Current Cardiovascular Disease Risk Research Articles

Abstract 14328: Performance of Current Cardiovascular Risk Scores Among the Brazilian Population: Findings From the ELSA-Brasil Study

Background: Cardiovascular disease (CVD) poses a significant health burden in low- and middle-income countries (LMIC), yet existing risk stratification strategies are primarily designed and validated in high-income countries. Objectives: We evaluated the discrimination and calibration of four CVD risk scores - Framingham General Risk (FGR), Pooled Cohort Equations (PCE), World Health Organization CVD score (WHO), and European Society of Cardiology (Score-2) - within the largest Brazilian community-based cohort study (ELSA-Brasil). Methods: We included all individuals aged 40 to 75 years in the prospective ELSA-Brasil without prior CVD who were followed for incident adjudicated CVD events (fatal and non-fatal MI and stroke or CHD death). We compared the mean predicted CVD risk scaled to 4 years with the observed 4-year CVD events across baseline risk groups (<5%, 5-10% and ≥10%.). For the total population and by race/sex group, we assessed discrimination by measuring the area under the ROC curve and calibration by predicted-to-observed risk (P/O) ratios using the Grønnesby-Borgan goodness-of-fit test. Results: 12,742 individuals (52.9±8.1 years, 55.5% female) had 134 events. The model discrimination was acceptable for all scores (AUC>0.7), except for white women (AUC between 0.60 95% CI 0.44-0.76 and 0.64 95% CI 0.51-0.77). All risk scores overestimated the CVD risk in our study population (P/O ratio between 2.29 and 1.15). PCE and FGR scores displayed the highest overestimation (P/O ratio: 2.29 95% CI 2.07-2.51 and 2.19 95% CI 1.88-2.50, respectively), and the recalibrated WHO score for tropical Americas had the best calibration performance (P/O ratio: 1.15 95% CI 0.96-1.34). Conclusion: Current CVD risk scores have good discrimination but poor calibration in this admixed Brazilian population. The recalibrated WHO score showed the best calibration, highlighting the need for improved risk stratification and tailored risk-based prevention strategies in LMICs.

Association between 5-year change in cardiovascular risk and the incidence of atherosclerotic cardiovascular diseases: a multi-cohort study

BackgroundThe influence of the historical cardiovascular risk status on future risk of atherosclerotic cardiovascular disease (ASCVD) is poorly understood. We aimed to investigate the association between 5-year changes in cardiovascular risk and ASCVD incidence.MethodsWe analyzed pooled data from seven community-based prospective cohort studies with up to 20 years of follow-up data. The study populations included White or Black participants aged 40–75 years without prevalent ASCVD. Cardiovascular risk was assessed using the pooled cohort equation and was categorized into non-high (< 20%) or high risk (≥ 20%). Changes in cardiovascular disease (CVD) risk over a 5-year interval were recorded. The main outcome was incident ASCVD.ResultsAmong 11,026 participants (mean [SD] age, 60.0 [8.1] years), 4272 (38.7%) were female and 3127 (28.4%) were Black. During a median follow-up period of 9.9 years, 2560 (23.2%) ASCVD events occurred. In comparison with individuals showing a consistently high CVD risk, participants whose CVD risk changed from non-high to high (hazard ratio [HR], 0.67; 95% confidence interval [CI] 0.59–0.77) or high to non-high (HR, 0.57; 95% CI 0.41–0.80) and those with a consistently non-high risk (HR, 0.33; 95% CI 0.29–0.37) had a lower risk of incident ASCVD. In comparison with individuals showing a consistently non-high CVD risk, participants whose CVD risk changed from high to non-high (HR, 1.74; 95% CI 1.26–2.41) or from non-high to high risk (HR, 2.04; 95% CI 1.84–2.27) and those with a consistently high risk (HR 3.03; 95% CI 2.69–3.42) also showed an increased risk of incident ASCVD.ConclusionsIndividuals with the same current CVD risk status but different historical CVD risks exhibited varying risks of future ASCVD incidents. Dynamic risk evaluation may enable more accurate cardiovascular risk stratification, and decision-making regarding preventive interventions should take the historical risk status into account.Graphical

Perception and Counseling for Cardiac Health in Breast Cancer Survivors.

