Cardiovascular Disease Risk Assessment Tools Research Articles

Abstract 4136554: Comparison of short- and long-term atherosclerotic cardiovascular disease risk assessment tools in US young adults

Background: In 2023, the AHA published the PREVENT equations for estimating atherosclerotic cardiovascular disease (ASCVD) risk in adults aged 30-79 years. Research Questions: In young adults aged 20-39 years, does PREVENT improve risk prediction for 10- and 30-year ASCVD compared with existing risk assessment tools recommended in the current US guidelines (i.e., Pooled Cohort Equations [PCEs] and Pencina et al. equations)? Aims: To compare the performance of PREVENT vs. PCEs in predicting 10-year ASCVD, and PREVENT vs. Pencina equations in predicting 30-year ASCVD in young adults. Methods: We analyzed data from two complementary sources: (1) pooled data from two large cohorts: Coronary Artery Risk Development in Young Adults (CARDIA) and Framingham Heart Study (FHS; including the Offspring, Third Generation, Omni 1, and Omni 2 cohorts), and (2) electronic health records from Kaiser Permanente Southern California (KPSC). We included adults aged 20-39 years without a history of ASCVD at baseline. The outcome was incident ASCVD (defined as myocardial infarction, fatal coronary heart disease, fatal and nonfatal stroke) at 10 or 30 years. Model discrimination (Harrell’s C) and mean calibration (estimated as the ratio of predicted to observed event rates) were calculated for the overall population and stratified by sex and race/ethnicity. Results: We included 7,606 young adults (mean age 29 years, 53% female, 30% Black) from the pooled cohorts, and 284,667 (mean age 32 years, 61% female, 8% Black, 46% Hispanic) from KPSC. When predicting 10-year risk, PREVENT improved discrimination in both the pooled cohort (ΔHarrell’s C=0.052; 95% CI: 0.014, 0.095) and KPSC (ΔHarrell’s C=0.039; 95% CI: 0.028, 0.049) compared with the PCEs. PREVENT had good calibration (mean calibration ranged from 0.77 to 1.54), whereas the PCEs overestimated 10-year risk (mean calibration ranged from 1.99 to 4.82). When predicting 30-year risk, discrimination was similar for PREVENT and Pencina equations, but both algorithms underestimated 30-year risk with PREVENT showing worse calibration (mean calibration 0.61). Conclusion: PREVENT improved 10-year ASCVD risk prediction in young adults compared to the PCEs but underestimated 30-year risk.

Assessment of Lifetime Risk for Cardiovascular Disease: Time to Move Forward.

Over the past decades, there has been a notable increase in the risk of Cardiovascular Disease (CVD), even among younger individuals. Policymakers and the health community have revised CVD prevention programs to include younger people in order to take these new circumstances into account. A variety of CVD risk assessment tools have been developed in the past years with the aim of identifying potential CVD candidates at the population level; however, they can hardly discriminate against younger individuals at high risk of CVD.Therefore, in addition to the traditional 10-year CVD risk assessment, lifetime CVD risk assessment has recently been recommended by the American Heart Association/American College of Cardiology and the European Society of Cardiology prevention guidelines, particularly for young individuals. Methodologically, the benefits of these lifetime prediction models are the incorporation of left truncation observed in survival curves and the risk of competing events which are not considered equivalent in the common survival analysis. Thus, lifetime risk data are easily understandable and can be utilized as a risk communication tool for Public Health surveillance. However, given the peculiarities behind these estimates, structural harmonization should be conducted in order to create a sex-, race-specific tool that is sensitive to accurately identifying individuals who are at high risk of CVD. In this review manuscript, we present the most commonly used lifetime CVD risk tools, elucidate several methodological and critical points, their limitations, and the rationale behind their integration into everyday clinical practice.

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.

