Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk estimation for the primary prevention of cardiovascular disease: considerations for appropriate risk prediction model selection

Cardiovascular diseases remain the number one cause of death globally. Cardiovascular disease risk scores are an integral tool in primary prevention, being used to identify individuals at the highest risk and guide the assignment of preventive interventions. Available risk scores differ substantially in terms of the population sample data sources used for their derivation and, consequently, in the absolute risks they assign to individuals. Differences in cardiovascular disease epidemiology between the populations contributing to the development of risk scores, and the target populations in which they are applied, can result in overestimation or underestimation of cardiovascular disease risks for individuals, and poorly informed clinical decisions. Given the wide plethora of cardiovascular disease risk scores available, identification of an appropriate risk score for a target population can be challenging. This Review provides an up-to-date overview of guideline-recommended cardiovascular disease risk scores from global, regional, and national contexts, evaluates their comparative characteristics and qualities, and provides guidance on selection of an appropriate risk score.

Natural Products for Preventing and Managing Anthracycline-Induced Cardiotoxicity: A Comprehensive Review

Doxorubicin (DOX) is an anthracycline anticancer agent that is highly effective in the treatment of solid tumors. Given the multiplicity of mechanisms involved in doxorubicin-induced cardiotoxicity, it is difficult to identify a precise molecular target for toxicity. The findings of a literature review suggest that natural products may offer cardioprotective benefits against doxorubicin-induced cardiotoxicity, both in vitro and in vivo. However, further confirmatory studies are required to substantiate this claim. It is of the utmost importance to direct greater attention towards the intricate signaling networks that are of paramount importance for the survival and dysfunction of cardiomyocytes. Notwithstanding encouraging progress made in preclinical studies of natural products for the prevention of DOX-induced cardiotoxicity, these have not yet been translated for clinical use. One of the most significant obstacles hindering the development of cardioprotective adjuvants based on natural products is the lack of adequate bioavailability in humans. This review presents an overview of current knowledge on doxorubicin DOX-induced cardiotoxicity, with a focus on the potential benefits of natural compounds and herbal preparations in preventing this adverse effect. As literature search engines, the browsers in the Scopus, PubMed, Web of Science databases and the ClinicalTrials.gov register were used.

Risk-stratified analysis of long-term clinical outcomes and cumulative costs in Finnish patients with recent acute coronary syndrome or coronary revascularization: a 5-year real-world study using electronic health records

Aims

Risk assessment is essential in the prevention of cardiovascular disease. In patients with recent acute coronary syndrome (ACS) or coronary revascularization, risk prediction tools, like the European Society of Cardiology guideline recommended SMART-REACH risk score, are increasingly used to predict the risk of recurrent cardiovascular events enabling risk-based personalized prevention. However, little is known about the association between risk stratification and the social and healthcare costs at a population level. This study evaluated the associations between baseline SMART-REACH risk scores, long-term recurrent clinical events, cumulative costs, and post-index event LDL-C goal attainment in patients with recent ACS and/or revascularization.

Methods and results

This retrospective study used electronic health records and was conducted in the North Karelia region of Finland. The study cohort included all patients aged 45-85 admitted to a hospital for ACS or who underwent percutaneous coronary intervention or coronary artery bypass surgery between 1 January 2017 and 31 December 2021. Patients were divided into quintiles based on their baseline SMART-REACH risk scores to examine the associations between predicted 5-year scores and selected clinical and economic outcomes. In addition, simple age-based stratification was conducted as a sensitivity analysis. The observed 5-year cumulative incidence of recurrent events ranged from 20% in the lowest to 41% in the highest risk quintile, whereas the corresponding predicted risks ranged from 13% to 51%, and cumulative 5-year mean total costs per patient ranged from 15 827 to 46 182€, respectively. Both monitoring and attainment of low LDL-C values were suboptimal.

Conclusion

The use of the SMART-REACH quintiles as a population-level risk stratification tool successfully stratified patients into subgroups with different cumulative numbers of recurrent events and cumulative total costs. However, more research is needed to define clinically and economically optimal threshold values for a population-level stratification.

Chemotherapy Related Cardiotoxicity Evaluation-A Contemporary Review with a Focus on Cardiac Imaging

The long-term survivorship of patients diagnosed with cancer has improved due to accelerated detection and rapidly evolving cancer treatment strategies. As such, the evaluation and management of cancer therapy related complications has become increasingly important, including cardiovascular complications. These have been captured under the umbrella term "cardiotoxicity" and include left ventricular dysfunction and heart failure, acute coronary syndromes, valvular abnormalities, pericardial disease, arrhythmia, myocarditis, and vascular complications. These complications add to the burden of cardiovascular disease (CVD) or are risk factors patients with cancer treatment are presenting with. Of note, both pre- and newly developing CVD is of prognostic significance, not only from a cardiovascular perspective but also overall, potentially impacting the level of cancer therapy that is possible. Currently, there are varying recommendations and practices regarding CVD risk assessment and mitigating strategies throughout the cancer continuum. This article provides an overview on this topic, in particular, the role of cardiac imaging in the care of the patient with cancer. Furthermore, it summarizes the current evidence on the spectrum, prevention, and management of chemotherapy-related adverse cardiac effects.

Weekend and holiday admissions for decompensated heart failure and in-hospital mortality. A cumulative effect of "nonworking" days?

INTRODUCTION AND OBJECTIVES

The aim of this study was to analyze whether nonelective admissions in patients with heart failure (HF) on nonworking days (NWD) are associated with higher in-hospital mortality.

METHODS

We conducted a retrospective (2018-2019) observational study of episodes of nonelective admissions in patients aged 18 years and older discharged with a principal diagnosis of HF in acute general hospitals of the Spanish National Health System. NWD at admission were defined as Fridays after 14:00hours, Saturdays, Sundays, and national and regional holidays. In-hospital mortality was analyzed with logistic regression models. The length of NWD was considered as an independent continuous variable. Propensity score matching was used as a sensitivity analysis.

RESULTS

We selected 235 281 episodes of nonelective HF admissions. When the NWD periods were included in the in-hospital mortality model, the increases in in-hospital mortality compared with weekday admission were as follows: 1 NWD day (OR, 1.11; 95%CI, 1.07-1.16); 2 days (OR, 1.13; 95%CI, 1.09-1.17); 3 (OR, 1.16; 95%CI, 1.05-1.27); and ≥4 days (OR, 1.20; 95%CI, 1.09-1.32). There was a statistically significant association between a linear increase in NWD and higher risk-adjusted in-hospital mortality (chi-square trend P=.0002). After propensity score matching, patients with HF admitted on NWD had higher in-hospital mortality than those admitted on weekdays (OR, 1.11; average treatment effect, 12.2% vs 11.1%; P<.001).

CONCLUSIONS

We found an association between admissions for decompensated HF on an NWD and higher in-hospital mortality. The excess mortality is likely not explained by differences in severity. In this study, the "weekend effect" tended to increase as the NWD period became longer.

Validation of the Novel Web-Based Application HUMTELEMED for a Comprehensive Assessment of Cardiovascular Risk Based on the 2021 European Society of Cardiology Guidelines

Background and aims: SCORE2/SCORE2-OP cardiovascular risk (CVR) charts and online calculators do not apply to patients with comorbidities, target organ damage, or atherosclerotic cardiovascular disease, for whom the assessment relies on the conventional consultation of the 2021 ESC guidelines (qualitative approach). To simplify the CVR evaluation, we developed an integrated multi-language and free-to-use web application. This study assessed the agreement between the conventional method versus our web app. Methods: A cross-sectional study was carried out on 1306 consecutive patients aged 40+ years referred to our center for the diagnosis and management of hypertension and dyslipidemia. Two double-blind operators performed the CVR assessment and classified each patient into low-moderate-, high-, and very-high-risk categories by using the conventional method (SCORE2/SCORE2-OP charts and consultation of the 2021 ESC guidelines) and the web app. The Kappa statistics were used to compare the two methods. Results: The mean age was 60.3 ± 11.9 years, with male prevalence (51.4%). Patients in primary prevention were 77.0%. According to the SCORE2/SCORE2-OP charts and 2021 ESC guideline consultation, the CVR was low-moderate in 18.6% (n° 243), high in 36.8% (n° 480), and very high in 44.6% (n° 583). According to the web app, individual CVR was low-moderate in 19.5% (n° 255), high in 35.4% (n° 462), and very high in 45.1% (n° 589). The two methods strongly agreed (Kappa = 0.960, p < 0.001), with a 97.5% concordance. Conclusions: our application has excellent reliability in a broad "real life" population and may help non-expert users and busy clinicians to assess individual CVR appropriately, representing a free-to-use, simple, time-sparing and widely available alternative to the conventional CVR evaluation using SCORE2/SCORE2-OP and 2021 ESC guideline charts.