Context: Breast cancer survivors have increased cardiovascular disease (CVD) risk compared to those without cancer history. CVD is the leading cause of death for breast cancer survivors. Objective: To assess current CVD risk counseling practices and risk perception in breast cancer survivors. Study design and analysis: Interviews conducted with breast cancer survivors. Analysis of categorical data by frequency and quantitative variables by mean and standard deviation. Inductive qualitative analysis performed using NVIVO. Setting: Academic Family Medicine Outpatient Practices Population studied: Breast cancer survivors with an identified primary care provider. Intervention/instrument: Interviews on CVD risk behaviors, risk perception, challenges with risk reduction, and previous history of risk counseling. Outcome measures: Self-reported history of CVD, risk perception, and risk behaviors. Results: The average age of participants (n=19) was 57 with 57% being white and 32% African American. Of interviewed women, 89.5% reported a personal history and 89.5% reported a family history of CVD. Only 52.6% had previously reported receipt of CVD counseling. Primary care providers most commonly provided the counseling (72.7%), however it was additionally provided by oncology (27.3%). Among breast cancer survivors, 31.6% perceived they were at increased CVD risk and 47.5% were unsure of their relative CVD risk compared to women their age. Factors affecting perceived CVD risk included family history, cancer treatments, cardiovascular diagnoses, and lifestyle factors. Video (78.9%) and text messaging (68.4%) were the most highly reported mechanisms through which breast cancer survivors requested to receive additional information and counseling on CVD risk and risk reduction. Commonly reported barriers to adopting risk reduction strategies (such as increasing physical activity) included time, resources, physical limitations, and competing responsibilities. Barriers specific to survivorship status include concerns for immune status during COVID, physical limitations associated with cancer treatment, and psychosocial aspects of cancer survivorship. Conclusions: These data suggest improving the frequency and content of CVD risk reduction counseling is needed. Strategies should identify the best methods for providing CVD counseling, and should address general barriers as well as unique challenges faced by cancer survivors.

Current Cardiovascular Disease Risk Prediction Models Are Not Applicable in MDS Patients: Preliminary Results of a Prospective Observational Single-Centre Cohort Study

Background/aims Cardiovascular disease (CVD) is a leading cause of death in lower-risk Myelodysplastic syndrome (LR-MDS) patients and a shared pathobiology between MDS and CVD has been postulated. However, current evidence emanates only from retrospective cohorts suffering from crucial shortcomings. Prospective annotation can overcome these limitations and delineate the role of MDS as an independent risk factor for CVD. For this reason we conducted a prospective observational single-centre cohort study in LR-MDS patients. Methods Patients underwent thorough evaluation for CVD every 6 months. Cerebrovascular, peripheral and coronary vascular beds were assessed for atherosclerosis by ultrasound and coronary artery calcium (CAC), respectively. Cardiac structure and function was assessed by echocardiography. Multi-Ethnic Study of Atherosclerosis (MESA), Framingham (FRS) risk scores and serum markers of myocardial injury (Serum high-sensitivity troponin T, hsTnT), stress (N-terminal pro-B-type natriuretic peptide, NT-proBNP), and systemic inflammation (high-sensitivity C-reactive protein, hsCRP) were also estimated at each visit. Chi-square, Wilcoxon signed-ranks tests and Pearson's correlation coefficient were used as appropriate. Multiple linear regression was applied for modeling the relationship between a dependent and one or more independent variables. The level of statistical significance was set to P=0.05. Results Table 1 presents baseline characteristics of 26 patients included so far. There were no correlations of CAC, MESA and FRS with either MDS subtype or IPSS-R risk category after adjustment for preexisting CVD, age, sex, and transfusion dependence. In sharp contrast to the general population (Okwuosa, TM et al. JACC 2011), CAC score was not associated with FRS (p=0.7) and was disproportionately increased in low and very low FRS risk patients (Figure 1). Likewise, the number of affected vascular beds (AVB) did not correlate with FRS (p=0,51) (Figure 2), further suggesting that the current CVD risk prediction tools are inaccurate in MDS and arguing for an intrinsic tendency of MDS towards CVD development. A second and a third evaluation was available in 17 and 7 patients, respectively. All patients increased significantly the CAC score both at 6 months (p=0.04) and 1 year (p=0.003). The average increase from baseline was 26.2% at 6 months and 72.6% at 1 year, markedly higher than expected in the general population (McCullough PA et al. Arch Int Med 2009), and was marginally higher in transfusion dependent patients (p=0.049), but not associated with baseline MESA score, FRS, preexisting CVD, exposure to ESAS, statin therapy, sex. Finally, baseline NT-proBNP levels correlated strongly with CAC score P=0.001 (Figure 3) in line with numerous evidence showing that NT-proBNP can potentially serve as a predictor of CVD risk in both MDS and non-MDS individuals. Conclusion To our knowledge this is the first study in LR-MDS patients assessing longitudinally all critical parameters and providing objective measurements of subclinical atherosclerosis in all vascular beds. Our preliminary results indicate that the established CVD prediction models do not operate properly in LR-MDS patients and reinforce the notion of a pro-atherogenic role of MDS. Accurate assessment of CVD risk and prompt detection of subclinical cardiovascular disease in MDS patients will assist clinical decisions on the introduction of intensive monitoring and preventive use of CVD-specific interventions in these individuals. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Abstract 10457: Improved 10-Year Cardiovascular Risk Prediction Combining Serum Metabolites With Traditional Cardiovascular Risk Factors in People With Type 2 Diabetes: Edinburgh Type 2 Diabetes Study

