Major Global Coronary Artery Calcium Guidelines

Small dense low-density lipoprotein cholesterol and coronary artery calcification in the Multi-Ethnic Study of Atherosclerosis

AIMS

Elevated small dense LDL cholesterol (sd-LDL-C) increases atherosclerotic cardiovascular disease (CVD) risk. Although coronary artery calcification (CAC) is widely used for predicting CVD events, few studies have examined the relationship between sd-LDL-C and CAC.

METHODS AND RESULTS

This study included 4672 individuals with directly measured baseline sd-LDL-C and CAC from the Multi-Ethnic Study of Atherosclerosis [mean (standard deviation) age: 61.9 (10.4) years; 52.5% women; 47.3% with baseline CAC (mean score >0)]. We used multi-variable general linear models and restricted cubic splines with the goodness of fit testing to evaluate the association of sd-LDL-C with the presence of CAC. Odds ratios [OR (95% confidence interval)] were adjusted for demographics and cardiovascular risk factors, including estimated total LDL-C. Higher quartiles of sd-LDL-C were associated with the presence of CAC, even after accounting for total LDL-C. Compared with the lowest quartile of sd-LDL-C, participants in Quartiles 2, 3, and 4 had higher odds for the presence of baseline CAC [Quartile 2 OR: 1.24 (1.00, 1.53); Quartile 3 OR: 1.51 (1.19, 1.93); and Quartile 4 OR 1.59 (1.17, 2.16)]. Splines suggested a quadratic curvilinear relationship of continuous sd-LDL-C with CAC after adjustment for demographics and CVD risk factors (quadratic vs. first-order sd-LDL-C terms likelihood ratio test: P = 0.015), but not after accounting for total LDL-C (quadratic vs. first-order terms: P = 0.156).

CONCLUSION

In a large, multi-ethnic sample without known CVD, higher sd-LDL-C was associated with the presence of CAC, above and beyond total LDL-C. Whether selective direct measurement of sd-LDL-C is indicated to refine cardiovascular risk assessment in primary prevention warrants further investigation.

A practical guide for assessing and managing cardiovascular risk during androgen-deprivation therapy in patients with prostate cancer

Prostate cancer is the most common malignancy among men worldwide, and androgen-deprivation therapy (ADT) is a mainstay of treatment. There are observational data demonstrating an increased risk of cardiovascular events in patients who receive ADT, particularly those who have an elevated baseline cardiovascular risk. Because, for most patients with prostate cancer, death is predominantly from noncancer-related causes, cardiovascular disease and its risk factors should be optimized during cancer treatment. This review provides an overview of the landscape of ADT treatment and serves as a guide for appropriate cardiovascular screening and risk-mitigation strategies. The authors emphasize the importance of shared communication between the multidisciplinary cancer team and primary care to improve baseline cardiovascular screening and treatment of modifiable risk factors within this higher risk population.

Enhancing cardiovascular risk prediction through AI-enabled calcium-omics

Whole-heart coronary calcium Agatston score is a well-established predictor of major adverse cardiovascular events (MACE), but it does not account for individual calcification features related to the pathophysiology of the disease (e.g., multiple-vessel disease, spread of the disease along the vessel, stable calcifications, numbers of lesions, and density). We used novel, hand-crafted calcification features (calcium-omics); Cox time-to-event modeling; elastic net; and up and down synthetic sampling methods for imbalanced data, to assess MACE risk. We used 2457 CT calcium score (CTCS) images enriched for MACE events from our large no-cost CLARIFY program (ClinicalTrials.gov Identifier: NCT04075162). Among calcium-omics features, numbers of calcifications, LAD mass, and diffusivity (a measure of spatial distribution) were especially important determinants of increased risk, with dense calcification (> 1000HU, stable calcifications) associated with reduced risk Our calcium-omics model with (training/testing, 80/20) gave C-index (80.5%/71.6%) and 2-year AUC (82.4%/74.8%). Although the C-index is notoriously impervious to model improvements, calcium-omics compared favorably to Agatston and gave a significant difference (P < 0.001). The calcium-omics model identified 73.5% of MACE cases in the high-risk group, a 13.2% improvement as compared to Agatston, suggesting that calcium-omics could be used to better identity candidates for intensive follow-up and therapies. The categorical net-reclassification index was NRI = 0.153. Our findings from this exploratory study suggest the utility of calcium-omics in improved risk prediction. These promising results will pave the way for more extensive, multi-institutional studies of calcium-omics.