Spatial analysis of 10-year predicted risk and incident atherosclerotic cardiovascular disease: the CoLaus cohort

Whether cardiovascular risk scores geographically aggregate and inform on spatial development of atherosclerotic cardiovascular diseases (ASCVD) remains unknown. Our aim is to determine the spatial distribution of 10-year predicted cardiovascular risk and ASCVD, and to compare the overlap of the resulting spatial distributions. Using prospective data from the CoLaus|PsyCoLaus cohort study (2003-2021) we computed SCORE2 in participants free from ASCVD. Geographical distributions of predicted risk and events were determined using the Gi* Getis-Ord autocorrelation statistic. 6203 individuals (54% women, mean age 52.5 ± SD 10.7, ASCVD incidence rate 5.7%) were included. We identified clusters of high versus low predicted risk (4%, 6%, respectively) and ASCVD (5%, 5% respectively) at baseline. They persisted at follow-up. Overlap of SCORE2 and ASCVD clusters was marginal. Body-mass index and alcohol consumption explained most of the predicted risk distribution. For ASCVD, high clusters persisted or were reinforced after multivariate adjustment, while low incidence clusters were reduced, multifactorial determinants. Incidence rate of ASCVD was 2.5% higher (IC 95%, 1.4-3.7) in clusters of higher incidence of ASCVD. To develop up-to-date, geographically targeted prevention strategies, there is a need to study novel geographically risk factors affecting ASCVD and to update commonly used prediction models for a population approach.

Recent advances in polygenic scores: translation, equitability, methods and FAIR tools

Polygenic scores (PGS) can be used for risk stratification by quantifying individuals' genetic predisposition to disease, and many potentially clinically useful applications have been proposed. Here, we review the latest potential benefits of PGS in the clinic and challenges to implementation. PGS could augment risk stratification through combined use with traditional risk factors (demographics, disease-specific risk factors, family history, etc.), to support diagnostic pathways, to predict groups with therapeutic benefits, and to increase the efficiency of clinical trials. However, there exist challenges to maximizing the clinical utility of PGS, including FAIR (Findable, Accessible, Interoperable, and Reusable) use and standardized sharing of the genomic data needed to develop and recalculate PGS, the equitable performance of PGS across populations and ancestries, the generation of robust and reproducible PGS calculations, and the responsible communication and interpretation of results. We outline how these challenges may be overcome analytically and with more diverse data as well as highlight sustained community efforts to achieve equitable, impactful, and responsible use of PGS in healthcare.

To What Extent Does Cardiovascular Risk Classification of Patients with Type 2 Diabetes Differ between European Guidelines from 2023, 2021, and 2019? A Cross-Sectional Study

Background and Objectives: Type 2 Diabetes (T2DM) is intricately associated with an increased cardiovascular (CV) risk, highlighting the imperative for tailored intervention in the prevention and management of CV diseases. To assess the CV risk and subsequent interventions in patients with diabetes, the European Society of Cardiology (ESC) has been consistently developing and updating specific guidelines for risk assessment and patient management since 2019. The 2023 risk classification method has significantly changed, introducing a novel probability-based assessment through the implementation of SCORE2-Diabetes instrument. This marks a shift from the risk factor-based classification employed in the 2019 and 2021 methods, representing an innovative approach in risk assessment for individuals with T2DM. This study aims to evaluate the differences in the CV risk classification among hospitalized patients with T2DM using the three proposed methods within the Romanian population, a European population considered to be at very high cardiovascular risk. Materials and Methods: in a consecutive-case, population-based study design, 70 patients hospitalized with T2DM from a European population characterized by very high CV risk were assessed for CV risk using the three proposed methods. The differences between these classifications were subsequently analyzed. Results: In the study group, according to 2023 classification, one patient (1.4%) was classified with moderate CV risk, eight (11.4%) with high cardiovascular risk, and sixty-one (87.2%) with very high cardiovascular risk. A total of 36 patients (51.4%) were classified differently compared to 2021 criteria, the differences being statistically significant (p = 0.047), while 13 (18.6%) were different compared to 2019 criteria, the differences being statistically non-significant (p = 0.731). By comparing the 2021 to the 2019 ESC Guidelines recommendations, 40 patients had a one-step decrease in cardiovascular risk category, from very high to high risk. Conclusions: Most patients included in the analysis were classified as very high CV risk (87.2%). Within a European population characterized by very high CV risk, the SCORE2-Diabetes instrument proves to be a valuable tool, contributing to most step-ups in CV risk classes within the 2023 classification. In a very-high-risk demographic, the 2023 algorithm resulted in different classifications in contrast to the 2021 method but similar classifications observed with the 2019 method.

Development of machine learning-based models to predict 10-year risk of cardiovascular disease: a prospective cohort study

BACKGROUND

Previous prediction algorithms for cardiovascular diseases (CVD) were established using risk factors retrieved largely based on empirical clinical knowledge. This study sought to identify predictors among a comprehensive variable space, and then employ machine learning (ML) algorithms to develop a novel CVD risk prediction model.

METHODS

From a longitudinal population-based cohort of UK Biobank, this study included 473 611 CVD-free participants aged between 37 and 73 years old. We implemented an ML-based data-driven pipeline to identify predictors from 645 candidate variables covering a comprehensive range of health-related factors and assessed multiple ML classifiers to establish a risk prediction model on 10-year incident CVD. The model was validated through a leave-one-center-out cross-validation.

RESULTS

During a median follow-up of 12.2 years, 31 466 participants developed CVD within 10 years after baseline visits. A novel UK Biobank CVD risk prediction (UKCRP) model was established that comprised 10 predictors including age, sex, medication of cholesterol and blood pressure, cholesterol ratio (total/high-density lipoprotein), systolic blood pressure, previous angina or heart disease, number of medications taken, cystatin C, chest pain and pack-years of smoking. Our model obtained satisfied discriminative performance with an area under the receiver operating characteristic curve (AUC) of 0.762±0.010 that outperformed multiple existing clinical models, and it was well-calibrated with a Brier Score of 0.057±0.006. Further, the UKCRP can obtain comparable performance for myocardial infarction (AUC 0.774±0.011) and ischaemic stroke (AUC 0.730±0.020), but inferior performance for haemorrhagic stroke (AUC 0.644±0.026).

CONCLUSION

ML-based classification models can learn expressive representations from potential high-risked CVD participants who may benefit from earlier clinical decisions.

Individual lifetime benefit from low-dose colchicine in patients with chronic coronary artery disease

AIMS

Low-dose colchicine reduces cardiovascular risk in patients with coronary artery disease (CAD), but absolute benefits may vary between individuals. This study aimed to assess the range of individual absolute benefits from low-dose colchicine according to patient risk profile.

METHODS AND RESULTS

The European Society of Cardiology (ESC) guideline-recommended SMART-REACH model was combined with the relative treatment effect of low-dose colchicine and applied to patients with CAD from the Low-Dose Colchicine 2 (LoDoCo2) trial and the Utrecht Cardiovascular Cohort-Second Manifestations of ARTerial disease (UCC-SMART) study (n = 10 830). Individual treatment benefits were expressed as 10-year absolute risk reductions (ARRs) for myocardial infarction, stroke, or cardiovascular death (MACE), and MACE-free life-years gained. Predictions were also performed for MACE plus coronary revascularization (MACE+), using a new lifetime model derived in the REduction of Atherothrombosis for Continued Health (REACH) registry. Colchicine was compared with other ESC guideline-recommended intensified (Step 2) prevention strategies, i.e. LDL cholesterol (LDL-c) reduction to 1.4 mmol/L and systolic blood pressure (SBP) reduction to 130 mmHg. The generalizability to other populations was assessed in patients with CAD from REACH North America and Western Europe (n = 25 812). The median 10-year ARR from low-dose colchicine was 4.6% [interquartile range (IQR) 3.6-6.0%] for MACE and 8.6% (IQR 7.6-9.8%) for MACE+. Lifetime benefit was 2.0 (IQR 1.6-2.5) MACE-free years, and 3.4 (IQR 2.6-4.2) MACE+-free life-years gained. For LDL-c and SBP reduction, respectively, the median 10-year ARR for MACE was 3.0% (IQR 1.5-5.1%) and 1.7% (IQR 0.0-5.7%), and the lifetime benefit was 1.2 (IQR 0.6-2.1) and 0.7 (IQR 0.0-2.3) MACE-free life-years gained. Similar results were obtained for MACE+ and in American and European patients from REACH.

CONCLUSION

The absolute benefits of low-dose colchicine vary between individual patients with chronic CAD. They may be expected to be of at least similar magnitude to those of intensified LDL-c and SBP reduction in a majority of patients already on conventional lipid-lowering and blood pressure-lowering therapy.

Guideline-Based Cardiovascular Risk Assessment Delivered by an mHealth App: Development Study

BACKGROUND

Identifying high-risk individuals is crucial for preventing cardiovascular diseases (CVDs). Currently, risk assessment is mostly performed by physicians. Mobile health apps could help decouple the determination of risk from medical resources by allowing unrestricted self-assessment. The respective test results need to be interpretable for laypersons.

OBJECTIVE

Together with a patient organization, we aimed to design a digital risk calculator that allows people to individually assess and optimize their CVD risk. The risk calculator was integrated into the mobile health app HerzFit, which provides the respective background information.