Introduction: Cardiovascular disease (CVD) is the leading cause of death for people with type 2 diabetes (T2D). The predictive performance of existing CVD risk scores in T2D populations is suboptimal. Metabolomics is a promising method of identifying novel biomarkers which might improve risk prediction. We aimed to identify a group of metabolites associated with incident CVD in people with T2D and assess its predictive performance over-and-above a current CVD risk score (QRISK3). Methods: In 1,066 individuals with T2D (Edinburgh Type 2 Diabetes Study), a panel of 228 serum metabolites was measured at baseline and incident CVD events were identified over the subsequent 10 years. We applied 100 repeats of Cox LASSO (least absolute shrinkage and selection operator) to select metabolites with frequency &gt;90% as candidate components for a metabolites-based risk score (MRS). The MRS was calculated using the linear predictor in an unpenalized Cox regression model where only candidate metabolites were included. The predictive performance of the MRS was assessed in relation to a reference score which refitted components of QRISK3 plus prevalent CVD and statin use at baseline. Predictive metrics were internally validated using 500-repeat bootstrapping. Results: In 1,021 available individuals (mean age 67.9 years, 51.7% male), 255 people developed CVD (25.0%) during a median of 10.6 years of follow-up. Twelve metabolites relating to fluid balance, ketone bodies, amino acids, fatty acids, glycolysis and lipoproteins were selected to construct the MRS. C-statistics were 0.673 (95%CI 0.642, 0.704) for the MRS alone and 0.718 (95%CI 0.689, 0.747) for the reference score, increasing slightly to 0.736 (95%CI 0.707, 0.764) for the combination of the two. The improved prediction by combining the MRS with the reference score was internally validated in bootstrapping samples, where the C-statistics for the reference score and the combination were 0.679 (95%CI 0.650, 0.708) vs. 0.699 (95%CI 0.671, 0.728) separately. Conclusions: Metabolomics data might improve predictive performance of current CVD risk scores based on traditional risk factors in people with T2D. External validation is warranted to assess the generalizability of improved CVD risk prediction using the MRS.

Deep Phenotyping and Prediction of Long-term Cardiovascular Disease: Optimized by Machine Learning.