Plasma proteomics for prediction of subclinical coronary artery calcifications in primary prevention

BACKGROUND AND AIMS

Recent developments in high-throughput proteomic technologies enable the discovery of novel biomarkers of coronary atherosclerosis. The aims of this study were to test if plasma protein subsets could detect coronary artery calcifications (CAC) in asymptomatic individuals and if they add predictive value beyond traditional risk factors.

METHODS

Using proximity extension assays, 1,342 plasma proteins were measured in 1,827 individuals from the Impaired Glucose Tolerance and Microbiota (IGTM) study and 883 individuals from the Swedish Cardiopulmonary BioImage Study (SCAPIS) aged 50-64 years without history of ischaemic heart disease and with CAC assessed by computed tomography. After data-driven feature selection, extreme gradient boosting machine learning models were trained on the IGTM cohort to predict the presence of CAC using combinations of proteins and traditional risk factors. The trained models were validated in SCAPIS.

RESULTS

The best plasma protein subset (44 proteins) predicted CAC with an area under the curve (AUC) of 0.691 in the validation cohort. However, this was not better than prediction by traditional risk factors alone (AUC = 0.710, P = .17). Adding proteins to traditional risk factors did not improve the predictions (AUC = 0.705, P = .6). Most of these 44 proteins were highly correlated with traditional risk factors.

CONCLUSIONS

A plasma protein subset that could predict the presence of subclinical CAC was identified but it did not outperform nor improve a model based on traditional risk factors. Thus, support for this targeted proteomics platform to predict subclinical CAC beyond traditional risk factors was not found.

SEA 2024 Standards for Global Control of Vascular Risk

One of the objectives of the Spanish Society of Arteriosclerosis is to contribute to the knowledge, prevention and treatment of vascular diseases, which are the leading cause of death in Spain and entail a high degree of disability and health expenditure. Atherosclerosis is a multifactorial disease and its prevention requires a global approach that takes into account the associated risk factors. This document summarises the current evidence and includes recommendations for patients with established vascular disease or at high vascular risk: it reviews the symptoms and signs to evaluate, the laboratory and imaging procedures to request routinely or in special situations, and includes the estimation of vascular risk, diagnostic criteria for entities that are vascular risk factors, and general and specific recommendations for their treatment. Finally, it presents aspects that are not usually referenced in the literature, such as the organisation of a vascular risk consultation.

Innovations in cardiac computed tomography: Imaging in coronary artery disease

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool in the non-invasive evaluation of coronary artery disease (CAD). Recent advancements in imaging techniques, quantitative plaque assessment methods, assessment of coronary physiology, and perivascular coronary inflammation have propelled CCTA to the forefront of CAD management, enabling precise risk stratification, disease monitoring, and evaluation of treatment response. However, challenges persist, including the need for cardiovascular outcomes data for therapy modifications based on CCTA findings and the lack of standardized quantitative plaque assessment techniques to establish universal guidelines for treatment strategies. This review explores the current utilization of CCTA in clinical practice, highlighting its clinical impact and discussing challenges and opportunities for future development. By addressing these nuances, CCTA holds promise for revolutionizing coronary imaging and improving CAD management in the years to come. Ultimately, the goal is to provide precise risk stratification, optimize medical therapy, and improve cardiovascular outcomes while ensuring cost-effectiveness for healthcare systems.

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes

Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis. This review aims to provide essential knowledge on the AI-based techniques currently applied to CACS, setting the stage for a holistic analysis of the use of these techniques in coronary artery calcium imaging. While the focus of the review will be detailing the evidence, strengths, and limitations of end-to-end CACS algorithms in electrocardiography-gated and non-gated scans, the current role of deep-learning image reconstructions, segmentation techniques, and combined applications such as simultaneous coronary artery calcium and pulmonary nodule segmentation, will also be discussed.