Using deep learning to detect atherosclerotic plaques on carotid ultrasound images in the UK Biobank

Abstract Background Atherosclerosis is the main underlying cause of cardiovascular disease (CVD). Existing CVD risk assessment tools do not consider the burden of subclinical atherosclerosis. The presence of carotid plaques on carotid ultrasound is a well-known marker of subclinical atherosclerosis. The accumulation of population-scale data on the presence of atherosclerotic plaques, along with deep phenotyping, can allow not only to address the effectiveness of carotid ultrasound in routine clinical practice, but to shed light on the biology of atherosclerosis development. Purpose To develop an effective deep learning model for plaque detection in carotid ultrasound images in the UK Biobank. Methods We used 680 carotid ultrasound images with manually annotated plaques to train a deep learning model employing the YOLOv8 architecture. Different augmentation techniques were used to increase the generalizability of the model. The developed model was applied to automatically detect plaques in raw ultrasound images from 19,507 UK Biobank participants. Logistic and Cox regression were used to explore the associations of plaque presence and number as predicted by the model with conventional CVD risk factors and the risk of future CVD events over follow-up. To explore the genetic architecture of subclinical atherosclerosis, we conducted a genome-wide association study (GWAS) on plaque presence, followed by meta-analysis with data from the CHARGE Consortium. Results Our plaque detection model achieved high classification metrics of accuracy, sensitivity, and specificity (89.3%, 89.5%, and 89.2%, respectively) and detected atherosclerotic plaques in 44% of UK Biobank participants. As expected, plaques were more common among men than women and their prevalence increased linearly with age. Both plaque presence and number of plaques were correlated with conventional CVD risk factors including diabetes, hypertension, and hyperlipidemia, and showed strong associations with future risk of incident CVD events (Hazard Ratio for plaque presence: 1.48 [95%CI: 1.21-1.82], for 2 plaques or more: 1.65, [95% CI: 1.28-2.13]). Incorporating plaque-derived phenotypes minimally altered the C-index of the time-to-event model. GWAS meta-analysis of carotid plaque presence revealed 5 previously known loci, as well as a significant locus including the LPA gene that had not previously been associated with carotid plaque. Conclusion We have developed and implemented an efficient plaque detection model to data from the UK Biobank, which holds significant promise for studying atherosclerosis at a population-wide scale through integration with multiomics data and electronic health records.

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

Prevalence of Cardiovascular Disease and Comparison of Risk Category Predictions of Systemic Coronary Risk Evaluation Score-2 and 4 Other Cardiovascular Disease Risk Assessment Tools Among People Living with Human Immunodefficiency Virus in Türkiye.

Cardiovascular disease (CVD) is a major cause of mortality among people living with HIV (PLWH). We aimed to assess the prevalence of diagnosed CVD and the risk of CVD among PLWH using 5 different tools. This retrospective, cross-sectional study was conducted in 20 tertiary centers in Türkiye between October 2021 and March 2022, among 1425 PLWH aged 40-75 years. About 82.7% were male, with a median age of 51. Web-based tools for each score were used for CVD risk calculations. Of 1425 PLWH enrolled, 10.8% had confirmed CVD, and 1132 had their risk scores evaluated. Of those participants, 42.8% had a higher risk of CVD (10-year risk of atherosclerotic CVD risk score (ASCVD) above 7.5%), and according to the European Society of Cardiology systemic coronary risk evaluation 2 (SCORE2), 71.7% had a high- to very high-risk rate. The agreement between various CVD risk tools varied, with Framingham heart study risk score (FRS), modified FRS, data collection on adverse effects of anti-HIV drugs (DAD), and SCORE2 for high-risk countries showing overall agreement rates of 82%, 94%, 91%, and 36%, respectively, compared to ASCVD. According to the 2021 European and 2019 American Cardiology guidelines, 75.3% and 47.1% of PLWH would be eligible for lipid-lowering agents, respectively. The diagnosed CVD prevalence highlighted the importance of monitoring cardiovascular health and comorbidities in this population. SCORE2 identified a greater number of individuals at high/very high risk compared to other prediction tools. The implementation of CVD prevention through lipid-lowering therapy was far from desired levels in our cohort.