Prediction of cardiovascular disease (CVD) is important in clinical practice. Machine learning (ML) may offer an improved alternative to current CVD risk stratification in individual patients. We aim to identify important predictors and compare ML models with traditional models according to their prediction performance in a large long-term follow-up cohort. The Atherosclerosis Risk in Communities (ARIC) study was designed to study the progression of subclinical disease to cardiovascular events over a 25-year follow-up period. All phenotypic variables at visit 1 were obtained. All-cause death, CVD, and coronary heart disease were the outcomes for analysis. The ML framework involved variable selection using the random survival forest (RSF) method, model building, and 5-fold cross-validation. Model performance was evaluated by discrimination using the Harrell concordance index (C-index), accuracy using the Brier score (BS), and interpretability using the number of variables in the model. Of the 14,842 participants in ARIC, the average age was 54.2 years, with 45.2% male and 26.2% Black participants. Thirty-eight unique variables were selected in the RSF top 20 importance ranking of all 6 outcomes. Aging, hypertension, glucose metabolism, renal function, coagulation, adiposity, and sodium retention dominated the predictions of all outcomes. The ML models outperformed the regression models and established risk scores with a higher C-index, lower BS, and varied interpretability. The ML framework is useful for identifying important predictors of CVD and for developing models with robust performance compared with existing risk models.

Next Generation Risk Markers in Preventive Cardio-oncology.

Cardiovascular disease (CVD) and cancer are the first and second most common causes of death within the USA. It is well established that a diagnosis of cancer increases risk and predisposes the patient to CVD, and vice versa. Despite these associations, cancer is not yet incorporated into current CVD risk calculators, necessitating additional CV risk markers for improved stratification in this at-risk population. In this review, we consider the utility of breast arterial calcification (BAC), coronary artery calcification (CAC), clonal hematopoiesis of indeterminate potential (CHIP), and cancer and cancer treatment in CVD risk assessment. There is evidence supporting the use of BAC, CAC, CHIP, and cancer and cancer treatment for improved CV risk stratification in patients with cancer and those who are being screened for cancer. BAC has been shown to predict CAC, coronary atherosclerotic plaque on coronary CTA, coronary artery stenosis on coronary angiography, and CVD events and accordingly enhances CVD risk stratification beyond the atherosclerotic CVD (ASCVD) risk pooled cohort equation. Additionally, CAC visualized on CT utilized for lung cancer screening, radiation planning, and cancer staging is predictive of coronary artery disease (CAD). Furthermore, CHIP can also be utilized in risk stratification, as the presence of CHIP carries a 40% increase in CV risk independent of traditional CV risk factors. Finally, cancer and many oncologic therapies confer a lifelong increased risk of CVD. We propose an emerging set of tools to be incorporated into the routine continuum of CVD risk assessment in individuals who have been treated for cancer or who are being screened for cancer development. In this review, we discuss BAC, CAC, CHIP, and cancer and cancer treatment as emerging risk markers in cardiovascular health assessment. Their effectiveness in predicting and influencing the burden of CVD will be discussed, along with suggestions on their incorporation into preventive cardio-oncology practice. Future research will focus on short- and long-term CVD outcomes in these populations.

The Relationship between Cardiovascular Risk Scores and Several Markers of Subclinical Atherosclerosis in an Asymptomatic Population.

Background: The current cardiovascular disease (CVD) primary prevention guidelines prioritize risk stratification by using clinical risk scores. However, subclinical atherosclerosis may rest long term undetected. This study aimed to evaluate multiple subclinical atherosclerosis parameters in relation to several CV risk scores in asymptomatic individuals. Methods: A cross-sectional, single-center study included 120 asymptomatic CVD subjects. Four CVD risk scores were computed: SCORE, Framingham, QRISK, and PROCAM. Subclinical atherosclerosis has been determined by carotid intima-media thickness (cIMT), pulse wave velocity (PWV), aortic and brachial augmentation indexes (AIXAo, respectively AIXbr), aortic systolic blood pressure (SBPao), and ankle-brachial index (ABI). Results: The mean age was 52.01 ± 10.73 years. For cIMT—SCORE was more sensitive; for PWV—Framingham score was more sensitive; for AIXbr—QRISK and PROCAM were more sensitive while for AIXao—QRISK presented better results. As for SBPao—SCORE presented more sensitive results. However, ABI did not correlate with any CVD risk score. Conclusions: All four CV risk scores are associated with markers of subclinical atherosclerosis in asymptomatic population, except for ABI, with specific particularities for each CVD risk score. Moreover, we propose specific cut-off values of CV risk scores that may indicate the need for subclinical atherosclerosis assessment.