Diagnostic Ability of Manual Calcification Length Assessment on Non-Electrocardiographically Gated Computed Tomography for Estimating the Presence of Coronary Artery Disease

Background: Coronary artery calcification score (CACS) on electrocardiography (ECG)-gated computed tomography (CT) is used for risk stratification of atherosclerotic cardiovascular disease, which requires dedicated analytic software. In this study, we evaluated the diagnostic ability of manual calcification length assessment on non-ECG-gated CT for epicardial coronary artery disease (CAD). Methods: A total of 100 patients undergoing both non-ECG-gated plain CT scans with a slice interval of 1.25 mm and invasive coronary angiography were retrospectively included. We manually measured the length of the longest calcified lesions of coronary arteries on each branch. The relationship between the number of coronary arteries with the length of coronary calcium > 5, 10, or 15 mm and the presence of epicardial CAD on invasive angiography was evaluated. Standard CACS was also evaluated using established software. Results: Of 100 patients, 49 (49.0%) had significant epicardial CAD on angiography. The median standard CACS was 346 [7, 1965]. In both manual calcium assessment and standard CACS, the increase in calcium burden was progressively associated with the presence of epicardial CAD on angiography. The receiver operating characteristic curve analysis showed similar diagnostic abilities of the two diagnostic methods. The best cut-off values for CAD were 2, 1, and 1 for the number of vessels with calcium > 5, 10, and 15 mm, respectively. Overall, the diagnostic ability of manual calcium assessment was similar to that of standard CACS > 400. Conclusions: Manual assessment of coronary calcium length on non-ECG-gated plain CT provided similar diagnostic ability for the presence of significant epicardial CAD on invasive angiography, as compared to standard CACS.

Epidemiology and Prognostic Implications of Coronary Artery Calcium in Asymptomatic Individuals With Prediabetes: A Multicohort Study

OBJECTIVE

To describe the epidemiology and prognostic value of coronary artery calcium (CAC) in individuals with prediabetes.

RESEARCH DESIGN AND METHODS

We pooled participants free of clinical atherosclerotic cardiovascular disease (ASCVD) from four prospective cohorts: the Multi-Ethnic Study of Atherosclerosis, Heinz Nixdorf Recall Study, Framingham Heart Study, and Jackson Heart Study. Two definitions were used for prediabetes: inclusive (fasting plasma glucose [FPG] ≥100 to <126 mg/dL and hemoglobin A1c [HbA1c] ≥5.7% to <6.5%, if available, and no glucose-lowering medications) and restrictive (FPG ≥110 to <126 mg/dL and HbA1c ≥5.7% to <6.5%, if available, among participants not taking glucose-lowering medications).

RESULTS

The study included 13,376 participants (mean age 58 years; 54% women; 57% White; 27% Black). The proportions with CAC ≥100 were 17%, 22%, and 37% in those with euglycemia, prediabetes, and diabetes, respectively. Over a median (25th-75th percentile) follow-up time of 14.6 (interquartile range 7.8-16.4) years, individuals with prediabetes and CAC ≥100 had a higher unadjusted 10-year incidence of ASCVD (13.4%) than the overall group of those with diabetes (10.6%). In adjusted analyses, using the inclusive definition of prediabetes, compared with euglycemia, the hazard ratios (HRs) for ASCVD were 0.79 (95% CI 0.62, 1.01) for prediabetes and CAC 0, 0.70 (0.54, 0.89) for prediabetes and CAC 1-99, 1.54 (1.27, 1.88) for prediabetes and CAC ≥100, and 1.64 (1.39, 1.93) for diabetes. Using the restrictive definition, the HR for ASCVD was 1.63 (1.29, 2.06) for prediabetes and CAC ≥100.

CONCLUSIONS

CAC ≥100 is frequent among individuals with prediabetes and identifies a high ASCVD risk subgroup in which the adjusted ASCVD risk is similar to that in individuals with diabetes.

Contemporary attitudes and beliefs on coronary artery calcium from social media using artificial intelligence

Coronary artery calcium (CAC) is a powerful tool to refine atherosclerotic cardiovascular disease (ASCVD) risk assessment. Despite its growing interest, contemporary public attitudes around CAC are not well-described in literature and have important implications for shared decision-making around cardiovascular prevention. We used an artificial intelligence (AI) pipeline consisting of a semi-supervised natural language processing model and unsupervised machine learning techniques to analyze 5,606 CAC-related discussions on Reddit. A total of 91 discussion topics were identified and were classified into 14 overarching thematic groups. These included the strong impact of CAC on therapeutic decision-making, ongoing non-evidence-based use of CAC testing, and the patient perceived downsides of CAC testing (e.g., radiation risk). Sentiment analysis also revealed that most discussions had a neutral (49.5%) or negative (48.4%) sentiment. The results of this study demonstrate the potential of an AI-based approach to analyze large, publicly available social media data to generate insights into public perceptions about CAC, which may help guide strategies to improve shared decision-making around ASCVD management and public health interventions.