CVD Case Series: Screening and Risk Reduction

Undetected cardiovascular disease is one of the leading causes of complications during pregnancy in the United States. Maternal mortality reviews indicate that lack of suspicion and delays in diagnosis are the primary drivers of CVD-related mortality. Purpose of this study is to examine the effect of implementing the CVD (Cardiovascular Disease) Risk Assessment tool developed by the California Maternal Quality Care Collaborative (CMQCC) team in 2018. Eligibility of patients in the case series was determined through CVD risk screen score of 4 or higher using a standardized stool adopted from the CMQCC. The patient was scored at the point of hospital entry. Factors used in scoring included symptoms, vitals and risk factors. Patients who scored positive were sent for further work up. This included in-depth analysis of other significant clinical factors influencing patient presentation and subsequent management. The CV patient cases presented in this case series illustrate the benefits of early identification and implementation of standardized CVD risk assessment. There are significant benefits in early use of the CV screening tool contributing to mortality risk reduction including continued close antenatal surveillance, postpartum follow-up, and continued collaborative multidisciplinary care. Patients with risk factors underwent continued surveillance and received appropriate specialized follow-up that allowed for improved maternal outcomes. Proper implementation of CVD risk assessment tool for patients who are at-risk of development of CVD in pregnancy can effectively reduce adverse maternal outcomes related to cardiac disease.

CVD Case Series: Screening and Risk Reduction

Undetected cardiovascular disease is one of the leading causes of complications during pregnancy in the United States. Maternal mortality reviews indicate that lack of suspicion and delays in diagnosis are the primary drivers of CVD-related mortality. Purpose of this study is to examine the effect of implementing the CVD (Cardiovascular Disease) Risk Assessment tool developed by the California Maternal Quality Care Collaborative (CMQCC) team in 2018. Eligibility of patients in the case series was determined through CVD risk screen score of 4 or higher using a standardized stool adopted from the CMQCC. The patient was scored at the point of hospital entry. Factors used in scoring included symptoms, vitals and risk factors. Patients who scored positive were sent for further work up. This included in-depth analysis of other significant clinical factors influencing patient presentation and subsequent management. The CV patient cases presented in this case series illustrate the benefits of early identification and implementation of standardized CVD risk assessment. There are significant benefits in early use of the CV screening tool contributing to mortality risk reduction including continued close antenatal surveillance, postpartum follow-up, and continued collaborative multidisciplinary care. Patients with risk factors underwent continued surveillance and received appropriate specialized follow-up that allowed for improved maternal outcomes. Proper implementation of CVD risk assessment tool for patients who are at-risk of development of CVD in pregnancy can effectively reduce adverse maternal outcomes related to cardiac disease.

Cardiovascular Risk Assessment in Pregnancy: Findings From a Large Urban Academic Medical Center [ID 2683572

INTRODUCTION: The goal of this study is to describe patients who screened positive and had true cardiovascular disease (CVD) identified using a risk assessment tool in pregnancy or postpartum. METHODS: This is a prospective validation study of the CVD screening algorithm proposed by the California Maternal Quality Care Collaborative (CMQCC). The CVD risk assessment tool was embedded in the electronic medical record for use by all prenatal care providers with a goal of at least one CVD risk assessment during pregnancy and/or postpartum period. Patients identified with increased risk of CVD received an echocardiogram, electrocardiogram, and cardiology consultation. We describe the assessment tool responses, timing of assessment, cardiac findings, and subsequent interventions. This study was approved by the IRB at Albert Einstein College of Medicine. RESULTS: A total of 1,877 patients were screened as of September 1, 2023, with 148 screening positive for at risk of CVD. Thirty-two patients were found to be true positives including 2 (6.25%) with systolic and/or diastolic dysfunction, 10 (31.3%) with ventricular dilation or hypertrophy, and 23 (71.9%) with a valvular abnormality. CONCLUSION: All 32 true-positive cases were seen by a multidisciplinary cardio-obstetrics team at least once. Ten patients had multiple visits with the cardio-obstetrics team. Three patients were deemed to be of higher risk for decompensation during labor by modified World Health Organization classification and required detailed plans for intrapartum and postpartum management. Seven patients were started on cardiovascular medications. The cardiovascular risk assessment tool proved valuable for identifying and providing individualized care for cardio-obstetric patients.

A Retrospective Five-Year Study of Cardiovascular Risk Assessment and Risk-Based Interventions Among Hypertensive Patients in Nairobi Hospital, Kenya.