La presión arterial ambulatoria, en comparación con la medida clínica, mejora notablemente la estratificación del riesgo cardiovascular de Framingham

Introduction and objectivesAmbulatory blood pressure (BP) better predicts cardiovascular disease (CVD) outcomes than office BP measurements (OBPM). Nonetheless, current CVD risk stratification models continue to rely on exclusively daytime OBPM along with traditional factors, eg, age, sex, smoking, dyslipidemia, and/or diabetes. MethodsData from 19 949 participants of the primary care-based Hygia Project assessed by 48-hour ambulatory BP monitoring (ABPM) and without prior CVD events were used to compare the diagnostic accuracy, discrimination, and performance of the original Framingham risk score (RSOFG) and its adjusted version to the Hygia Project study population (RSAFG) with that of a novel CVD risk stratification model constructed by replacing OBPM with ABPM-derived prognostic parameters (RSABPM). ResultsDuring the follow−up, lasting up to 12.7 years, 1854 participants experienced a primary CVD outcome of CVD death, myocardial infarction, coronary revascularization, heart failure, stroke, transient ischemic attack, angina pectoris, or peripheral artery disease. Asleep systolic BP (SBP) mean and sleep−time relative SBP decline were the only joint significant ABPM−derived predictive factors of CVD risk and were therefore used to substitute for in−clinic SBP in the RSABPM model. The RSABPM model, in comparison with the RSOFG and RSAFG models, showed significantly improved calibration, diagnostic accuracy, discrimination, and performance (always P<.001). The RSAFG−derived event−probabilities of 57.3% of the participants were outside the 95% confidence limits of the event probability determined by the RSABPM model. ConclusionsThese collective findings reveal important limitations of CVD risk stratification when based upon OBPM, as in the Framingham score, and corroborate the clinical value of around−the−clock ABPM to properly diagnose true hypertension and reliably stratify CVD vulnerability.

Cardiovascular disease risk stratification by the Framigham score is markedly improved by ambulatory compared with office blood pressure

Introduction and objectivesAmbulatory blood pressure (BP) better predicts cardiovascular disease (CVD) outcomes than office BP measurements (OBPM). Nonetheless, current CVD risk stratification models continue to rely on exclusively daytime OBPM along with traditional factors, eg, age, sex, smoking, dyslipidemia, and/or diabetes. MethodsData from 19 949 participants of the primary care-based Hygia Project assessed by 48-hour ambulatory BP monitoring (ABPM) and without prior CVD events were used to compare the diagnostic accuracy, discrimination, and performance of the original Framingham risk score (RSOFG) and its adjusted version to the Hygia Project study population (RSAFG) with that of a novel CVD risk stratification model constructed by replacing OBPM with ABPM-derived prognostic parameters (RSABPM). ResultsDuring the follow−up, lasting up to 12.7 years, 1854 participants experienced a primary CVD outcome of CVD death, myocardial infarction, coronary revascularization, heart failure, stroke, transient ischemic attack, angina pectoris, or peripheral artery disease. Asleep systolic BP (SBP) mean and sleep−time relative SBP decline were the only joint significant ABPM−derived predictive factors of CVD risk and were therefore used to substitute for in−clinic SBP in the RSABPM model. The RSABPM model, in comparison with the RSOFG and RSAFG models, showed significantly improved calibration, diagnostic accuracy, discrimination, and performance (always P<.001). The RSAFG−derived event−probabilities of 57.3% of the participants were outside the 95% confidence limits of the event probability determined by the RSABPM model. ConclusionsThese collective findings reveal important limitations of CVD risk stratification when based upon OBPM, as in the Framingham score, and corroborate the clinical value of around−the−clock ABPM to properly diagnose true hypertension and reliably stratify CVD vulnerability.