Beyond symptoms: Unlocking the potential of coronary calcium scoring in the prevention and treatment of coronary artery disease

Coronary Artery Disease (CAD) represents a persistent global health menace, particularly prevalent in Eastern European nations. Often asymptomatic until its advanced stages, CAD can precipitate life-threatening events like myocardial infarction or stroke. While conventional risk factors provide some insight into CAD risk, their predictive accuracy is suboptimal. Amidst this, Coronary Calcium Scoring (CCS), facilitated by non-invasive computed tomography (CT), emerges as a superior diagnostic modality. By quantifying calcium deposits in coronary arteries, CCS serves as a robust indicator of atherosclerotic burden, thus refining risk stratification and guiding therapeutic interventions. Despite certain limitations, CCS stands as an instrumental tool in CAD management and in thwarting adverse cardiovascular incidents. This review delves into the pivotal role of CCS in CAD diagnosis and treatment, elucidates the involvement of calcium in atherosclerotic plaque formation, and outlines the principles and indications of utilizing CCS for predicting major cardiovascular events.

Prediction of high coronary artery calcium (CAC) scores from aortic arch calcification: An efficient tool for selection of non-optimal candidates for coronary CTA?

PURPOSE

Overutilization of healthcare resources is causing a high socioeconomic burden. Patients with high coronary artery calcium (CAC) scores > 1000AU are not optimal candidates for coronary CTA and better suited for other diagnostic strategies. Therefore, our objective was to evaluate whether a 4-scale aortic arch calcification severity (AoArCa) score from CT and X-Ray predicts high-CAC scores.

METHODS

Patients referred to coronary/aortic CT-Angiography were enrolled. The severity of aortic arch calcification (AoArCa) was scored as grade: 0 = absent, 1 = minimal (<25 % of circumference), 2 = mild (25-50 %), 3 = moderate (50-75 %) and 4 = severe (75-100 %) on both thoracic CT and X-ray.

RESULTS

In 130 patients, the absence of AoArCa by CT was highly accurate to rule out CAC > 1000AU (sens. 100 %). No or minimal AoArCa had a high NPV of 95.6 % to rule out CAC > 1000 and grade 0,1 + 2 a NPV of 86.96 %. The AUC of AoArCa by CT for predicting high CAC > 1000 was c = 0.84 (p < 0.001; 95 %CI: 0.771--0.91). For moderate-to-severe AoArCa, accuracy was c = 0.792 (p < 0.001). The intermodality agreement between CT and X-Ray based AoArCa Scores was good (r = 0.824, p < 0.001); ICC = 0.902. For X-ray, AUC was c = 0.715 to predict CAC > 1000 (p < 0.001). In regression models, only moderate-or-severe AoArCa, but not the other CVRF predicted CAC > 1000 (p < 0.001), and there was an association of the number of CVRF.

CONCLUSIONS

Patients with moderate-to-severe aortic arch calcification have a high probability of CAC > 1000AU, but not those with no, minimal and mild. The absence of AoArCa rules out CAC > 1000AU. AoArCa severity may serve as valuable tool for selecting the diagnostic strategy.

Social disadvantage, coronary artery calcium, and their interplay in the prediction of atherosclerotic cardiovascular disease events

BACKGROUND AND AIMS

Social determinants of health (SDOH) are key for the identification of populations at increased risk of atherosclerotic cardiovascular disease (ASCVD). However, whether at the individual level SDOH improve current ASCVD risk prediction paradigms beyond traditional risk factors and the coronary artery calcium (CAC) score, is unknown. We evaluated the interplay between CAC and SDOH in ASCVD risk prediction.

METHODS

MESA is a prospective study of US adults free of clinical ASCVD at baseline. We used an SDOH index inclusive of 14 determinants from 5 domains. The index ranged 0-1 and was divided into quartiles, with higher ones representing worse SDOH. Cox regression was used to evaluate the adjusted associations between CAC, SDOH, their interplay, and ASCVD events. The C-statistic was computed to assess improvement in risk discrimination for prediction of ASCVD events.

RESULTS

We included 6479 MESA participants (50% with CAC = 0, 24% CAC>100). ASCVD incidence increased with increasing CAC scores across SDOH quartiles. The lowest incidence was noted in those with CAC = 0 and favourable SDOH (2/1000 person-years) and highest in those with CAC>100 and most unfavourable SDOH (20.6/1000 person-years). While CAC was strongly associated with ASCVD across SDOH quartiles, SDOH was weakly associated with ASCVD across CAC strata. CAC improved the discriminatory ability of all prediction models beyond traditional risk factors, the improvement in C-statistic ranging +0.02 - +0.05. Improvements with SDOH were smaller, and were none on top of CAC.