Introduction Cardiovascular disease (CVD) is a leading cause of global morbidity and mortality. It is projected that the prevalence of CVD will continue to rise in developing countries, largely driven by an increase in the prevalence of potentially modifiable risk factors. Atherosclerotic cardiovascular risk assessment among individuals with risk factors for CVD but without CVD is an inexpensive and viable strategy in CVD risk stratification and prevention. Despite the known benefits of CVD risk assessment, it is not well established whether physicians/ cardiologists in Kenya comply with the guideline-recommended practice of CVD risk stratification as a prerequisite for initiation of primary CVD preventive interventions. Aims and objectives This study was designed to audit the utilization of cardiovascular risk assessment tools in risk stratification of hypertensive individuals and physician provision of risk-based primary CVD prevention interventions. Results A five-year (2017-2022) retrospective study of patients' medical records was conducted in December 2022 at the PrimeCare cardiology clinic in Nairobi Hospital, Kenya. Data were collected from 373 patients' medical records retrospectively. The data were analyzed using IBMSPSSStatistics for Windows, Version 25 (Released 2017; IBM Corp., Armonk, New York, United States). The mean age of the patients was 60 years with the majority being female (54%). The mean BMI was 30.3 kg/m2 while the mean systolic and diastolic pressurewas 140mmHg and 80mmHg, respectively. Only 2.1% of participants were current smokers. The national or alternative guideline-recommended CVD risk assessment tool was used in 0.3% and 2.4%, respectively. The 10-year CVD risk score was documented in only 1.3%. The majority of the participants (93%) had low CVD risk. Half of the patients were taking statins for primary prevention while > 60% of them had been offered therapeutic lifestyle advice. Conclusion The study revealed poor compliance with guideline-recommended CVD risk assessment tools and documentation of the CVD risk level. However, there was above-average adherence to documentation of therapeutic lifestyle measures for primary CVD prevention.

Agreement between ten-years cardiovascular disease risk assessment tools: An application to Iranian population in Shahedieh Cohort Study

Background and aimCardiovascular risk-prediction models are efficient primary prevention tools to detect high-risk individuals. The study aims to use three tools to estimate the 10-year risk of developing cardiovascular disease (CVD) and investigate their agreement in an Iranian adult population. MethodsThe current cross-sectional study was carried out on 8569 adults between 35 and 70 who participated in the first phase of the Shahedieh cohort study in Yazd, Iran, and were free of CVDs (cardiac ischemia or myocardial infarction or stroke). World Health Organization/International Society of Hypertension (WHO/ISH) chart, Laboratory-Based (LB) and Non-Laboratory-Based (NLB) Framingham Risk Score (FRS) were used to predict the 10-year risk of developing CVD. The agreement across tools was determined by Kappa. ResultsWHO/ISH chart indicated the highest prevalence of low CVD risk for males (96.10%) and females (96.50%), while NLB Framingham had the highest prevalence of high CVD risk for males (19.40%) and females (5.30%). In total, there was substantial agreement between both FRS models (Kappa = o.70), while there was a slight agreement between WHO/ISH and both FRS tools. For under 60 years males and females, substantial agreements were observed between FRS methods (kappa = 0.73 and kappa = 0.68). For males and females over 60 years, this agreement was moderate and substantial, respectively (kappa = 0.54 and kappa = 0.64). WHO/ISH and LB Framingham model had substantial agreement for over 60 years females (kappa = 0.61). ConclusionsFramingham models classified more participants in the high-risk category than WHO/ISH. Due to the lethality of CVDs, categorizing individuals based on FRS can ensure that most of the real high-risk people are detected. Remarkable agreement between FRS methods in all sex-age groups suggested using the NLB Framingham model as a primary screening tool, especially in a shortage of resources condition.

Impact of lifestyle-based interventions on absolute cardiovascular disease risk: a systematic review and meta-analysis.

