Mean Versus Peak Coronary Calcium Density on Non-Contrast CT: Calcium Scoring and ASCVD Risk Prediction

ObjectivesThis study sought to assess the relationship between mean vs peak calcified plaque density and their impact on calculating coronary artery calcium (CAC) scores and to compare the corresponding differential prediction of atherosclerotic cardiovascular disease (ASCVD) and coronary heart disease (CHD) mortality.BackgroundThe Agatston CAC score is quantified per lesion as the product of plaque area and a 4-level categorical peak calcium density factor. However, mean calcium density may more accurately measure the heterogenous mixture of lipid-rich, fibrous, and calcified plaque reflective of ASCVD risk.MethodsWe included 10,373 individuals from the CAC Consortium who had CAC >0 and per-vessel measurements of peak calcium density factor and mean calcium density. Area under the curve and continuous net reclassification improvement analyses were performed for CHD and ASCVD mortality to compare the predictive abilities of mean calcium density vs peak calcium density factor when calculating the Agatston CAC score.ResultsParticipants were on average 53.4 years of age, 24.4% were women, and the median CAC score was 68 Agatston units. The average values for mean calcium density and peak calcium density factor were 210 ± 50 HU and 3.1 ± 0.5, respectively. Individuals younger than 50 years of age and/or those with a total plaque area <100 mm² had the largest differences between the peak and mean density measures. Among persons with CAC 1-99, the use of mean calcium density resulted in a larger improvement in ASCVD mortality net reclassification improvement (NRI) (NRI = 0.49; P < 0.001 vs. NRI = 0.18; P = 0.08) and CHD mortality discrimination (Δ area under the curve (AUC) = +0.169 vs +0.036; P < 0.001) compared with peak calcium density factor. Neither peak nor mean calcium density improved mortality prediction at CAC scores >100.ConclusionMean and peak calcium density may differentially describe plaque composition early in the atherosclerotic process. Mean calcium density performs better than peak calcium density factor when combined with plaque area for ASCVD mortality prediction among persons with Agatston CAC 1-99.     

Discordance Between Coronary Artery Calcium Area and Density Predicts Long-Term Atherosclerotic Cardiovascular Disease Risk

BackgroundCoronary artery calcium (CAC) is commonly quantified as the product of 2 generally correlated measures: plaque area and calcium density.ObjectivesThe authors sought to determine whether discordance between calcium area and density has long-term prognostic importance in atherosclerotic cardiovascular disease (ASCVD) risk.MethodsThe authors studied 10,373 primary prevention participants from the CAC Consortium with CAC >0. Based on their median values, calcium area and mean calcium density were divided into 4 mutually exclusive concordant/discordant groups. Cox proportional hazards regression assessed the association of calcium area/density groups with ASCVD mortality over a median of 11.7 years, adjusting for traditional risk factors and the Agatston CAC score.ResultsThe mean age was 56.7 years, and 24% were female. The prevalence of plaque discordance was 19% (9% low calcium area/high calcium density, 10% high calcium area/low calcium density). Female sex (odds ratio [OR]: 1.48 [95% CI: 1.27-1.74]) and body mass index (OR: 0.81 [95% CI: 0.76-0.87], per 5 kg/m² higher) were significantly associated with high calcium density discordance, whereas diabetes (OR: 2.23 [95% CI: 1.85-3.19]) was most strongly associated with discordantly low calcium density. Compared to those with low calcium area/low calcium density, individuals with low calcium area/high calcium density had a 71% lower risk of ASCVD death (HR: 0.29 [95% CI: 0.09-0.95]).ConclusionsFor a given CAC score, high calcium density relative to plaque area confers lower long-term ASCVD risk, likely serving as an imaging marker of biological resilience for lesion vulnerability. Additional research is needed to define a robust definition of calcium area/density discordance for routine clinical risk prediction.     