CONCLUSIONS

CAC improves ASCVD risk stratification across the spectrum of social vulnerability, while SDOH fail to improve risk prediction beyond traditional RFs and CAC.

Assessment of Subclinical Atherosclerosis in Asymptomatic People In Vivo: Measurements Suitable for Biomarker and Mendelian Randomization Studies

BACKGROUND

One strategy to reduce the burden of cardiovascular disease is the early detection and treatment of atherosclerosis. This has led to significant interest in studies of subclinical atherosclerosis, using different phenotypes, not all of which are accurate reflections of the presence of asymptomatic atherosclerotic plaques. The aim of part 2 of this series is to provide a review of the existing literature on purported measures of subclinical disease and recommendations concerning which tests may be appropriate in the prevention of incident cardiovascular disease.

METHODS

We conducted a critical review of measurements used to infer the presence of subclinical atherosclerosis in the major conduit arteries and focused on the predictive value of these tests for future cardiovascular events, independent of conventional cardiovascular risk factors, in asymptomatic people. The emphasis was on studies with >10 000 person-years of follow-up, with meta-analysis of results reporting adjusted hazard ratios (HRs) with 95% CIs. The arterial territories were limited to carotid, coronary, aorta, and lower limb arteries.

RESULTS

In the carotid arteries, the presence of plaque (8 studies) was independently associated with future stroke (pooled HR, 1.89 [1.04-3.44]) and cardiac events (7 studies), with a pooled HR, 1.77 (1.19-2.62). Increased coronary artery calcium (5 studies) was associated with the risk of coronary heart disease events, pooled HR, 1.54 (1.07-2.07) and increasing severity of calcification (by Agaston score) was associated with escalation of risk (13 studies). An ankle/brachial index (ABI) of <0.9, the pooled HR for cardiovascular death from 7 studies was 2.01 (1.43-2.81). There were insufficient studies of either, thoracic or aortic calcium, aortic diameter, or femoral plaque to synthesize the data based on consistent reporting of these measures.

CONCLUSIONS

The presence of carotid plaque, coronary artery calcium, or abnormal ankle pressures seems to be a valid indicator of the presence of subclinical atherosclerosis and may be considered for use in biomarker, Mendelian randomization and similar studies.

Percentiles of predicted 10-year cardiovascular disease risk by sex and age in Brazil and their association with estimated risk of long-term atherosclerotic events

OBJECTIVE

Expressing the cardiovascular disease (CVD) risk in relation to peers may complement the estimation of absolute CVD risk. We aimed to determine 10-year CVD risk percentiles by sex and age in the Brazilian population and evaluate their association with estimated long-term atherosclerotic CVD (ASCVD) risk.

METHODS

A cross-sectional analysis of baseline data from the ELSA-Brasil study was conducted in individuals aged 40-74 years without prior ASCVD. Ten-year CVD risk and long-term ASCVD risk were estimated by the WHO risk score and the Multinational Cardiovascular Risk Consortium tool, respectively. Ten-year risk percentiles were determined by ranking the calculated risks within each sex and age group.

RESULTS

Ten-year CVD risk versus percentile plots were constructed for each sex and age group using data from 13,364 participants (55% females; median age, 52 [IQR, 46-59] years). Long-term ASCVD risk was calculated in 12,973 (97.1%) participants. Compared to individuals at the <25th risk percentile, those at the ≥75th percentile had a greater risk of being in the highest quartile of long-term risk (ORs [95% CIs] 6.57 [5.18-8.30] in females and 11.59 [8.42-15.96] in males) in regression models adjusted for age, race, education, and 10-year CVD risk. In both sexes, the association between risk percentile and long-term risk weakened after age 50. A tool for calculating 10-year CVD risk and the corresponding percentile is available at https://bit.ly/3CzPUi6.

CONCLUSIONS

We established percentiles of predicted 10-year CVD risk by sex and age in the Brazilian population, which independently reflect the estimated long-term ASCVD risk in younger individuals.