The objective of the review was to synthesize the evidence of the effectiveness of lifestyle-based interventions for mitigating absolute cardiovascular disease (CVD) risk. Evidence-based guidelines recommend employing an absolute CVD risk score to inform the selection and intensity of preventive interventions. However, studies employing this strategy have reported mixed results, hence the need for a systematic review of the current evidence. Studies published in English that included a lifestyle-based intervention to mitigate CVD risk were considered. Studies were eligible if they enrolled individuals aged ≥18 years, with no history of CVD at baseline. The primary outcome was change in absolute CVD risk score post-intervention. PubMed, Embase, and CINAHL searches were conducted from database inception to February 2022. The trial registers searched included Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrials.gov. Searches for unpublished studies/gray literature were conducted in ProQuest Dissertations and Theses Global, GreyLit Report, and OCLC First Search Proceedings. Two independent reviewers selected the studies and critically appraised them for methodological quality using JBI tools. Data extraction was performed for main outcome variables. Data were presented using separate pooled statistical meta-analysis for quasi-experimental and randomized clinical trials. Random effects models were employed in the analyses. Effect sizes (Cohen's d) were expressed as standardized mean difference at 95% CI. Heterogeneity was assessed via Cochran's Q statistic, and the inconsistency index ( I2 ) was used to describe variability in effect estimates due to heterogeneity rather than sampling error. Twenty-nine studies with a total sample of 5490 adults with no CVD at baseline were included. Fifteen were randomized controlled trials (RCTs; n=3605) and 14 were quasi-experimental studies (n=1885). The studies were conducted in Europe (n=18), the United States (n = 5), Asia (n=3), Mexico (n=1), Canada (n = 1), and Australia (n=1) and included the following lifestyle interventions: diet, physical activity, motivational interviewing, problem-solving, psychological counseling, cardiovascular risk assessment and feedback, health self-management education, and peer support. Six validated absolute CVD risk assessment tools were used to measure the study outcomes, including Framingham, SCORE, Heart Health Risk Assessment Score, Dundee, ASSIGN, and The UK Prospective Diabetes Study risk score. Overall, the methodological rigor of the RCTs and quasi-experimental studies was high. Of the 15 RCTs included in the meta-analysis, lifestyle intervention was favored over control in reducing absolute CVD risk score (Cohen's d = -0.39; P =0.032; Z= -2.14; I2 = 96). Similarly, in the 14 quasi-experimental studies, the absolute CVD risk score after lifestyle intervention was significantly lower compared to baseline (Cohen's d = -0.39; P <0.001; Z= -3.54; I2= 88). RCTs that combined diet and physical activity reported no significant impact on absolute CVD risk score, but those that used either intervention independently reported significant improvement in the absolute CVD risk score. There is evidence supporting the positive impact of lifestyle modification on absolute CVD risk score in adult populations without CVD. Our analysis further suggests that diet and physical activity had significant impact on absolute CVD risk, and a variety of validated screening tools can be used to monitor, evaluate, and communicate changes in absolute risk score after lifestyle modification. A Spanish-language version of the abstract of this review is available [ http://links.lww.com/SRX/A29 ].

Community Health Worker-Led Cardiovascular Disease Risk Screening and Referral for Care and Further Management in Rural and Urban Communities in Rwanda.

Cardiovascular disease (CVD) is a global health issue. Low- and middle-income countries (LMICs) are facing early CVD-related morbidity. Early diagnosis and treatment are an effective strategy to tackle CVD. The aim of this study was to assess the ability of community health workers (CHWs) to screen and identify persons with high risks of CVD in the communities, using a body mass index (BMI)-based CVD risk assessment tool, and to refer them to the health facility for care and follow-up. This was an action research study conducted in rural and urban communities, conveniently sampled in Rwanda. Five villages were randomly selected from each community, and one CHW per each selected village was identified and trained to conduct CVD risk screening using a BMI-based CVD risk screening tool. Each CHW was assigned to screen 100 fellow community members (CMs) for CVD risk and to refer those with CVD risk scores ≥10 (either moderate or high CVD risk) to a health facility for care and further management. Descriptive statistics with Pearson's chi-square test were used to assess any differences between rural and urban study participants vis-à-vis the key studied variables. Spearman's rank coefficient and Cohen's Kappa coefficient were mainly used to compare the CVD risk scoring from the CHWs with the CVD risk scoring from the nurses. Community members aged 35 to 74 years were included in the study. The participation rates were 99.6% and 99.4% in rural and urban communities, respectively, with female predominance (57.8% vs. 55.3% for rural and urban, p-value: 0.426). Of the participants screened, 7.4% had a high CVD risk (≥20%), with predominance in the rural community compared to the urban community (8.0% vs. 6.8%, p-value: 0.111). Furthermore, the prevalence of moderate or high CVD risk (≥10%) was higher in the rural community than in the urban community (26.7% vs. 21.1%, p-value: 0.111). There was a strong positive correlation between CHW-based CVD risk scoring and nurse-based CVD risk scoring in both rural and urban communities, 0.6215 (p-value < 0.001) vs. 0.7308 (p-value = 0.005). In regard to CVD risk characterization, the observed agreement to both the CHW-generated 10-year CVD risk assessment and the nurse-generated 10-year CVD risk assessment was characterized as "fair" in both rural and urban areas at 41.6% with the kappa statistic of 0.3275 (p-value < 001) and 43.2% with kappa statistic of 0.3229 (p-value =0.057), respectively. In Rwanda, CHWs can screen their fellow CMs for CVD risk and link those with high CVD risk to the healthcare facility for care and follow-up. CHWs could contribute to the prevention of CVDs through early diagnosis and early treatment at the bottom of the health system.