Impact of the 2017 American Heart Association and American College of Cardiology hypertension guideline in aged individuals.

The AHA/ACC-2017 hypertension guideline recommends an age-independent target blood pressure (BP) of less than 130/80 mmHg. In an elderly cohort without established cardiovascular disease (CVD) at baseline, we determined the impact of this guideline on the prevalence of hypertension and associated CVD risk. Nineteen thousand, one hundred and fourteen participants aged at least 65 years from the ASPirin in Reducing Events in the Elderly (ASPREE) study were grouped by baseline BP: 'pre-2017 hypertensive' (BP ≥140/90 mmHg and/or on antihypertensive drugs); 'reclassified hypertensive' (normotensive by pre-2017 guidelines; hypertensive by AHA/ACC-2017 guideline), and 'normotensive' (BP <130 and <80 mmHg). For each group, we evaluated CVD risk factors, predicted 10-year CVD risk using the Atherosclerotic Cardiovascular Disease (ASCVD) risk equation, and reported observed CVD event rates during a median 4.7-year follow-up. Overall, 74.4% (14 213/19 114) were 'pre-2017 hypertensive'; an additional 12.3% (2354/19 114) were 'reclassified hypertensive' by the AHA/ACC-2017 guideline. Of those 'reclassified hypertensive', the majority (94.5%) met criteria for antihypertensive treatment although 29% had no other traditional CVD risk factors other than age. Further, a relatively lower mean 10-year predicted CVD risk (18% versus 26%, P < 0.001) and lower CVD rates (8.9 versus 12.1/1000 person-years, P = 0.01) were observed in 'reclassified hypertensive' compared with 'pre-2017 hypertensive'. Compared with 'normotensive', a hazard ratio (95% confidence interval) for CVD events of 1.60 (1.26-2.02) for 'pre-2017 hypertensive' and 1.26 (0.93-1.71) for 'reclassified hypertensive' was observed. Applying current CVD risk calculators in the elderly 'reclassified hypertensive', as a result of shifting the BP threshold lower, increases eligibility for antihypertensive treatment but documented CVD rates remain lower than hypertensive patients defined by pre2017 BP thresholds.

Abstract P346: Cohort Identification to Harness the Electronic Health Record for Cardiovascular Disease Prediction

Background: Current cardiovascular disease (CVD) risk scores are derived from research cohorts and are particularly inaccurate in women, older adults, and those with missing data. To overcome these limitations, we aimed to develop a cohort to capitalize on the depth and breadth of clinical data within electronic health record (EHR) systems in order to develop next-generation sex-specific risk prediction scores for incident CVD. Methods: All individuals 30 years of age or older residing in Olmsted County, Minnesota on 1/1/2006 were identified. We developed and validated algorithms to define a variety of risk factors, thus building a comprehensive risk profile for each patient. Outcomes including myocardial infarction (MI), percutaneous intervention (PCI), coronary artery bypass graft (CABG), and CVD death were ascertained through 9/30/2017. Results: We identified 73,069 individuals without CVD (Table). We retrieved a total of 14,962,762 lab results; 14,534,466 diagnoses; 17,062,601 services/procedures; 1,236,998 outpatient prescriptions; 1,079,065 heart rate measurements; and 1,320,115 blood pressure measurements. The median number of blood pressure and heart rate measurements ascertained per individuals were 11 and 9, respectively. The five most prevalent conditions were: hypertension, hyperlipidemia, arthritis, depression, and cardiac arrhythmias. During follow-up 1,455 MIs, 1,581 PCI, 652 CABG, and 2,161 CVD-related deaths occurred. Conclusions: We developed a cohort with comprehensive risk profiles and follow-up for each patient. Using sophisticated machine learning approaches, this electronic cohort will be utilized to develop next-generation sex-specific CVD risk prediction scores. These approaches will allow us to address several challenges with use of EHR data including the ability to 1) deal with missing values, 2) assess and utilize a large number of variables without over-fitting, 3) allow non-linear relationships, and 4) use time-to-event data.

Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease.