METHODS

To cover a broad spectrum of individuals for both primary and secondary prevention, we integrated the respective scores (Framingham 10-year CVD, Systematic Coronary Risk Evaluation 2, Systematic Coronary Risk Evaluation 2 in Older Persons, and Secondary Manifestations Of Arterial Disease) into a single risk calculator that was recalibrated for the German population. In primary prevention, an individual's heart age is estimated, which gives the user an easy-to-understand metric for assessing cardiac health. For secondary prevention, the risk of recurrence was assessed. In addition, a comparison of expected to mean and optimal risk levels was determined. The risk calculator is available free of charge. Data safety is ensured by processing the data locally on the users' smartphones.

RESULTS

Offering a risk calculator to the general population requires the use of multiple instruments, as each provides only a limited spectrum in terms of age and risk distribution. The integration of 4 internationally recommended scores allows risk calculation in individuals aged 30 to 90 years with and without CVD. Such integration requires recalibration and harmonization to provide consistent and plausible estimates. In the first 14 months after the launch, the HerzFit calculator was downloaded more than 96,000 times, indicating great demand. Public information campaigns proved effective in publicizing the risk calculator and contributed significantly to download numbers.

CONCLUSIONS

The HerzFit calculator provides CVD risk assessment for the general population. The public demonstrated great demand for such a risk calculator as it was downloaded up to 10,000 times per month, depending on campaigns creating awareness for the instrument.

Cardiovascular risk assessment in patients with antiphospholipid syndrome: a cross-sectional performance analysis of nine clinical risk prediction tools

OBJECTIVES

This study aimed to assess the performance of cardiovascular risk (CVR) prediction models reported by European Alliance of Associations for Rheumatology and European Society of Cardiology recommendations to identify high-atherosclerotic CVR (ASCVR) patients with antiphospholipid syndrome (APS).

METHODS

Six models predicting the risk of a first cardiovascular disease event (first-CVD) (Systematic Coronary Risk Evaluation (SCORE); modified-SCORE; Framingham risk score; Pooled Cohorts Risk Equation; Prospective Cardiovascular Münster calculator; Globorisk), three risk prediction models for patients with a history of prior arterial events (recurrent-CVD) (adjusted Global APS Score (aGAPSS); aGAPSSCVD; Secondary Manifestations of Arterial Disease (SMART)) and carotid/femoral artery vascular ultrasound (VUS) were used to assess ASCVR in 121 APS patients (mean age: 45.8±11.8 years; women: 68.6%). We cross-sectionally examined the calibration, discrimination and classification accuracy of all prediction models to identify high ASCVR due to VUS-detected atherosclerotic plaques, and risk reclassification of patients classified as non high-risk according to first-CVD/recurrent-CVD tools to actual high risk based on VUS.

RESULTS

Spiegelhalter's z-test p values 0.47-0.57, area under the receiver-operating characteristics curve (AUROC) 0.56-0.75 and Matthews correlation coefficient (MCC) 0.01-0.35 indicated moderate calibration, poor-to-acceptable discrimination and negligible-to-moderate classification accuracy, respectively, for all risk models. Among recurrent-CVD tools, SMART and aGAPSSCVD (for non-triple antiphospholipid antibody-positive patients) performed better (z/AUROC/MCC: 0.47/0.64/0.29 and 0.52/0.69/0.29, respectively) than aGAPSS. VUS reclassified 34.2%-47.9% and 40.5%-52.6% of patients classified as non-high-ASCVR by first-CVD and recurrent-CVD prediction models, respectively. In patients aged 40-54 years, >40% VUS-guided reclassification was observed for first-CVD risk tools and >50% for recurrent-CVD prediction models.

CONCLUSION

Clinical CVR prediction tools underestimate actual high ASCVR in APS. VUS may help to improve CVR assessment and optimal risk factor management.

An Update on Inflammation in Atherosclerosis: How to Effectively Treat Residual Risk

PURPOSE

This study reviewed the contribution of inflammation to atherosclerotic cardiovascular disease (ASCVD), which has gained widespread recognition in recent years.

METHODS

This critical review evaluated how recent publications and ongoing clinical trials in atherosclerotic inflammation will affect clinical care.

FINDINGS

Key trials, including CANTOS (Canakinumab Anti-Inflammatory Thrombosis Outcomes Study) with canakinumab (interleukin-1β inhibition), and COLCOT (Colchicine Cardiovascular Outcomes Trial) and LoDoCo2 (Low Dose Colchicine 2) with colchicine, have shown that suppressing inflammation can improve outcomes in ASCVD. Cholesterol crystals play an important role in activating the NOD-, LRR-, and pyrin domain-containing protein 3 inflammasome and subsequent cytokine cascade. Inflammation contributes to significant residual risk after optimal lipid-lowering therapy. High-sensitivity C-reactive protein is a recognized biomarker of residual risk, and newer biomarkers such as the neutrophil to lymphocyte ratio may add additional information. The role of lipoprotein(a) as a proinflammatory agent or possible inflammatory biomarker is under investigation. The contribution of clonal hematopoiesis of indeterminate potential and trained immunity are in the early stages of investigation. Ongoing clinical trials of suppressing inflammation with NOD-, LRR-, and pyrin domain-containing protein 3 inflammasome inhibition (colchicine) and alternative approaches with downstream interleukin-6 ligand inhibition (ziltivekimab) will expand the evidence base for the use of anti-inflammatory agents in ASCVD.

IMPLICATIONS

Based on current evidence and ongoing clinical trials, targeting inflammation alongside optimal lipid lowering is likely to be central to the future treatment of ASCVD. (Clin Ther. 2023;45:XXX-XXX) © 2023 Elsevier HS Journals, Inc.

Personalized lifetime prediction of survival and treatment benefit in patients with heart failure with reduced ejection fraction: The LIFE-HF model

AIMS

Although trials have proven the group-level effectiveness of various therapies for heart failure with reduced ejection fraction (HFrEF), important differences in absolute effectiveness exist between individuals. We developed and validated the LIFEtime-perspective for Heart Failure (LIFE-HF) model for the prediction of individual (lifetime) risk and treatment benefit in patients with HFrEF.

METHODS AND RESULTS

Cox proportional hazards functions with age as the time scale were developed in the PARADIGM-HF and ATMOSPHERE trials (n = 15 415). Outcomes were cardiovascular death, heart failure (HF) hospitalization or cardiovascular death, and non-cardiovascular mortality. Predictors were age, sex, New York Heart Association class, prior HF hospitalization, diabetes mellitus, extracardiac vascular disease, systolic blood pressure, left ventricular ejection fraction, N-terminal pro-B-type natriuretic peptide, and glomerular filtration rate. The functions were combined in life-tables to predict individual overall and HF hospitalization-free survival. External validation was performed in the SwedeHF registry, ASIAN-HF registry, and DAPA-HF trial (n = 51 286). Calibration of 2- to 10-year risk was adequate, and c-statistics were 0.65-0.74. An interactive tool was developed combining the model with hazard ratios from trials to allow estimation of an individual's (lifetime) risk and treatment benefit in clinical practice. Applying the tool to the development cohort, combined treatment with a mineralocorticoid receptor antagonist, sodium-glucose cotransporter 2 inhibitor, and angiotensin receptor-neprilysin inhibitor was estimated to afford a median of 2.5 (interquartile range [IQR] 1.7-3.7) and 3.7 (IQR 2.4-5.5) additional years of overall and HF hospitalization-free survival, respectively.

CONCLUSION

The LIFE-HF model enables estimation of lifelong overall and HF hospitalization-free survival, and (lifetime) treatment benefit for individual patients with HFrEF. It could serve as a tool to improve the management of HFrEF by facilitating personalized medicine and shared decision-making.

Cardiometabolic risk estimation using exposome data and machine learning

BACKGROUND

The human exposome encompasses all exposures that individuals encounter throughout their lifetime. It is now widely acknowledged that health outcomes are influenced not only by genetic factors but also by the interactions between these factors and various exposures. Consequently, the exposome has emerged as a significant contributor to the overall risk of developing major diseases, such as cardiovascular disease (CVD) and diabetes. Therefore, personalized early risk assessment based on exposome attributes might be a promising tool for identifying high-risk individuals and improving disease prevention.

OBJECTIVE

Develop and evaluate a novel and fair machine learning (ML) model for CVD and type 2 diabetes (T2D) risk prediction based on a set of readily available exposome factors. We evaluated our model using internal and external validation groups from a multi-center cohort. To be considered fair, the model was required to demonstrate consistent performance across different sub-groups of the cohort.

METHODS

From the UK Biobank, we identified 5,348 and 1,534 participants who within 13 years from the baseline visit were diagnosed with CVD and T2D, respectively. An equal number of participants who did not develop these pathologies were randomly selected as the control group. 109 readily available exposure variables from six different categories (physical measures, environmental, lifestyle, mental health events, sociodemographics, and early-life factors) from the participant's baseline visit were considered. We adopted the XGBoost ensemble model to predict individuals at risk of developing the diseases. The model's performance was compared to that of an integrative ML model which is based on a set of biological, clinical, physical, and sociodemographic variables, and, additionally for CVD, to the Framingham risk score. Moreover, we assessed the proposed model for potential bias related to sex, ethnicity, and age. Lastly, we interpreted the model's results using SHAP, a state-of-the-art explainability method.