Abstract 4361: The plasma proteome as a cardiovascular disease risk assessment tool in cancer survivors

Abstract Cardiovascular disease (CVD) is the most common non-cancer cause of death in cancer survivors and there is an unmet clinical need for easy, accurate, and safe CVD prognostic risk-stratification in adult cancer survivors. This study investigated whether a previously validated 27-plasma protein prognostic model for four-year cardiovascular (CV) events could have such a utility. We used the 27-plasma protein model to predict the four-year risk of a CV event (myocardial infarction, stroke, transient ischemic attack, heart failure hospitalization, death) in 906 participants with a prior history or active malignancy of any type of cancer and compared predictive results to follow-up CV outcome data. The participants were from the BASEL VIII or ARIC (visit 3) studies with a medically adjudicated prior diagnosis of cancer. BASEL VIII is an observational cohort study in patients with suspected coronary artery disease. ARIC is a multi-site cohort study funded by the NHLBI, NCI, and NPCR investigating risk factors for CV health. A subset analysis was conducted to assess model performance in participants with no prior history of CVD and those with stable CVD. The 27-plasma protein model accurately stratified participants into 4 distinct and non-overlapping (95% CI) risk bins. The median time to event for all cancer survivors who had an event in this study was 1.3 years. Observed 4-year event rates across the 4 risk bins (low, medium-low, medium-high, and high) were 11.0%, 17.3%, 31.2% and 60.2%, respectively, which were higher than stratified event rates from our previously published metacohort analyses (5.6%, 11.2%, 20.0% and 43.4%, respectively) in participants with elevated CVD risk factors (e.g., prior events, diabetes, kidney disease and suspected coronary artery disease). The plasma protein model accurately predicted 4-year CVD risk with a C-index of 0.71 (0.68, 0.74) and 4-year AUC of 0.74 (0.69, 0.79). Performance of the protein model was comparable between participants with no prior history of CVD (C-Index: 0.69; AUC: 0.71) and stable CVD (C-Index: 0.69; AUC: 0.72), demonstrating the model accurately predicts CV event risk in cancer survivors regardless of cardiovascular history. Cancer survivors in this cohort can be distinguished with 4-year CV event rates as high as 60.2%, underscoring the urgent need for an easy and accurate risk stratification tool for this population. Prognostic protein testing may provide a novel tool for CVD risk assessment in adult cancer survivors. Citation Format: Emma V. Troth, Matthew Ayala, Jessica Chadwick, Erin Hales, Michael Hinterberg, Jessica N. Kuzma, Clare Paterson, Rachel Ostroff, Joan E. Walter, Christian Mueller, Josef Coresh. The plasma proteome as a cardiovascular disease risk assessment tool in cancer survivors. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4361.

Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores.

This study aims to evaluate the ability of a deep-learning-based cardiovascular disease (CVD) retinal biomarker, Reti-CVD, to identify individuals with intermediate- and high-risk for CVD. We defined the intermediate- and high-risk groups according to Pooled Cohort Equation (PCE), QRISK3, and modified Framingham Risk Score (FRS). Reti-CVD's prediction was compared to the number of individuals identified as intermediate- and high-risk according to standard CVD risk assessment tools, and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess the results. In the UK Biobank, among 48 260 participants, 20 643 (42.8%) and 7192 (14.9%) were classified into the intermediate- and high-risk groups according to PCE, and QRISK3, respectively. In the Singapore Epidemiology of Eye Diseases study, among 6810 participants, 3799 (55.8%) were classified as intermediate- and high-risk group according to modified FRS. Reti-CVD identified PCE-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.7%, 87.6%, 86.5%, and 84.0%, respectively. Reti-CVD identified QRISK3-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.6%, 85.5%, 49.9%, and 96.6%, respectively. Reti-CVD identified intermediate- and high-risk groups according to the modified FRS with a sensitivity, specificity, PPV, and NPV of 82.1%, 80.6%, 76.4%, and 85.5%, respectively. The retinal photograph biomarker (Reti-CVD) was able to identify individuals with intermediate and high-risk for CVD, in accordance with existing risk assessment tools.