Chronic kidney disease is common in the general population and associated with excess cardiovascular disease (CVD), but kidney function does not feature in current CVD risk prediction models. We tested three formulae for estimated glomerular filtration rate (eGFR) to determine the most clinically informative for predicting CVD and mortality. Using data from 440,526 participants from UK Biobank, eGFR was calculated using serum creatinine, cystatin C (eGFRcys) and creatinine-cystatin C. Associations of each eGFR with CVD outcome and mortality were compared using Cox models adjusting for atherosclerotic risk factors (per relevant risk scores), and predictive utility was determined by the C-statistic and categorical Net Reclassification Index. We show that eGFRcys is most strongly associated with CVD and mortality, and along with albuminuria adds predictive discrimination to current CVD risk scores, whilst traditional creatinine-based measures are weakly associated with risk. Clinicians should consider measuring eGFRcys as part of cardiovascular risk assessment.

A Cox-Based Risk Prediction Model for Early Detection of Cardiovascular Disease: Identification of Key Risk Factors for the Development of a 10-Year CVD Risk Prediction.

Background and Objective. Current cardiovascular disease (CVD) risk models are typically based on traditional laboratory-based predictors. The objective of this research was to identify key risk factors that affect the CVD risk prediction and to develop a 10-year CVD risk prediction model using the identified risk factors. Methods. A Cox proportional hazard regression method was applied to generate the proposed risk model. We used the dataset from Framingham Original Cohort of 5079 men and women aged 30-62 years, who had no overt symptoms of CVD at the baseline; among the selected cohort 3189 had a CVD event. Results. A 10-year CVD risk model based on multiple risk factors (such as age, sex, body mass index (BMI), hypertension, systolic blood pressure (SBP), cigarettes per day, pulse rate, and diabetes) was developed in which heart rate was identified as one of the novel risk factors. The proposed model achieved a good discrimination and calibration ability with C-index (receiver operating characteristic (ROC)) being 0.71 in the validation dataset. We validated the model via statistical and empirical validation. Conclusion. The proposed CVD risk prediction model is based on standard risk factors, which could help reduce the cost and time required for conducting the clinical/laboratory tests. Healthcare providers, clinicians, and patients can use this tool to see the 10-year risk of CVD for an individual. Heart rate was incorporated as a novel predictor, which extends the predictive ability of the past existing risk equations.

Predictive value of 3d intima-media thickness for coronary calcium score in subjects with intermediate cardiovascular risk

Aim: Current cardiovascular disease (CVD) risk stratification scales drawn up from traditional risk factors have important limitations, especially in intermediate risk population. Surrogate markers of atherosclerosis have been shown to improve the predictability of CVD but they are scarcely available due to their economic cost and poor accessibility.The aim of our study was to compare the predictive capacity of intima-media thickness (IMT) of carotid and femoral arteries measured by 2D and 3D ultrasound (US) and the total plaque volume (TPV) for CACS in a middle-aged sample with intermediate 10-year CVD risk (7.5-20%).

Plaque burden in carotid and femoral arteries measured by 3D versus 2D ultrasound and association with coronary calcium in men with intermedian cardiovascular risk

Aim: Current cardiovascular disease (CVD) risk stratification scales drawn up from traditional risk factors have important limitations, especially in intermediate risk population. Our aim was to evaluate carotid and femoral plaques prevalence, scanned by 3D vs 2D ultrasound (US) for detection of positive coronary artery calcium score (CACS), used as proxy for CVD in a middle-aged sample with intermediate 10-year CVD risk (7.5-20%).

For HIV Patients, Which Cardiovascular Disease Risk Prediction Model Is Accurate?