Premature atherosclerosis: An analysis over 39 years in the Netherlands. Implications for young individuals in high-risk families

Cardiovascular disease (CVD), especially atherosclerotic cardiovascular disease (ASCVD), is one of the most important disease problems in the world accounting for an estimated 18.6 million deaths globally. Although older individuals are more often affected, ASCVD event at a young age is of particular importance because of more healthy years lost. Therefore, it is important to identify young individuals correctly at risk of ASCVD events in an early stage. Unfortunately, current risk score algorithms underestimate ASCVD event risk at a younger age. Both coronary artery calcium scoring (CACs) and family history of premature ASCVD (FH-PASCVD) have emerged as reliable screening tools to be able to identify individuals at risk for ASCVD events. Positive FH-PASCVD is associated with higher absolute CAC scores in first-degree 'healthy' family members and the proportion of individuals above the CACs percentile threshold to warrant treatment is also higher as compared to the general population. Therefore, a positive FH-PASCVD identifies so-called high-risk families and adding CAC scoring within these families identifies individuals at increased risk for ASCVD events. In individuals from high-risk families with an elevated CAC score, ASCVD events can be prevented when treated with statins and aspirin. Therefore, we suggest assessing FH-PASCVD in young 'healthy' individuals as a first screening step and subsequently performing CAC scoring to be able to start treatment at an early stage, since not only the lower is better, but also the earlier is better.

Coronary artery calcium and sudden cardiac death: current evidence and future directions

PURPOSE OF REVIEW

To provide a summary of the current evidence and highlight future directions regarding coronary artery calcium (CAC) and risk of sudden cardiac death (SCD).

RECENT FINDINGS

Although up to 80% of all SCD is attributed to coronary heart disease (CHD), the subclinical atherosclerosis markers that help to improve SCD risk prediction are largely unknown. Recent observational data have demonstrated that, after adjustment for traditional risk factors, there is a stepwise higher risk for SCD across increasing CAC burden such that asymptomatic patients without overt atherosclerotic cardiovascular disease (ASCVD) experience a three-fold to five-fold higher SCD risk beginning at CAC at least 100 when compared with CAC = 0. Although the mechanisms underlying increasing CAC and SCD risk have yet to be fully elucidated, risk for myocardial infarction and scar, and/or exercise-induced ischemia may be potential mediators.

SUMMARY

High CAC burden is an important risk factor for SCD in asymptomatic middle-aged adults, suggesting that SCD risk stratification can begin in the early stages of CHD via measurement of calcific plaque on noncontrast computed tomography. Despite the clinical inertia for downstream functional cardiac testing after detecting high CAC, comprehensive ASCVD prevention strategies should be the primary focus for SCD risk reduction.

No evidence of a causal relationship between ankylosing spondylitis and cardiovascular disease: a two-sample Mendelian randomization study

Objective

Observational studies have suggested an increased risk of cardiovascular disease in individuals with ankylosing spondylitis. However, these studies are prone to confounding factors and reverse causality. To address these limitations, we conducted a Mendelian randomization study to assess the causal relationship between AS and CVD.

Methods

The study population comprises 9,069 individuals with ankylosing spondylitis and 509,093 individuals with either of six common cardiovascular diseases and a related indicator. Causal analysis using summary effect estimates and inverse variance weighting were employed as the main methods.

Results

The CAUSE analysis showed no evidence of a causal relationship between AS and CVD. The odds ratios for total CVD, heart failure, myocardial infarction, valvular heart disease, ischemic heart disease, and venous thromboembolism, Arterial stiffness index, were as follows: OR, 1.01; 95% confidence interval, 0.96-1.05; P = 0.91; OR, 1.03; 95% CI, 0.99-1.08; P = 0.50; OR, 0.94; 95% CI, 0.86-1.03; P = 0.53; OR, 0.99; 95% CI, 0.94-1.04; P = 0.99; OR, 0.98; 95% CI, 0.91-1.04; P = 0.94; OR, 0.98; 95% CI, 0.91-1.04; P = 0.99; β, -0.0019; 95% CI, 0.97-1.01; P = 0.99. The IVW and weighted median methods also yielded consistent results, and no heterogeneity or pleiotropy was found. Likewise, a reverse Mendelian randomization analysis did not uncover a heritable causal relationship between AS and CVD.

Conclusion

This Mendelian randomization study does not support a causal relationship between AS and CVD. Further research is needed to confirm this association.

When Does a Calcium Score Equate to Secondary Prevention?: Insights From the Multinational CONFIRM Registry

BACKGROUND

Elevated coronary artery calcium (CAC) scores in subjects without prior atherosclerotic cardiovascular disease (ASCVD) have been shown to be associated with increased cardiovascular risk.