Abnormal electrocardiogram or echocardiogram as interim measures for CVD risk stratification in pregnancy and postpartum

Cardiovascular disease (CVD) is the leading cause of maternal mortality in the United States. The diagnosis of CVD is challenging as signs and symptoms of normal pregnancy may mimic CVD. The California Maternal Quality Care Collaborative (CMQCC) CVD risk assessment algorithm was used to help stratify pregnant and postpartum patients into low or high risk for CVD and guide further cardiac testing. We sought to evaluate the intermediate outcomes, i.e., abnormal electrocardiogram (EKG) and echocardiogram, as surrogates for CVD to assess the positive predictive value of the CMQCC tool in patients determined to be at high risk for CVD. Retrospective medical record review of 1,399 patients that underwent CVD risk stratification using the CMQCC algorithm over an 18-month period at a major hospital network in California. The primary outcome was the rate of abnormal EKG or echo, defined as abnormal cardiac structure and/or function, among patients who were determined to be at increased risk for CVD. Of 29 patients identified to be at increased risk, 20 received follow-up testing with EKG or echo within 60 days of the risk assessment. Over half (65%) of the patients were found to have underlying EKG or echo abnormality. Abnormal cardiovascular testing results included findings such as sinus tachycardia (HR > 100 bpm), conduction delays, Wolff Parkinson-White syndrome, left ventricular hypertrophy/diastolic dysfunction, and chamber dilation. Using these results as a surrogate for CVD, the CMQCC risk assessment tool identified 13 cases of previously undiagnosed cardiovascular dysfunction in the study population (Table 1). Use of the CMQCC CVD risk assessment tool provides an opportunity for early diagnosis of CVD that may allow for prompt clinical intervention in addition to patient education and promotion of healthy lifestyle changes. EKG and echo results may be used as intermediate outcomes to assess the positive predictive value of the tool. Future long-term studies should evaluate the benefits of obstetric CVD risk assessment on the prevention of CVD over the life course.

Medication adherence prediction through temporal modelling in cardiovascular disease management

BackgroundChronic conditions place a considerable burden on modern healthcare systems. Within New Zealand and worldwide cardiovascular disease (CVD) affects a significant proportion of the population and it is the leading cause of death. Like other chronic diseases, the course of cardiovascular disease is usually prolonged and its management necessarily long-term. Despite being highly effective in reducing CVD risk, non-adherence to long-term medication continues to be a longstanding challenge in healthcare delivery. The study investigates the benefits of integrating patient history and assesses the contribution of explicitly temporal models to medication adherence prediction in the context of lipid-lowering therapy.MethodsData from a CVD risk assessment tool is linked to routinely collected national and regional data sets including pharmaceutical dispensing, hospitalisation, lab test results and deaths. The study extracts a sub-cohort from 564,180 patients who had primary CVD risk assessment for analysis. Based on community pharmaceutical dispensing record, proportion of days covered (PDC) ge 80 is used as the threshold for adherence. Two years (8 quarters) of patient history before their CVD risk assessment is used as the observation window to predict patient adherence in the subsequent 5 years (20 quarters). The predictive performance of temporal deep learning models long short-term memory (LSTM) and simple recurrent neural networks (Simple RNN) are compared against non-temporal models multilayer perceptron (MLP), ridge classifier (RC) and logistic regression (LR). Further, the study investigates the effect of lengthening the observation window on the task of adherence prediction.ResultsTemporal models that use sequential data outperform non-temporal models, with LSTM producing the best predictive performance achieving a ROC AUC of 0.805. A performance gap is observed between models that can discover non-linear interactions between predictor variables and their linear counter parts, with neural network (NN) based models significantly outperforming linear models. Additionally, the predictive advantage of temporal models become more pronounced when the length of the observation window is increased.ConclusionThe findings of the study provide evidence that using deep temporal models to integrate patient history in adherence prediction is advantageous. In particular, the RNN architecture LSTM significantly outperforms all other model comparators.

