4) were 0.59 (0.40, 0.87), 0.54 (0.40, 0.72), 0.72 (0.57, 0.91) and 0.65 (0.53, 0.80), respectively (all Ps < 0.01). There’s no significant difference of hazard ratios by intervention across risk quartiles (P for interaction = 0.370). Only the relative risk of hypotension, not symptomatic hypotension, was elevated in the intervention group among upper three quartiles.ConclusionsIntensive BP lowering strategy designed by CRHCP group was effective and safe in preventing cardiovascular events independent of baseline CVD risk.Trial registrationThe trial is registered with ClinicalTrials.gov, NCT03527719.

The estimated 10-year risk of first-onset cardiovascular disease in Swedish-born and non-Swedish-born primary healthcare patients

BackgroundSCORE2 has been introduced as an updated risk assessment tool for calculating the 10-year risk of first-onset cardiovascular disease (CVD). However, it does not account for ethnicity or socioeconomic status, known to affect CVD risk. This study investigated and compared SCORE2 estimates in Swedish-born and non-Swedish-born primary healthcare patients. The second aim was to examine if several risk factors could explain differences in CVD risk between the groups.MethodsThis was an observational, cross-sectional study. Data were obtained from the 4D Diabetes Project study, providing a total of 444 participants aged between 40 and 69 years. All participants had complete risk variable data necessary for the SCORE2 tool and no history of previous CVD. Descriptive analysis was conducted to compare distributions of risk factors between Swedes and immigrants and odds ratios of risk factors amongst these two groups in correlation to elevated CVD risk were calculated using logistic regression.ResultsSwedish-born patients showed a significantly higher risk of elevated CVD risk estimates (≥ 2.5% CVD risk increase for individuals < 50 years, respectively, ≥ 5% for individuals aged 51–69) than the non-Swedish-born population, even after adjustment for educational level (OR = 1.61, 95% CI 1.08–2.39). Weekly alcohol consumption implicated a risk of being classified as high risk of CVD risk, regardless of country of birth (OR = 1.93 CI 1.25-3.00). However, Swedes accounted for most of the alcohol consumption (62.6% vs. 19.6%). No other explanatory variable showed significance in association with elevated CVD risk.ConclusionsSwedish-born patients were found to be at higher risk of an increased 10-year CVD risk. The association of alcohol consumption with elevated CVD risk needs to be further studied in longitudinal studies in representative populations, notably among Sweden’s diverse ethnic groups.

Sex inequalities in cardiovascular risk prediction.

Evaluate sex differences in cardiovascular disease (CVD) risk prediction, including use of i) optimal sex-specific risk predictors and ii) sex-specific risk thresholds. Prospective cohort study using UK Biobank, including 121,724 and 182,632 healthy men and women, respectively, aged 38-73 years at baseline. There were 11,899 (men) and 9,110 (women) incident CVD cases (hospitalization or mortality) with median 12.1 years follow-up. We used recalibrated Pooled Cohort Equations (PCE, 7.5% 10-year risk threshold as per US guidelines), QRISK3 (10% 10-year risk threshold as per UK guidelines) and Cox survival models using sparse sex-specific variable sets (via LASSO stability selection) to predict CVD risk separately in men and women. LASSO stability selection included 12 variables in common between men and women, with three additional variables selected for men and one for women. C-statistics were slightly lower for PCE than QRISK3 and models using stably-selected variables, but were similar between men and women: 0.67 [0.66-0.68], 0.70 [0.69-0.71], and 0.71 [0.70-0.72] in men and 0.69 [0.68-0.70], 0.72 [0.71-0.73], and 0.72 [0.71-0.73] in women for PCE, QRISK3 and models using stably-selected variables, respectively. At current clinically implemented risk thresholds, test sensitivity was markedly lower in women than men for all models: at 7.5% 10-year risk, sensitivity was 65.1% and 68.2% in men and 24.0% and 33.4% in women for PCE and models using stably-selected variables, respectively; at 10% 10-year risk, sensitivity was 53.7% and 52.3% in men and 16.8% and 20.2% in women for QRISK3 and models using stably-selected variables, respectively. Specificity was correspondingly higher in women than men. However, the sensitivity in women at 5% 10-year risk threshold increased to 50.1%, 58.5% and 55.7% for PCE, QRISK3 and models using stably-selected variables, respectively. Use of sparse sex-specific variables improved CVD risk prediction compared with PCE but not QRISK3. At current risk thresholds, PCE and QRISK3 work less well for women than men but sensitivity was improved in women using a 5% 10-year risk threshold. Use of sex-specific risk thresholds should be considered in any re-evaluation of CVD risk calculators. Cardiovascular disease (CVD) risk prediction is an important component of clinical risk management and disease prevention. We find that at risk prediction thresholds used by currently applied risk prediction algorithms (PCE 7.5% 10-year risk threshold in the US and QRISK3 10% risk threshold in the UK), sensitivity of these risk prediction tools is markedly lower in women than in men. This sex inequality implies that women are proportionately less likely to receive appropriate clinical management including lipid-lowering therapy. If the risk prediction threshold is lowered to 5% 10-year risk in women, then sensitivity in women is substantially increased.

Implementing absolute cardiovascular disease risk assessment into pathology collection services.

Pathology services represent an ideal setting to integrate absolute cardiovascular disease (CVD) risk estimation when patients attend for routine cholesterol testing. This study aimed to explore the process of implementing CVD risk estimation into point-of-care service delivery by pathology staff to inform future implementation and sustainability. A new service for CVD risk estimation via a self-directed screening station was implemented into 14 pathology service sites across Tasmania, Australia. Before implementation, observations at pathology services (n = 26) and semi-structured interviews were undertaken with 26 pathology staff (88% female, 77% aged 41-60 years) to identify factors that could impact implementation of the service. The process of implementation was then evaluated using participant observations and clinical trial recruitment data. Transcripts and field notes were analysed thematically according to the Medical Research Council Framework and used to develop a programme logic model to understand how the service could be adapted to be successfully integrated into routine workflow at pathology services. Eight key themes were identified during the pre-implementation phase as important factors that could impact upon integration of CVD risk estimation into pathology services. Themes related to factors within the organisation, including available resources, logistics and workflow, as well as having sufficient time to complete the intervention. Additional factors related to the individual motivations of staff, collaborative leadership and patient characteristics. Success of implementation varied among sites, requiring the trialling of different strategies to support uptake of the service and patient recruitment. Implementing CVD risk estimation into point-of-care pathology services required an understanding of the core implementation components specific to each context, and for implementation strategies to be targeted to the individual and organisational contexts. The generated programme logic model may be useful in guiding future implementation endeavours within these services and aiding the selection of apt implementation strategies. ClinicalTrials.gov Identifier: NCT04896021, registered 19/05/2021, https://clinicaltrials.gov/study/NCT04896021.