OBJECTIVES

The authors sought to determine at what level individuals with elevated CAC scores who have not had an ASCVD event should be treated as aggressively for cardiovascular risk factors as patients who have already survived an ASCVD event.

METHODS

The authors performed a cohort study comparing event rates of patients with established ASVCD to event rates in persons with no history of ASCVD and known calcium scores to ascertain at what level elevated CAC scores equate to risk associated with existing ASCVD. In the multinational CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter) registry, the authors compared ASCVD event rates in persons without a history of myocardial infarction (MI) or revascularization (as categorized on CAC scores) to event rates in those with established ASCVD. They identified 4,511 individuals without known coronary artery disease (CAC) who were compared to 438 individuals with established ASCVD. CAC was categorized as 0, 1 to 100, 101 to 300, and >300. Cumulative major adverse cardiovascular events (MACE), MACE plus late revascularization, MI, and all-cause mortality incidence was assessed using the Kaplan-Meier method for persons with no ASCVD history by CAC level and persons with established ASCVD. Cox proportional hazards regression analysis was used to calculate HRs with 95% CIs, which were adjusted for traditional cardiovascular risk factors.

RESULTS

The mean age was 57.6 ± 12.4 years (56% male). In total, 442 of 4,949 (9%) patients experienced MACEs over a median follow-up of 4 years (IQR: 1.7-5.7 years). Incident MACEs increased with higher CAC scores, with the highest rates observed with CAC score >300 and in those with prior ASCVD. All-cause mortality, MACEs, MACE + late revascularization, and MI event rates were not statistically significantly different in those with CAC >300 compared with established ASCVD (all P > 0.05). Persons with a CAC score <300 had substantially lower event rates.

CONCLUSIONS

Patients with CAC scores >300 are at an equivalent risk of MACE and its components as those treated for established ASCVD. This observation, that those with CAC >300 have event rates comparable to those with established ASCVD, supplies important background for further study related to secondary prevention treatment targets in subjects without prior ASCVD with elevated CAC. Understanding the CAC scores that are associated with ASCVD risk equivalent to stable secondary prevention populations may be important for guiding the intensity of preventive approaches more broadly.

Artificial intelligence using a deep learning versus expert computed tomography human reading in calcium score and coronary artery calcium data and reporting system classification

BACKGROUND

Artificial intelligence (AI) applied to cardiac imaging may provide improved processing, reading precision and advantages of automation. Coronary artery calcium (CAC) score testing is a standard stratification tool that is rapid and highly reproducible. We analyzed CAC results of 100 studies in order to determine the accuracy and correlation between the AI software (Coreline AVIEW, Seoul, South Korea) and expert level-3 computed tomography (CT) human CAC interpretation and its performance when coronary artery disease data and reporting system (coronary artery calcium data and reporting system) classification is applied.

METHODS

A total of 100 non-contrast calcium score images were selected by blinded randomization and processed with the AI software versus human level-3 CT reading. The results were compared and the Pearson correlation index was calculated. The CAC-DRS classification system was applied, and the cause of category reclassification was determined using an anatomical qualitative description by the readers.

RESULTS

The mean age was age 64.5 years, with 48% female. The absolute CAC scores between AI versus human reading demonstrated a highly significant correlation (Pearson coefficient R  = 0.996); however, despite these minimal CAC score differences, 14% of the patients had their CAC-DRS category reclassified. The main source of reclassification was observed in CAC-DRS 0-1, where 13 were recategorized, particularly between studies having a CAC Agatston score of 0 versus 1. Qualitative description of the errors showed that the main cause of misclassification was AI underestimation of right coronary calcium, AI overestimation of right ventricle densities and human underestimation of right coronary artery calcium.

CONCLUSION

Correlation between AI and human values is excellent with absolute numbers. When the CAC-DRS classification system was adopted, there was a strong correlation in the respective categories. Misclassified were predominantly in the category of CAC = 0, most often with minimal values of calcium volume. Additional algorithm optimization with enhanced sensitivity and specificity for low values of calcium volume will be required to enhance AI CAC score utilization for minimal disease. Over a broad range of calcium scores, AI software for calcium scoring had an excellent correlation compared to human expert reading and in rare cases determined calcium missed by human interpretation.