Assessment of QRISK3 as a predictor of cardiovascular disease events in type 2 diabetes mellitus.

The risk of cardiovascular disease (CVD) in diabetes mellitus (DM) patients is two- to three-fold higher than in the general population. We designed a 10-year cohort trial in T2DM patients to explore the performance of QRESEARCH risk estimator version 3 (QRISK3) as a CVD risk assessment tool and compared to Framingham Risk Score (FRS). This is a single-center analysis of prospective data collected from 566 newly-diagnosed patients with type 2 DM (T2DM). The risk scores were compared to CVD development in patients with and without CVD. The risk variables of CVD were identified using univariate analysis and multivariate cox regression analysis. The number of patients classified as low risk (<10%), intermediate risk (10%-20%), and high risk (>20%) for two tools were identified and compared, as well as their sensitivity, specificity, positive and negative predictive values, and consistency (C) statistics analysis. Among the 566 individuals identified in our cohort, there were 138 (24.4%) CVD episodes. QRISK3 classified most CVD patients as high risk, with 91 (65.9%) patients. QRISK3 had a high sensitivity of 91.3% on a 10% cut-off dichotomy, but a higher specificity of 90.7% on a 20% cut-off dichotomy. With a 10% cut-off dichotomy, FRS had a higher specificity of 89.1%, but a higher sensitivity of 80.1% on a 20% cut-off dichotomy. Regardless of the cut-off dichotomy approach, the C-statistics of QRISK3 were higher than those of FRS. QRISK3 comprehensively and accurately predicted the risk of CVD events in T2DM patients, superior to FRS. In the future, we need to conduct a large-scale T2DM cohort study to verify further the ability of QRISK3 to predict CVD events.

Etiology and Management of Dyslipidemia in Patients With Cancer.

Patients with cancer are now living longer than ever before due to the growth and expansion of highly effective antineoplastic therapies. Many of these patients face additional health challenges, of which cardiovascular disease (CVD) is the leading contributor to morbidity and mortality. CVD and cancer share common biological mechanisms and risk factors, including lipid abnormalities. A better understanding of the relationship between lipid metabolism and cancer can reveal strategies for cancer prevention and CVD risk reduction. Several anticancer treatments adversely affect lipid levels, increasing triglycerides and/or LDL-cholesterol. The traditional CVD risk assessment tools do not include cancer-specific parameters and may underestimate the true long-term CVD risk in this patient population. Statins are the mainstay of therapy in both primary and secondary CVD prevention. The role of non-statin therapies, including ezetimibe, PCSK9 inhibitors, bempedoic acid and icosapent ethyl in the management of lipid disorders in patients with cancer remains largely unknown. A contemporary cancer patient needs a personalized comprehensive cardiovascular assessment, management of lipid abnormalities, and prevention of late CVD to achieve optimal overall outcomes.

"Healthy Heart, Healthy You": Ten-Year Cardiovascular Disease (CVD) Risk among Adults in Anekal Taluk Hospital, Bangalore Urban District, Karnataka.

Cardiovascular Disease (CVD) is the leading cause of mortality globally. Over 75% of CVD deaths occur in low- and middle-income countries. To assess the 10-year CVD risk among adults aged 30 years and above attending the outpatient department at a Taluk Hospital, Bangalore Urban District, Karnataka. A cross-sectional study was conducted among 217 subjects above 30 years of age attending the hospital. They were selected by consecutive sampling and administered a face-validated interview schedule. WHO/ISH CVD risk assessment tool was used to categorize them into four categories of CVD risk. Additional risk factors like alcohol use and smoking were also assessed. The mean age of the subjects was 55.7 ± 12.3 years. About 65% of the study population had low risk (<10%), 21.2% had mild risk (10%-20%), 9.7% had moderate risk (20%-30%) and 4.1% had high risk (>30%) according to the World Health Organization/International Society of Hypertension (WHO/ISH) CVD risk assessment tool. In the study population, 4.6% were abusing alcohol as per the CAGE questionnaire. The burden of CVD risk among the adults interviewed was high. The WHO/ISH chart is an inexpensive tool that can be used for screening in a regular OPD.