RESULTS

The proposed ML model presents a comparable performance to the integrative ML model despite using solely exposome information, achieving a ROC-AUC of 0.78±0.01 and 0.77±0.01 for CVD and T2D, respectively. Additionally, for CVD risk prediction, the exposome-based model presents an improved performance over the traditional Framingham risk score. No bias in terms of key sensitive variables was identified.

CONCLUSIONS

We identified exposome factors that play an important role in identifying patients at risk of CVD and T2D, such as naps during the day, age completed full-time education, past tobacco smoking, frequency of tiredness/unenthusiasm, and current work status. Overall, this work demonstrates the potential of exposome-based machine learning as a fair CVD and T2D risk assessment tool.

Coronary Atherosclerosis Across the Glycemic Spectrum Among Asymptomatic Adults: The Miami Heart Study at Baptist Health South Florida

BACKGROUND

The contemporary burden and characteristics of coronary atherosclerosis, assessed using coronary computed tomography angiography (CCTA), is unknown among asymptomatic adults with diabetes and prediabetes in the United States. The pooled cohort equations and coronary artery calcium (CAC) score stratify atherosclerotic cardiovascular disease risk, but their association with CCTA findings across glycemic categories is not well established.

METHODS

Asymptomatic adults without atherosclerotic cardiovascular disease enrolled in the Miami Heart Study were included. Participants underwent CAC and CCTA testing and were classified into glycemic categories. Prevalence of coronary atherosclerosis (any plaque, noncalcified plaque, plaque with ≥1 high-risk feature, maximal stenosis ≥50%) assessed by CCTA was described across glycemic categories and further stratified by pooled cohort equations-estimated atherosclerotic cardiovascular disease risk and CAC score. Adjusted logistic regression was used to evaluate the associations between glycemic categories and coronary outcomes.

RESULTS

Among 2352 participants (49.5% women), the prevalence of euglycemia, prediabetes, and diabetes was 63%, 30%, and 7%, respectively. Coronary plaque was more commonly present across worsening glycemic categories (euglycemia, 43%; prediabetes, 58%; diabetes, 69%), and similar pattern was observed for other coronary outcomes. In adjusted analyses, compared with euglycemia, prediabetes and diabetes were each associated with higher odds of any coronary plaque (OR, 1.30 [95% CI, 1.05-1.60] and 1.75 [1.17-2.61], respectively), noncalcified plaque (OR, 1.47 [1.19-1.81] and 1.99 [1.38-2.87], respectively), and plaque with ≥1 high-risk feature (OR, 1.65 [1.14-2.39] and 2.53 [1.48-4.33], respectively). Diabetes was associated with stenosis ≥50% (OR, 3.01 [1.79-5.08]; reference=euglycemia). Among participants with diabetes and estimated atherosclerotic cardiovascular disease risk <5%, 46% had coronary plaque and 10% had stenosis ≥50%. Among participants with diabetes and CAC=0, 30% had coronary plaque and 3% had stenosis ≥50%.

CONCLUSIONS

Among asymptomatic adults, worse glycemic status is associated with higher prevalence and extent of coronary atherosclerosis, high-risk plaque, and stenosis. In diabetes, CAC was more closely associated with CCTA findings and informative in a larger population than the pooled cohort equations.

Linking Cardiovascular Risk With Estradiol Level in Men

Aim      To study the relationship between the cardiovascular risk and the level of estradiol in men of young and middle age. The main group included 71 patients with newly diagnosed hyperestrogenia (HE) (serum estradiol >41.2 pg/ ml). Using pseudorandomization, 68 men with normal estradiol level and age- and body weight index (BWI)-matched with the main group were included into the control group. Anthropometric data, bioimpedance variables, blood pressure (BP), and concentrations of estradiol, testosterone, glucose, and total cholesterol were analyzed in both groups.Results Patients of the main and control groups did not differ in age, BWI, and smoking status. Testosterone concentration was 10.18 nmol/l in the HE group and 12.18 nmol /l in the control group (p=0.006). Systolic BP was 142.0 mm Hg in the HE group and 135.2 mm Hg in the control group (p=0.011); diastolic BP was 90.3 mm Hg in the HE group and 86.2 mm Hg in the control group (p=0.008). Total cholesterol was 5.87 mmol/l in the HE group and 5.33 mmol/l in the control group (p=0.023). Blood glucose did not differ between the groups. The presence of HE in men 2.11 times (р=0.038) increased the probability of arterial hypertension. The intergroup difference by the SCORE scale did not reach statistical significance (р=0.172). BWI, waist and hip circumferences, and bioimpedance body composition parameters did not differ between the groups.Conclusion      In the studied cohort of young and middle-aged men, HE was an independent predictor for the presence of arterial hypertension. There were no significant intergroup differences in the total risk of cardiovascular diseases calculated with the SCORE scale.

Atherosclerotic cardiovascular disease risk stratification and management in type 2 diabetes: review of recent evidence-based guidelines

Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of mortality and morbidity in individuals with type 2 diabetes mellitus (T2DM). Accordingly, several scientific societies have released clinical practice guidelines to assist health professionals in ASCVD risk management in patients with T2DM. However, some recommendations differ from each other, contributing to uncertainty about the optimal clinical management of patients with T2DM and established ASCVD or at high risk for ASCVD. Thus, the purpose of this paper is to discuss recent evidence-based guidelines on ASCVD risk stratification and prevention in patients with T2DM, in terms of disparities and similarities. To close the gap between different guidelines, a multidisciplinary approach involving general practitioners, endocrinologists, and cardiologists may enhance the coordination of diagnosis, therapy, and long-term follow-up of ASCVD in patients with T2DM.

Medical care and biomarker-based assessment of mortality in two cohorts of patients with chronic coronary syndrome 10 years apart

BACKGROUND

This study aimed to describe the characteristics and mortality of two cohorts of patients with chronic coronary syndrome (CCS) recruited with identical study designs in the same rehabilitation clinics but approximately 10 years apart.

METHODS

The KAROLA cohorts included patients with CCS participating in an inpatient cardiac rehabilitation programme in Germany (KAROLA-I: years 1999/2000, KAROLA-II: 2009-2011). Blood samples and information on sociodemographic factors, lifestyle, and medical treatment were collected at baseline, at the end of rehabilitation, and after one year of follow-up. A biomarker-based risk model (ABC-CHD model) and Cox regression analysis were used to evaluate cardiovascular (CV) and non-CV mortality risk.

RESULTS

We included 1130 patients from KAROLA-I (mean age 58.7 years, 84.4% men) and 860 from KAROLA-II (mean age 60.4 years, 83.4% men). Patients in the KAROLA-I cohort had significantly higher concentrations of CV biomarkers and fewer patients were taking CV medications, except for statins. The biomarker-based ABC-CHD model provided a higher estimate of CV death risk for patients in the KAROLA-I cohort (median 3-year risk, 3.8%) than for patients in the KAROLA-II cohort (median 3-year risk, 2.7%, p-value for difference < 0.001). After 10 years of follow-up, 91 (8.1%) patients in KAROLA-I and 45 (5.2%) in KAROLA-II had died from a CV event.

CONCLUSIONS

Advances in disease management over the past 20 years may have led to modest improvements in pharmacological treatment during cardiac rehabilitation and long-term outpatient care for patients with CCS. However, modifiable risk factors such as obesity have increased in the more recent cohort and should be targeted to further improve the prognosis of these patients.

Implications of Social Disadvantage Score in Cardiovascular Outcomes and Risk Assessment: Findings From the Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Social determinants of health contribute to disparate cardiovascular outcomes, yet they have not been operationalized into the current paradigm of cardiovascular risk assessment.

METHODS

Data from the Multi-Ethnic Study of Atherosclerosis, which includes participants from 6 US field centers, were used to create an index of baseline Social Disadvantage Score (SDS) to explore its association with incident atherosclerotic cardiovascular disease (ASCVD) and all-cause mortality and impact on ASCVD risk prediction. SDS, which ranges from 0 to 4, was calculated by tallying the following social factors: (1) household income less than the federal poverty level; (2) educational attainment less than a high school diploma; (3) single-living status; and (4) experience of lifetime discrimination. Cox models were used to examine the association between SDS and each outcome with adjustment for traditional cardiovascular risk factors. Changes in the discrimination and reclassification of ASCVD risk by incorporating SDS into the pooled cohort equations were examined.

RESULTS

A total of 6434 participants (mean age, 61.9±10.2 years; female 52.8%; non-white 60.9%) had available SDS 1733 (26.9%) with SDS 0; 2614 (40.6%) with SDS 1; 1515 (23.5%) with SDS 2; and 572 (8.9%) with SDS ≥3. In total, 775 incident ASCVD events and 1573 deaths were observed over a median follow-up of 17.0 years. Increasing SDS was significantly associated with incident ASCVD and all-cause mortality after adjusting for traditional risk factors (ASCVD: per unit increase in SDS hazard ratio, 1.15 [95% CI, 1.07-1.24]; mortality: per unit increase in SDS hazard ratio, 1.13 [95% CI, 1.08-1.19]). Adding SDS to pooled cohort equations components in a Cox model for 10-year ASCVD risk prediction did not significantly improve discrimination (P=0.208) or reclassification (P=0.112).