People with HIV have an elevated number of cardiovascular disease (CVD) risk factors and a higher risk for CVD events. Yet, whether current CVD risk

Cardiovascular disease risk and management in people who experience serious mental illness

Background : People with serious mental illness (SMI), particularly schizophrenia, have significantly reduced life expectancy and a mortality rate two to three times higher than the general population. It is estimated that cardiovascular disease (CVD) accounts for 40 to 50 per cent of this excess mortality. However people diagnosed with SMI are not specifically mentioned in New Zealand guidelines for assessing and managing cardiovascular risk. Aims : We reviewed the literature to identify: 1) The relative increase in CVD risk associated with SMI; 2) The recommended assessment and management of CVD and CVD risk in people with SMI. Methods: We reviewed systematic reviews, meta-analyses and relevant single studies published since 2000 or of particular relevance to the New Zealand context. 102 articles passed abstract screening, 42 met the inclusion criteria and were assessed in full for relevance, 34 papers were found to be relevant. Results : - People who experience SMI have a greater relative risk of CVD than the general population after controlling for other risk factors. - This increased risk is present at an earlier age. - Current CVD risk assessment tools may underestimate the risk for this population. - There are inequities in the assessment and management of CVD risk and CVD for people who experience SMI. - People who experience SMI have a significantly higher risk of dying from CVD than their population counterparts. Conclusions : People with SMI have a greater risk of CVD than their counterparts in the general population. The causal pathways are complex. Established risk factors such as smoking and diet do not fully account for this increased risk. Inequities in assessment and management of CVD risk are likely contributors along with the cardio metabolic effects of psychotropic medication. Ensuring guidelines-concordant cardiovascular risk assessment and management is particularly important for this population. It is also necessary to bear in mind that current risk assessment tools are likely to underestimate the risk. The utility of adapting a general population tool to adjust for mental illness, or of creating a specific tool, should be assessed in a New Zealand context.

Cardiovascular disease screening in general practice: General practitioner recording of common risk factors.

The assessment and screening of individual risk factors for cardiovascular disease (CVD) is a critical component of CVD prevention strategies in general practice (GP). This study sought to examine current CVD risk factor recording as recommended by Australian guidelines for the management of absolute cardiovascular disease risk. A retrospective analysis of routine GP data from 149,306 GP patients aged 45years and above in eastern Melbourne was conducted. Data were collected from GP clinics located throughout inner east Melbourne from July 2011 to September 2014 through the Melbourne East Monash General Practice Database. Recording of primary risk factors necessary for CVD screening as recommended by the national guidelines was assessed, and logistic regression with generalised estimating equations was used to estimate associations between patient characteristics and risk factor recording. 137,976 (92.4%) patients were found to have had at least one risk factor recorded, 62,214 (41.7%) had the Framingham risk factors recorded (lipids, blood pressure, smoking status), while only 1957 (1.3%) had all risk factors recorded. Females (Odds Ratio [OR]: 0.72, 95% Confidence Interval [CI]: 0.65, 0.81), and those identified with diabetes (OR: 12.26, 95% CI: 9.58, 15.68) were less and more likely to have documented risk factors, respectively. Given the role of GPs in the prevention and management of CVD, it is important to improve the identification of high risk patients through screening and recording of CVD risk factors. Strategies are therefore needed to encourage ongoing CVD risk factor recording to support preventive care by GPs.

Personalized Cardiovascular Disease Prediction and Treatment-A Review of Existing Strategies and Novel Systems Medicine Tools.

Cardiovascular disease (CVD) continues to constitute the leading cause of death globally. CVD risk stratification is an essential tool to sort through heterogeneous populations and identify individuals at risk of developing CVD. However, applications of current risk scores have recently been shown to result in considerable misclassification of high-risk subjects. In addition, despite long standing beneficial effects in secondary prevention, current CVD medications have in a primary prevention setting shown modest benefit in terms of increasing life expectancy. A systems biology approach to CVD risk stratification may be employed for improving risk-estimating algorithms through addition of high-throughput derived omics biomarkers. In addition, modeling of personalized benefit-of-treatment may help in guiding choice of intervention. In the area of medicine, realizing that CVD involves perturbations of large complex biological networks, future directions in drug development may involve moving away from a reductionist approach toward a system level approach. Here, we review current CVD risk scores and explore how novel algorithms could help to improve the identification of risk and maximize personalized treatment benefit. We also discuss possible future directions in the development of effective treatment strategies for CVD through the use of genome-scale metabolic models (GEMs) as well as other biological network-based approaches.