Management of patients on antithrombotic therapy with severe infections: a joint clinical consensus statement of the ESC Working Group on Thrombosis, the ESC Working Group on Atherosclerosis and Vascular Biology, and the International Society on Thrombosis and Haemostasis

Patients with severe infections and a pre-existing indication for antithrombotic therapy, i.e. antiplatelet agents, anticoagulant drugs, or their combinations, require integrated clinical counselling among coagulation, infectious disease, and cardiology specialists, due to sepsis-induced coagulopathy that frequently occurs. Bacterial and viral pathogens constitute an increasing threat to global public health, especially for patients with ongoing antithrombotic treatment who have a high risk of thrombotic recurrences and high susceptibility to severe infections with increased morbidity and mortality. Similarly, sepsis survivors are at increased risk for major vascular events. Coagulopathy, which often complicates severe infections, is associated with a high mortality and obligates clinicians to adjust antithrombotic drug type and dosing to avoid bleeding while preventing thrombotic complications. This clinical consensus statement reviews the best available evidence to provide expert opinion and statements on the management of patients hospitalized for severe bacterial or viral infections with a pre-existing indication for antithrombotic therapy (single or combined), in whom sepsis-induced coagulopathy is often observed. Balancing the risk of thrombosis and bleeding in these patients and preventing infections with vaccines, if available, are crucial to prevent events or improve outcomes and prognosis.

Comparison of coronary artery calcium score and cardiovascular risk-stratification by European Society of Cardiology Guidelines and Steno Type 1 Risk Engine in statin-naïve adults with type 1 diabetes

BACKGROUND

Coronary artery calcium (CAC) is a marker of atherosclerotic cardiovascular disease (CVD). However, for patients with type 1 diabetes (T1D), its relationship with T1D-specific cardiovascular (CV) risk-stratification tools is unknown.

AIMS

Assess prevalence of CAC and evaluate relationship between CAC and T1D-specific CV risk-stratification methods in T1D.

METHODS

Cross-sectional study of adults with T1D age 20-60 years, statin-naïve and no history of CVD. Data was obtained from electronic medical records and by interview. Presence of CAC was assessed using non-contrast cardiac computed tomography and quantified by Agatston Units (AU). CV risk-stratification was assessed using the 2019 European Society of Cardiology (ESC) Guidelines and the Steno T1 Risk Engine (ST1RE).

RESULTS

85 patients were included with mean age 35.4 ± 10.3 years, HbA1c 8.3 ± 1.5 % and T1D duration 17.0 ± 10.1 years. 67 patients (78.9 %) had a CAC score of 0 AU, 17 (20.0 %) >0-100 AU, and one (1.2 %) >100 AU. Duration of T1D (p = 0.009), body mass index (p = 0.029), neuropathy (p = 0.016) and low-density lipoprotein cholesterol levels (p = 0.016) were independently associated with a positive CAC score on multivariate analysis. Positive predictive value for a positive CAC score was 85.7 % for the ST1RE high risk category and 31.3 % for the 2019 ESC Guidelines very high risk category.

CONCLUSIONS

One-fifth of this T1D cohort had a positive CAC score. The ST1RE was superior in identifying positive CAC compared to the 2019 ESC Guidelines. Further studies are required to elucidate the role of CAC in personalising CV risk-stratification and statin initiation in T1D.

Targeting macrophages in atherosclerosis using nanocarriers loaded with liver X receptor agonists: A narrow review

Macrophages are involved in the whole process of atherosclerosis, which is characterized by accumulation of lipid and inflammation. Presently, clinically used lipid-lowering drugs cannot completely retard the progress of atherosclerosis. Liver X receptor (LXR) plays a key role in regulation of lipid metabolism and inflammation. Accumulating evidence have demonstrated that synthetic LXR agonists can significantly retard the development of atherosclerosis. However, these agonists induce sever hypertriglyceridemia and liver steatosis. These side effects have greatly limited their potential application for therapy of atherosclerosis. The rapid development of drug delivery system makes it possible to delivery interested drugs to special organs or cells using nanocarriers. Macrophages express various receptors which can recognize and ingest specially modified nanocarriers loaded with LXR agonists. In the past decades, a great progress has been made in this field. These macrophage-targeted nanocarriers loaded with LXR agonists are found to decrease atherosclerosis by reducing cholesterol accumulation and inflammatory reactions. Of important, these nanocarriers can alleviate side effects of LXR agonists. In this article, we briefly review the roles of macrophages in atherosclerosis, mechanisms of action of LXR agonists, and focus on the advances of macrophage-targeted nanocarriers loaded with LXR agonists. This work may promote the potential clinical application of these nanocarriers.