CONCLUSIONS

Although SDS is independently associated with incident ASCVD and all-cause mortality, it does not improve 10-year ASCVD risk prediction beyond pooled cohort equations.

External validation of bleeding risk models for the prediction of long-term bleeding risk in patients with established cardiovascular disease

OBJECTIVE

The long-term predictive performance of existing bleeding risk models in patients with various manifestations of cardiovascular disease (CVD) is not well known. This study aims to assess and compare the performance of relevant existing bleeding risk models in estimating the long-term risk of major bleeding in a cohort of patients with established CVD.

METHODS

Seven existing bleeding risk models (PRECISE-DAPT, DAPT, Ducrocq et al, de Vries et al, S₂TOP-BLEED, Intracranial B₂LEED₃S and HAS-BLED) were identified and externally validated in 7,249 patients with established CVD included in the Utrecht Cardiovascular Cohort-second manifestations of arterial disease study. Predictive performance was assessed in terms of discrimination and calibration, both at 10 years and the original prediction horizon of the models. Major bleeding was defined as Bleeding Academic Research Consortium type 3 or 5.

RESULTS

After a median follow-up of 8.4 years (interquartile range 4.5-12.5), a total of 233 (3.2%) major bleeding events occurred. C-statistics for discrimination at 10 years ranged from 0.53 (95%CI 0.49-0.57) to 0.64 (95%CI 0.60-0.68). Calibration plots after recalibration to 10 years showed best agreement between predicted and observed bleeding risk for De Vries et al, S₂TOP-BLEED, DAPT and PRECISE-DAPT.

CONCLUSIONS

The performance of existing bleeding risk models to predict long-term bleeding in patients with CVD varied. Discrimination and calibration were best for the models of de Vries et al, S₂TOP-BLEED, DAPT and PRECISE-DAPT. Of these, recalibrated models requiring the least predictors may be preferred for use to personalize prevention with antithrombotic therapy.

Adjustment of the GRACE score by the stress hyperglycemia ratio improves the prediction of long-term major adverse cardiac events in patients with acute coronary syndrome undergoing percutaneous coronary intervention: A multicenter retrospective study

AIMS

The predictive value of the stress hyperglycemia ratio (SHR) for long-term prognosis in acute coronary syndrome (ACS) is inconsistent. Whether the SHR provides additional prognostic value in addition to the GRACE score in ACS patients undergoing percutaneous coronary intervention (PCI) remains unknown.

METHODS

A development-validation method was adopted to develop an algorithm to adjust the GRACE score using the SHR in ACS patients undergoing PCI from 11 hospitals.

RESULTS

During a median follow-up of 31.33 months, the occurrence of major adverse cardiac events (MACEs), defined as a composite of all-cause mortality and nonfatal myocardial infarction, was more frequent in the patients with a higher level of SHR. The SHR independently predicted long-term MACEs (hazard ratio 3.3479; 95% CI 1.4103-7.9475; P = 0.0062). Adjustment of the GRACE risk by addition of the SHR increased the C-statistic from 0.706 (95% CI: 0.599-0.813) to 0.727 (95% CI: 0.616-0.837) (P < 0.01), with a continuous net reclassification improvement of 30.5% and an integrated discrimination improvement of 0.042 (P < 0.01) in the derivation cohort; and addition of the SHR showed superior discrimination and good calibration in the validation cohort.

CONCLUSIONS

The SHR is an independent predictor of long-term MACEs in ACS patients undergoing PCI and markedly improves the performance of the GRACE score.

Associations of risk factor burden and genetic predisposition with the 10-year risk of atrial fibrillation: observations from a large prospective study of 348,904 participants

BACKGROUND

Understanding the effects of risk factor burden and genetic predisposition on the long-term risk of atrial fibrillation (AF) is important to improve public health initiatives. However, the 10-year risk of AF considering risk factor burden and genetic predisposition is unknown.

METHODS

A total of 348,904 genetically unrelated participants without AF at baseline from the UK were categorized into three groups: index ages 45 years (n = 84,206), 55 years (n=117,520), and 65 years (n=147,178). Optimal, borderline, or elevated risk factor burden was determined by body mass index, blood pressure, diabetes mellitus, alcohol consumption, smoking status, and history of myocardial infarction or heart failure. Genetic predisposition was estimated using the polygenic risk score (PRS), constructed using 165 predefined genetic risk variants. The combined effects of risk factor burden and PRS on the risk of incident AF in 10 years were estimated for each index age. Fine and Gray models were developed to predict the 10-year risk of AF.

RESULTS

The overall 10-year risk of AF was 0.67% (95% CI: 0.61-0.73%) for index age 45 years, 2.05% (95% CI: 1.96-2.13%) for index age 55 years, and 6.34% (95% CI: 6.21-6.46%) for index age 65 years, respectively. An optimal risk factor burden was associated with later AF onset regardless of genetic predisposition and sex (P < 0.001). Significant synergistic interactions were observed for risk factor burden with PRS at each index age (P < 0.05). Participants with an elevated risk factor burden and high PRS had the highest 10-year risk of AF in reference to those who had both an optimal risk factor burden and a low PRS. At younger ages, optimal risk burden and high PRS might also lead to later onset of AF, compared to the joint effect of elevated risk burden and low/intermediate PRS.

CONCLUSIONS

Risk factor burden together with a genetic predisposition is associated with the 10-year risk of AF. Our results may be helpful in selecting high-risk individuals for primary prevention of AF and facilitating subsequent health interventions.

Lipid management in systemic lupus erythematosus according to risk classifiers suggested by the European Society of Cardiology and disease-related risk factors reported by the EULAR recommendations

BACKGROUND

The European Alliance of Associations for Rheumatology recommended that lipid-lowering therapy (LLT) in systemic lupus erythematosus (SLE) should follow general population guidelines. We examined the eligibility for LLT in SLE according to Systematic Coronary Risk Evaluation (SCORE), with and without the addition of vascular ultrasound (VUS) and disease-related features.

METHODS

210 patients with SLE without prior cardiovascular events, diabetes or antiphospholipid syndrome underwent cardiovascular risk assessment with SCORE. LLT eligibility was evaluated in low-risk and moderate-risk patients following European Society of Cardiology (ESC) guidelines. Atherosclerotic plaques on carotid ultrasound (cUS)) and carotid and femoral ultrasound (cfUS), prolonged disease duration (PDD, ≥10 years), failure to achieve lupus low disease activity state (LLDAS_no), cumulative glucocorticoid 'cardiovascular harm' dose (GC_CVH, optimal cut-off to predict ultrasound-detected plaques) and antiphospholipid antibody positivity (aPL_pos) were tested as SCORE risk enhancers for classification ability (phi coefficient) and agreement (Cohen's kappa) using SCORE plus cfUS as a reference modality for LLT eligibility.

RESULTS

Plaques were detected in 9.9% of low-risk cases and 54.6% of moderate-risk cases. SCORE alone would indicate 0% of low-risk patients and 3% of moderate-risk patients for LLT eligibility. According to SCORE+cfUS, 9.9% of low-risk patients and 57.6% of moderate-risk patients, respectively, would be eligible for LLT based on ESC guidelines. Ιn low-risk/moderate-risk patients, phi values for SCORE+PDD, GC_CVH (cut-off ≥11 g), LLDAS_no and aPL_pos in antiplatelet-naïve antiphospholipid antibody-positive (aPL_pos/_APT-) cases were 0.06/0.13, 0.23/0.20, 0.07/0.16 and 0.06/0.33, respectively. Agreement for LLT eligibility to SCORE+cfUS was better for SCORE+PDD in moderate-risk patients and for SCORE+cUS in both groups of patients. SCORE+GC_CVH and SCORE+aPL_pos showed at least fair agreement (kappa ≥0.20) to SCORE+cfUS in low-risk or moderate-risk and in aPL_pos/APT- moderate-risk patients, respectively.

CONCLUSION

Disease-related and VUS features, in addition to SCORE, may help to improve LLT decision making in SLE. GC_CVH and aPL_pos improve LLT eligibility similarly and to a greater degree than PDD or LLDAS_no.

Cardiovascular risk and lifetime benefit from preventive treatment in type 2 diabetes: A post hoc analysis of the CAPTURE study

AIM

To assess the potential gain in the number of life-years free of a (recurrent) cardiovascular disease (CVD) event with optimal cardiovascular risk management (CVRM) and initiation of glucose-lowering agents with proven cardiovascular benefit in people with type 2 diabetes (T2D).

MATERIALS AND METHODS

9,416 individuals with T2D from the CAPTURE study, a non-interventional, cross-sectional, multinational study, were included. The diabetes lifetime-perspective prediction model was used for calculating individual 10-year and lifetime CVD risk. The distribution of preventive medication use was assessed according to predicted CVD risk and stratified for history of CVD. For the estimation of absolute individual benefit from lifelong preventive treatment, including optimal CVRM and the addition of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and sodium-glucose co-transporter-2 inhibitors (SGLT-2is), the model was combined with treatment effects from current evidence.

RESULTS

GLP-1 RA or SGLT-2i use did not greatly differ between patients with and without CVD history, while use of blood pressure-lowering medication, statins and aspirin was more frequent in patients with CVD. Mean (standard deviation [SD]) lifetime benefit from optimal CVRM was 3.9 (3.0) and 1.3 (1.9) years in patients with and without established CVD, respectively. Further addition of a GLP-1 RA and an SGLT-2i in patients with CVD gave an added mean (SD) lifetime benefit of 1.2 (0.6) years.

CONCLUSIONS

Life-years gained free of (recurrent) CVD by optimal CVRM and the addition of a GLP-1 RA or aSGLT-2i is dependent on baseline CVD status. These results aid individualizing prevention and promote shared decision-making in patients with T2D.

Cost-Effectiveness of the CNIC-Polypill Strategy Compared With Separate Monocomponents in Secondary Prevention of Cardiovascular and Cerebrovascular Disease in Portugal: The MERCURY Study

Background: Cardiovascular (CV) diseases remain a leading and costly cause of death globally. Patients with previous CV events are at high risk of recurrence. Secondary prevention therapies improve CV risk factor control and reduce disease costs. Objectives: To assess the cost-effectiveness of a CV polypill strategy (CNIC-Polypill) compared with the loose combination of monocomponents to improve the control of CV risk factors in patients with previous coronary heart disease or stroke. Methods: A Markov model cost-utility analysis was developed using 4 health states, SMART risk equation, and 3-month cycles for year 1 and annual cycles thereafter, over a lifetime horizon from the perspective of the National Health System in Portugal (base case). The NEPTUNO study, Portuguese registries, mortality tables, official reports, and the literature were consulted to define effectiveness, epidemiological costs, and utility data. Outcomes were costs (estimated in 2020 euros) per life-year (LY) and quality-adjusted LY (QALY) gained. A 4% discount rate was applied. Alternative scenarios and one-way and probabilistic sensitivity analyses tested the consistency and robustness of results. Results: The CNIC-Polypill strategy in secondary prevention provides more LY and QALY, at a higher cost, than monocomponents. The incremental cost-utility ratio is €1557/QALY gained. Assuming a willingness-to-pay threshold of €30 000/QALY gained, there is a 79.7% and a 44.4% probability of the CNIC-Polypill being cost-effective and cost-saving, respectively, compared with the loose combination of monocomponents. Results remain consistent in the alternative scenarios and robust in the sensitivity analyses. Discussion: The model reflects increments in the number of years patients would live and in quality of life with the CNIC-Polypill. The clinical effectiveness of the CNIC-Polypill strategy initially demonstrated in the NEPTUNO study has been recently corroborated in the SECURE trial. The incremental cost of the CNIC-Polypill strategy emerges slightly above the comparator, but willingness-to-pay estimates and sensitivity analyses indicate that the CNIC-Polypill strategy is consistently cost-effective compared with monocomponents and remains within acceptable affordability margins. Conclusion: The CNIC-Polypill is a cost-effective secondary prevention strategy. In patients with histories of coronary heart disease or stroke, the CNIC-Polypill more effectively controls CV risk factors compared with monocomponents.

EURObservational Research Programme: a bibliometric assessment of its scientific output

AIMS

Given the lack of reliable observational data, a network of volunteer centres, and standardized methodological procedures, the European Society of Cardiology EURObservational Research Programme (EORP) was set up to provide a better understanding of real-world cardiovascular care and outcomes. We aimed to evaluate the scientific impact of EORP using a bibliometric approach.

METHODS AND RESULTS

We collected data for each individual publication and for each individual journal with at least one EORP publication. Bibliometric indicators evaluating research performance were categorized into those evaluating EORP publications (publication-based indicators) and those assessing the journals where those papers were published (journal-based indicators). During the first ∼11 years since its inception, we found that EORP produced 189 publications, with most published in journals in the first quartile (60.9%) or the second quartile (33.5%) of the Web of Science Journal Citation Report. The total number of citations to EORP publications was 9630 (average citation per publication of 51, h-index of 54, and 29 EORP publications with ≥100 citations). Of EORP publications, 20 had an Altmetric Attention Score >50 and 9 had a score >100. A total of 52 EORP papers have been cited 65 times in ESC Clinical Practice Guidelines between 2013 and 2021.

CONCLUSION

EORP registries have contributed to impactful scientific knowledge. The high-quality metrics highlight the relevance of the EORP international cardiovascular registries to the academic community. Efforts are needed to support this, and other programmes aimed at delivering real-world evidence from independent patient data of cardiovascular care and outcomes across multiple geographies.

Cathepsin S Levels and Survival Among Patients With Non-ST-Segment Elevation Acute Coronary Syndromes

BACKGROUND

Patients with non-ST-segment elevation acute coronary syndromes (NSTE-ACS) are at high residual risk for long-term cardiovascular (CV) mortality. Cathepsin S (CTSS) is a lysosomal cysteine protease with elastolytic and collagenolytic activity that has been involved in atherosclerotic plaque rupture.

OBJECTIVES

The purpose of this study was to determine the following: 1) the prognostic value of circulating CTSS measured at patient admission for long-term mortality in NSTE-ACS; and 2) its additive value over the GRACE (Global Registry of Acute Coronary Events) risk score.

METHODS

This was a single-center cohort study, consecutively recruiting patients with adjudicated NSTE-ACS (n = 1,112) from the emergency department of an academic hospital. CTSS was measured in serum using enzyme-linked immunosorbent assay. All-cause mortality at 8 years was the primary endpoint. CV death was the secondary endpoint.

RESULTS

In total, 367 (33.0%) deaths were recorded. CTSS was associated with increased risk of all-cause mortality (HR for highest vs lowest quarter of CTSS: 1.89; 95% CI: 1.34-2.66; P < 0.001) and CV death (HR: 2.58; 95% CI: 1.15-5.77; P = 0.021) after adjusting for traditional CV risk factors, high-sensitivity C-reactive protein, left ventricular ejection fraction, high-sensitivity troponin-T, revascularization and index diagnosis (unstable angina/ non-ST-segment elevation myocardial infarction). When CTSS was added to the GRACE score, it conferred significant discrimination and reclassification value for all-cause mortality (Delta Harrell's C: 0.03; 95% CI: 0.012-0.047; P = 0.001; and net reclassification improvement = 0.202; P = 0.003) and CV death (AUC: 0.056; 95% CI: 0.017-0.095; P = 0.005; and net reclassification improvement = 0.390; P = 0.001) even after additionally considering high-sensitivity troponin-T and left ventricular ejection fraction.

CONCLUSIONS

Circulating CTSS is a predictor of long-term mortality and improves risk stratification of patients with NSTE-ACS over the GRACE score.

Achievements of primary prevention targets in individuals with high risk of cardiovascular disease: an 8-year follow-up of the Tromsø study

Aims

To study change over 8 years in cardiovascular risk, achievement of national guideline-based treatment targets of lipids, blood pressure (BP) and smoking in primary prevention of cardiovascular disease (CVD), medication use, and characteristics associated with target achievement among individuals with high CVD risk in a general population.

Methods and results

We followed 2524 women and men aged 40-79 years with high risk of CVD attending the population-based Tromsø study in 2007-08 (Tromsø6) to their participation in the next survey in 2015-16 (Tromsø7). We used descriptive statistics and regression models to study change in CVD risk and medication use, and characteristics associated with treatment target achievement. In total, 71.4% reported use of BP- and/or lipid-lowering medication at second screening. Overall, CVD risk decreased during follow-up, with a larger decrease among medication users compared with non-users. Treatment target achievement was 31.0% for total cholesterol <5 mmol/L, 27.3% for LDL cholesterol <3 mmol/L, 43.4% for BP <140/90 (<135/85 if diabetes) mmHg, and 85.4% for non-smoking. A total of 9.8% reached all treatment targets combined. Baseline risk factor levels and current medication use had the strongest associations with treatment target achievement.

Conclusion

We found an overall improvement in CVD risk factors among high-risk individuals over 8 years. However, guideline-based treatment target achievement was relatively low for all risk factors except smoking. Medication use was the strongest characteristic associated with achieving treatment targets. This study has demonstrated that primary prevention of CVD continues to remain a major challenge.

Serum PSA-based early detection of prostate cancer in Europe and globally: past, present and future

In the pre-PSA-detection era, a large proportion of men were diagnosed with metastatic prostate cancer and died of the disease; after the introduction of the serum PSA test, randomized controlled prostate cancer screening trials in the USA and Europe were conducted to assess the effect of PSA screening on prostate cancer mortality. Contradictory outcomes of the trials and the accompanying overdiagnosis resulted in recommendations against prostate cancer screening by organizations such as the United States Preventive Services Task Force. These recommendations were followed by a decline in PSA testing and a rise in late-stage diagnosis and prostate cancer mortality. Re-evaluation of the randomized trials, which accounted for contamination, showed that PSA-based screening does indeed reduce prostate cancer mortality; however, the debate about whether to screen or not to screen continues because of the considerable overdiagnosis that occurs using PSA-based screening. Meanwhile, awareness among the population of prostate cancer as a potentially lethal disease stimulates opportunistic screening practices that further increase overdiagnosis without the benefit of mortality reduction. However, in the past decade, new screening tools have been developed that make the classic PSA-only-based screening an outdated strategy. With improved use of PSA, in combination with age, prostate volume and with the application of prostate cancer risk calculators, a risk-adapted strategy enables improved stratification of men with prostate cancer and avoidance of unnecessary diagnostic procedures. This combination used with advanced detection techniques (such as MRI and targeted biopsy), can reduce overdiagnosis. Moreover, new biomarkers are becoming available and will enable further improvements in risk stratification.

Development and Validation of a Personalized, Sex-Specific Prediction Algorithm of Severe Atheromatosis in Middle-Aged Asymptomatic Individuals: The ILERVAS Study

Background

Although European guidelines recommend vascular ultrasound for the assessment of cardiovascular risk in low-to-moderate risk individuals, no algorithm properly identifies patients who could benefit from it. The aim of this study is to develop a sex-specific algorithm to identify those patients, especially women who are usually underdiagnosed.

Methods

Clinical, anthropometrical, and biochemical data were combined with a 12-territory vascular ultrasound to predict severe atheromatosis (SA: ≥ 3 territories with plaque). A Personalized Algorithm for Severe Atheromatosis Prediction (PASAP-ILERVAS) was obtained by machine learning. Models were trained in the ILERVAS cohort (n = 8,330; 51% women) and validated in the control subpopulation of the NEFRONA cohort (n = 559; 47% women). Performance was compared to the Systematic COronary Risk Evaluation (SCORE) model.

Results

The PASAP-ILERVAS is a sex-specific, easy-to-interpret predictive model that stratifies individuals according to their risk of SA in low, intermediate, or high risk. New clinical predictors beyond traditional factors were uncovered. In low- and high-risk (L&amp;H-risk) men, the net reclassification index (NRI) was 0.044 (95% CI: 0.020–0.068), and the integrated discrimination index (IDI) was 0.038 (95% CI: 0.029–0.048) compared to the SCORE. In L&amp;H-risk women, PASAP-ILERVAS showed a significant increase in the area under the curve (AUC, 0.074 (95% CI: 0.062–0.087), p-value: &lt; 0.001), an NRI of 0.193 (95% CI: 0.162–0.224), and an IDI of 0.119 (95% CI: 0.109–0.129).

Conclusion

The PASAP-ILERVAS improves SA prediction, especially in women. Thus, it could reduce the number of unnecessary complementary explorations selecting patients for a further imaging study within the intermediate risk group, increasing cost-effectiveness and optimizing health resources.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [NCT03228459].

Verification of subclinical carotid atherosclerosis as part of risk stratification in overweight and obesity: the role of machine learning in the development of a diagnostic algorithm

Aim. Comparative analysis of mathematical models obtained using multivariate logistic regression (MLR) with stepwise inclusion of predictors and machine learning (ML) for assessing the probability of subclinical carotid atherosclerosis in normotensive overweight and obese patients without cardiovascular diseases and/or diabetes.

Material and methods. We received data on patients from the Webiomed platform database. The inclusion criteria were age ≥18 years, body mass index ≥25 kg/m2, extracranial artery ultrasound results, while the exclusion criteria included diabetes and/or cardiovascular disease. MLR analysis was carried out with stepwise inclusion of predictors. ML algorithms were used to create an alternative model.

Results. The overall percentage of true results for MLR model was 73,2%, while the proportion of true negative and positive predictions was 80,1% and 63,4%, respectively. Mathematical models created using ML methods are characterized by a predictive value from 75 to 97% with a sensitivity of 77 to 92% and a specificity of 80 to 98%.

Conclusion. A significant superiority of ML models was revealed in the study of available clinical and paraclinical parameters. Integration of ML mathematical models into a diagnostic algorithm for making a decision to refer a low-risk patient for extracranial artery ultrasound will significantly improve its accuracy and cost efficiency.

Cardiovascular risk communication strategies in primary prevention. A systematic review with narrative synthesis

AIM

To evaluate the effectiveness of cardiovascular risk communication strategies to improve understanding and promote risk factor modification.

DESIGN

Systematic review with narrative synthesis.

DATA SOURCES

A comprehensive database search for quantitative and qualitative studies was conducted in five databases, Cumulative Index to Nursing and Allied health Literature (CINAHL), Medical Literature Analysis and Retrieval System Online (MEDLINE), EMBASE, Applied Social Sciences Index and Abstracts (ASSIA) and Web of Science. The searches were conducted between 1980 and July 2019.

REVIEW METHODS

The systematic review was conducted in accordance with Cochrane review methods. Data were extracted and a narrative synthesis of quantitative and qualitative results was undertaken.

RESULTS

The abstracts of 16,613 articles were assessed and 210 underwent in-depth review, with 31 fulfilling the inclusion criteria. We observed significant heterogeneity across study designs and outcomes. Nine communication strategies were identified including numerical formats, graphical formats, qualitative information, infographics, avatars, game interactions, timeframes, genetic risk scores and cardiovascular imaging. Strategies that used cardiovascular imaging had the biggest impact on health behaviour change and risk factor modification. Improvements were seen in diet, exercise, smoking, risk scores, cholesterol and intentions to take preventive medication.

CONCLUSION

A wide range of cardiovascular risk communication strategies has been evaluated, with those that employ personalized and visual evidence of current cardiovascular health status more likely to promote action to reduce risk.

IMPACT

Future risk communication strategies should incorporate methods to provide individuals with evidence of their current cardiovascular health status.

Estimated Life-Years Gained Free of New or Recurrent Major Cardiovascular Events With the Addition of Semaglutide to Standard of Care in People With Type 2 Diabetes and High Cardiovascular Risk

OBJECTIVE

Semaglutide, a glucagon-like peptide 1 receptor agonist, reduced major adverse cardiovascular events (MACE) in people with type 2 diabetes (T2D) at high risk of cardiovascular disease (CVD) in a post hoc analysis of pooled data from Trial to Evaluate Cardiovascular and Other Long-term Outcomes with Semaglutide in Subjects With Type 2 Diabetes (SUSTAIN) 6 and Peptide Innovation for Early Diabetes Treatment (PIONEER) 6. We estimated the benefit of adding semaglutide to standard of care (SoC) on life-years free of new/recurrent CVD events in people with T2D at high risk of CVD.

RESEARCH DESIGN AND METHODS

The Diabetes Lifetime-perspective prediction (DIAL) competing risk-adjusted lifetime CVD risk model for people with T2D was developed previously. Baseline characteristics of the pooled cohort from SUSTAIN 6 and PIONEER 6 (POOLED cohort) (N = 6,480) were used to estimate individual life expectancy free of CVD for patients in the POOLED cohort. The hazard ratio of MACE from adding semaglutide to SoC was derived from the POOLED cohort (hazard ratio [HR] 0.76 [95% CI 0.62-0.92]) and combined with an individual's risk to estimate their CVD benefit.

RESULTS

Adding semaglutide to SoC was associated with a wide distribution in life-years free of CVD gained, with a mean increase of 1.7 (95% CI 0.5-2.9) life-years. Estimated life-years free of CVD gained with semaglutide was dependent on baseline risk (life-years free of CVD gained in individuals with established CVD vs. those with cardiovascular risk factors only: 2.0 vs. 0.2) and age at treatment initiation.

CONCLUSIONS

Adding semaglutide to SoC was associated with a gain in life-years free of CVD events that was dependent on baseline CVD risk and age at treatment initiation. This study helps contextualize the results of semaglutide clinical trials.

Circulating MicroRNAs as Novel Biomarkers in Risk Assessment and Prognosis of Coronary Artery Disease

Coronary artery disease is among the leading causes of death worldwide. Nevertheless, available cardiovascular risk prediction algorithms still miss a significant portion of individuals at-risk. Thus, the search for novel non-invasive biomarkers to refine cardiovascular risk assessment is both an urgent need and an attractive topic, which may lead to a more accurate risk stratification and/or prognostic score definition for coronary artery disease. A new class of such non-invasive biomarkers is represented by extracellular microRNAs (miRNAs) circulating in the blood. MiRNAs are non-coding RNA of 22–25 nucleotides in length that play a significant role in both cardiovascular physiology and pathophysiology. Given their high stability and conservation, resistance to degradative enzymes, and detectability in body fluids, circulating miRNAs are promising emerging biomarkers, and specific expression patterns have already been associated with a wide range of cardiovascular conditions. In this review, an overview of the role of blood miRNAs in risk assessment and prognosis of coronary artery disease is given.

Early risk stratification in patients with cardiogenic shock irrespective of the underlying cause - The Cardiogenic Shock Score (CSS)

AIMS

Early risk stratification is essential to guide treatment in cardiogenic shock (CS). Existing CS risk scores were derived in selected cohorts, without accounting for the heterogeneity of CS. The aim of this study was to develop a universal risk score (CSS) for all CS patients, irrespective of underlying cause.

METHODS AND RESULTS

Within a registry of 1,308 CS unselected patients admitted to a tertiary-care hospital between 2009 and 2019, a Cox regression model was fitted to derive the CSS, with 30-day mortality as main outcome. CSS's predictive ability was compared to the IABP-Shock-II score, the CardShock score and SCAI classification by C-indices and validated in an external cohort of 934 CS patients. Based on the Cox regression, 9 predictors were included in the CSS: age, sex, acute myocardial infarction (AMI-CS), systolic blood pressure, heart rate, pH, lactate, glucose and cardiac arrest. CSS had the highest C-index in the overall cohort (0.740 vs. 0.677/0.683 for IABP-Shock-II score/CardShock score), in patients with AMI-CS (0.738 vs. 0.675/0.689 for IABP-Shock-II score/CardShock score) and in patients with non-AMI-CS (0.734 vs. 0.677/0.669 for IABP-Shock-II score/CardShock score). In the external validation cohort, the CSS had a C-index of 0.73, which was higher than all other tested scores.

CONCLUSION

The CSS provides improved information on the risk of death in unselected patients with CS compared to existing scores, irrespective of its cause. Because it is based on point-of-care variables which can be obtained even in critical situations, the CSS has the potential to guide treatment decisions in CS. This article is protected by copyright. All rights reserved.

Cardiovascular risk prediction in healthy older people

Identification of individuals with increased risk of major adverse cardiovascular events (MACE) is important. However, algorithms specific to the elderly are lacking. Data were analysed from a randomised trial involving 18,548 participants ≥ 70 years old (mean age 75.4 years), without prior cardiovascular disease events, dementia or physical disability. MACE included coronary heart disease death, fatal or nonfatal ischaemic stroke or myocardial infarction. Potential predictors tested were based on prior evidence and using a machine-learning approach. Cox regression analyses were used to calculate 5-year predicted risk, and discrimination evaluated from receiver operating characteristic curves. Calibration was also assessed, and the findings internally validated using bootstrapping. External validation was performed in 25,138 healthy, elderly individuals in the primary care environment. During median follow-up of 4.7 years, 594 MACE occurred. Predictors in the final model included age, sex, smoking, systolic blood pressure, high-density lipoprotein cholesterol (HDL-c), non-HDL-c, serum creatinine, diabetes and intake of antihypertensive agents. With variable selection based on machine-learning, age, sex and creatinine were the most important predictors. The final model resulted in an area under the curve (AUC) of 68.1 (95% confidence intervals 65.9; 70.4). The model had an AUC of 67.5 in internal and 64.2 in external validation. The model rank-ordered risk well but underestimated absolute risk in the external validation cohort. A model predicting incident MACE in healthy, elderly individuals includes well-recognised, potentially reversible risk factors and notably, renal function. Calibration would be necessary when used in other populations.

Engaging Female Community Health Volunteers (FCHVs) for cardiovascular diseases risk screening in Nepal

Introduction

Non-Communicable Diseases (NCDs) have become the leading public health problems worldwide and the cardiovascular diseases (CVDs) is one of the major NCDs. Female Community Health Volunteers (FCHVs) in Nepal are the key drivers to implementing frontline health services. We explored the potential for engaging FCHVs for CVD risk screening at the community level in Nepal.

Methods

We used multiple approaches (quantitative and qualitative) for data collection. The trained FCHVs administered CVD risk screening questionnaire among 491 adults in rural and urban areas and calculated the CVD risk scores. To maintain consistency and quality, a registered medical doctor also, using the same risk scoring chart, independently calculated the CVD risk scores. Kappa statistics and concordance coefficient were used to compare these two sets of risk screening results. Sensitivity and specificity analyses were conducted. Two focus group discussions among the FCHVs were conducted to determine their experiences with CVD risk screening and willingness to engage with CVD prevention and control efforts.

Results

The mean level of agreement between two sets of risk screening results was 94.5% (Kappa = 0.77, P<0.05). Sensitivity of FCHV screening was 90.3% (95% CI: 0.801–0.964); and the specificity was 97% (95% CI: 0.948, 0.984). FCHVs who participated in the FGDs expressed a strong enthusiasm and readiness to using the CVD risk screening tools. Despite their busy workload, all FCHVs showed high level of motivation and willingness in using CVD risk screening tools and contribute to the prevention and control efforts of NCDs. The FCHVs recommended needs for providing additional training and capacity building opportunities.

Conclusion

We conclude that there is a potential for engaging FCHVs to use simple CVD risk screening tools at the community level. The findings are promising, however, further studies engaging larger number of FCHVs and larger population would warrant feasibility of such tools within the existing healthcare systems in Nepal.

Development and Validation of Decision Rules Models to Stratify Coronary Artery Disease, Diabetes, and Hypertension Risk in Preventive Care: Cohort Study of Returning UK Biobank Participants

Many predictive models exist that predict risk of common cardiometabolic conditions. However, a vast majority of these models do not include genetic risk scores and do not distinguish between clinical risk requiring medical or pharmacological interventions and pre-clinical risk, where lifestyle interventions could be first-choice therapy. In this study, we developed, validated, and compared the performance of three decision rule algorithms including biomarkers, physical measurements, and genetic risk scores for incident coronary artery disease (CAD), diabetes (T2D), and hypertension against commonly used clinical risk scores in 60,782 UK Biobank participants. The rules models were tested for an association with incident CAD, T2D, and hypertension, and hazard ratios (with 95% confidence interval) were calculated from survival models. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), and Net Reclassification Index (NRI). The higher risk group in the decision rules model had a 40-, 40.9-, and 21.6-fold increased risk of CAD, T2D, and hypertension, respectively (p < 0.001 for all). Risk increased significantly between the three strata for all three conditions (p < 0.05). Based on genetic risk alone, we identified not only a high-risk group, but also a group at elevated risk for all health conditions. These decision rule models comprising blood biomarkers, physical measurements, and polygenic risk scores moderately improve commonly used clinical risk scores at identifying individuals likely to benefit from lifestyle intervention for three of the most common lifestyle-related chronic health conditions. Their utility as part of digital data or digital therapeutics platforms to support the implementation of lifestyle interventions in preventive and primary care should be further validated.

Prediction of Lifetime Risk of Cardiovascular Disease Deaths Stratified by Sex in the Japanese Population

Background

Lifetime risk is an informative estimate for driving lifestyle and behavioral changes especially for young adults. The impact of composite risk factors for cardiovascular disease on lifetime risk stratified by sex has not been investigated in the Japanese population, which has a much lower mortality of coronary heart disease compared with the Western population. We aimed to estimate lifetime risk of death from cardiovascular disease attributable to traditional risk factors.

Methods and Results

We analyzed pooled individual data from the Evidence for Cardiovascular Prevention from Observational Cohorts in a Japanese cohort study. A modified Kaplan–Meier approach was used to estimate the remaining lifetime risk of cardiovascular death. In total, 41 002 Japanese men and women with 537 126 person‐years of follow‐up were included. The lifetime risk at the index‐age of 45 years for those with optimal risk factors (total cholesterol <4.65 mmol/L, systolic blood pressure <120 mm Hg, diastolic blood pressure <80 mm Hg, absence of diabetes, and absence of smoking habit) was lower compared with the highest risk profile of ≥2 risk factors (6.8% [95% CI, 0%–11.9%] versus 19.4% [16.7%–21.4%] for men and 6.9% [1.2%–11.5%] versus 15.4% [12.6%–18.1%] for women).

Conclusions

The magnitude and the number of risk factors were progressively associated with increased lifetime risk even in individuals in early adulthood who tend to have low short‐term risk. The degree of established cardiovascular risk factors can be converted into lifetime risk. Our findings may be useful for risk communication in the early detection of future cardiovascular disease risk.

Lifetime prevention of cardiovascular disease. Part III: young, middle, elderly and senile age

Intensive investigation of cardiovascular disease (CVD) risk factors (RFs), both traditional (smoking, dyslipidemia, diabetes, etc.) and non-traditional, which are a component of the so-called exposome, as well as their non-drug and drug correction provide wide prospects for effective cardiovascular prevention. Prevention becomes the dominant trend in cardiology and in medicine in general. The aim of the article was to describe cardiovascular prevention in young, middle, elderly and senile age. Due to the multifaceted nature of cardiovascular RFs, an integrated biopsychosocial approach, individual and population-based prevention, cumulative risk assessment of all CVDs, intersectoral collaboration and the involvement of decision-makers, are key to the success and effectiveness of prevention measures. It is important to note that, on the one hand, preventive measures should be started as early as possible due to cumulative effect of RFs, on the other hand, most of the preventive interventions for CVD are extremely relevant at all life stages.

Score2: A New Updated Algorithm to Predict Cardiovascular Disease Risk in Europe

The recently published guidelines of the European Society of Cardiology for the prevention of cardiovascular diseases presented in August 2021 at the virtual European Society of Cardiology congress recommend the use of the SCORE2 risk index instead of the classic SCORE risk index to calculate the cardiovascular risk (specifically, ten-year fatal and nonfatal risk) in a healthy population under the age of 70 years, with a level of evidence IB. This new risk index was developed with the collaboration of about 200 investigators, including 45 cohorts in 13 countries with 700,000 participants, and covers the known risk factors for heart and circulatory diseases such as age, sex, lipid levels, blood pressure, and smoking. In addition, it divides the countries into four groups of risk and uses a competing risk model, adjusting the risk for the probability of having another event, which enables better estimation of the risk of fatal and nonfatal events in a younger population (40-69 years).