Machine Learning Adds to Clinical and CAC Assessments in Predicting 10-Year CHD and CVD Deaths

ObjectivesThe aim of this study was to evaluate whether machine learning (ML) of noncontrast computed tomographic (CT) and clinical variables improves the prediction of atherosclerotic cardiovascular disease (ASCVD) and coronary heart disease (CHD) deaths compared with coronary artery calcium (CAC) Agatston scoring and clinical data.BackgroundThe CAC score provides a measure of the global burden of coronary atherosclerosis, and its long-term prognostic utility has been consistently shown to have incremental value over clinical risk assessment. However, current approaches fail to integrate all available CT and clinical variables for comprehensive risk assessment.MethodsThe study included data from 66,636 asymptomatic subjects (mean age 54 ± 11 years, 67% men) without established ASCVD undergoing CAC scanning and followed for cardiovascular disease (CVD) and CHD deaths at 10 years. Clinical risk assessment incorporated the ASCVD risk score. For ML, an ensemble boosting approach was used to fit a predictive classifier for outcomes, followed by automated feature selection using information gain ratio. The model-building process incorporated all available clinical and CT data, including the CAC score; the number, volume, and density of CAC plaques; and extracoronary scores; comprising a total of 77 variables. The overall proposed model (ML all) was evaluated using a 10-fold cross-validation framework on the population data and area under the curve (AUC) as metrics. The prediction performance was also compared with 2 traditional scores (ASCVD risk and CAC score) and 2 additional models that were trained using all the clinical data (ML clinical) and CT variables (ML CT).ResultsThe AUC by ML all (0.845) for predicting CVD death was superior compared with those obtained by ASCVD risk alone (0.821), CAC score alone (0.781), and ML CT alone (0.804) (p < 0.001 for all). Similarly, for predicting CHD death, AUC by ML all (0.860) was superior to the other analyses (0.835 for ASCVD risk, 0.816 for CAC, and 0.827 for ML CT; p < 0.001).ConclusionsThe comprehensive ML model was superior to ASCVD risk, CAC score, and an ML model fitted using CT variables alone in the prediction of both CVD and CHD death.     

The Added Value of Coronary Calcium Score in Predicting Cardiovascular Events in Familial Hypercholesterolemia

ObjectivesThis study aimed at investigating the additional contribution of coronary artery calcium (CAC) score to SAFEHEART (Spanish Familial Hypercholesterolemia Cohort Study) risk equation (SAFEHEART-RE) for cardiovascular risk prediction in heterozygous familial hypercholesterolemia (HeFH).BackgroundCommon cardiovascular risk equations are imprecise for HeFH. Because of the high phenotype variability of HeFH, CAC score could help to better stratify the risk of atherosclerotic cardiovascular disease (ASCVD).MethodsREFERCHOL (French Registry of Familial Hypercholesterolemia) and SAFEHEART are 2 ongoing national registries on HeFH. We analyzed data from primary prevention HeFH patients undergoing CAC quantification. We used probability-weighted Cox proportional hazards models to estimate HRs. Area under the receiver-operating characteristic curve (AUC) and net reclassification improvement (NRI) were used to compare the incremental contribution of CAC score when added to the SAFEHEART-RE for ASCVD prediction. ASCVD was defined as coronary heart disease, stroke or transient ischemic attack, peripheral artery disease, resuscitated sudden death, and cardiovascular death.ResultsWe included 1,624 patients (mean age: 48.5 ± 12.8 years; men: 45.7%) from both registries. After a median follow-up of 2.7 years (interquartile range: 0.4-5.0 years), ASCVD occurred in 81 subjects. The presence of a CAC score of >100 was associated with an HR of 32.05 (95% CI: 10.08-101.94) of developing ASCVD as compared to a CAC score of 0. Receiving-operating curve analysis showed a good performance of CAC score alone in ASCVD prediction (AUC: 0.860 [95% CI: 0.853-0.869]). The addition of log(CAC + 1) to SAFEHEART-RE resulted in a significantly improved prediction of ASCVD (AUC: 0.884 [95% CI: 0.871-0.894] for SAFEHEART-RE + log(CAC + 1) vs AUC: 0.793 [95% CI: 0.779-0.818] for SAFEHEART-RE; P < 0.001). These results were confirmed also when considering only hard cardiovascular endpoints. The addition of CAC score was associated with an estimated overall net reclassification improvement of 45.4%.ConclusionsCAC score proved its use in improving cardiovascular risk stratification and ASCVD prediction in statin-treated HeFH.     

Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR: Results From MACHINE Registry

ObjectivesThis study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning–based coronary computed tomography (CT) angiography (cCTA)–derived fractional flow reserve (CT-FFR).BackgroundCT-FFR is used reliably to detect lesion-specific ischemia. Novel CT-FFR algorithms using machine-learning artificial intelligence techniques perform fast and require less complex computational fluid dynamics. Yet, influence of CAC score on diagnostic performance of the machine-learning approach has not been investigated.MethodsA total of 482 vessels from 314 patients (age 62.3 ± 9.3 years, 77% male) who underwent cCTA followed by invasive FFR were investigated from the MACHINE (Machine Learning based CT Angiography derived FFR: a Multi-center Registry) registry data. CAC scores were quantified using the Agatston convention. The diagnostic performance of CT-FFR to detect lesion-specific ischemia was assessed across all Agatston score categories (CAC 0, >0 to <100, 100 to <400, and ≥400) on a per-vessel level with invasive FFR as the reference standard.ResultsThe diagnostic accuracy of CT-FFR versus invasive FFR was superior to cCTA alone on a per-vessel level (78% vs. 60%) and per patient level (83% vs. 73%) across all Agatston score categories. No statistically significant differences in the diagnostic accuracy, sensitivity, or specificity of CT-FFR were observed across the categories. CT-FFR showed good discriminatory power in vessels with high Agatston scores (CAC ≥400) and high performance in low-to-intermediate Agatston scores (CAC >0 to <400) with a statistically significant difference in the area under the receiver-operating characteristic curve (AUC) (AUC: 0.71 [95% confidence interval (CI): 0.57 to 0.85] vs. 0.85 [95% CI: 0.82 to 0.89], p = 0.04). CT-FFR showed superior diagnostic value over cCTA in vessels with high Agatston scores (CAC ≥ 400: AUC 0.71 vs. 0.55, p = 0.04) and low-to-intermediate Agatston scores (CAC >0 to <400: AUC 0.86 vs. 0.63, p < 0.001).ConclusionsMachine-learning–based CT-FFR showed superior diagnostic performance over cCTA alone in CAC with a significant difference in the performance of CT-FFR as calcium burden/Agatston calcium score increased. (Machine Learning Based CT Angiography Derived FFR: a Multicenter, Registry [MACHINE] NCT02805621).     

Coronary Artery Calcium to Improve the Efficiency of Randomized Controlled Trials in Primary Cardiovascular Prevention

ObjectivesThis study sought to assess the value, in terms of sample size and cost, of using the coronary artery calcium (CAC) score to enrich the study population of primary prevention randomized controlled trials (RCTs) with participants at high absolute risk of atherosclerotic cardiovascular disease (ASCVD) events.BackgroundThe feasibility of RCTs assessing the efficacy of novel add-on therapies for primary prevention among high-risk individuals treated with statins may be limited by sample size and cost.MethodsWe evaluated 3,075 statin-naive participants from the MESA (Multi-Ethnic Study of Atherosclerosis) with estimated 10-year ASCVD risk of ≥7.5%. CAC of >100, CAC of >400, high sensitivity C-reactive protein levels of >2 and >3 mg/l, ankle-brachial index of <0.9, and triglyceride levels of >175 mg/dl were each evaluated as enrichment criteria on top of estimated ASCVD risk of ≥7.5%, ≥10%, ≥15% and ≥20%. For each criterion, using the observed 5-year incidence of CVD, we projected the incidence of CVD assuming a 28% relative risk reduction with high-intensity statin therapy and after addition of novel therapy with additive relative risk reductions of 15% and 25%. Sample size and cost of a hypothetical primary prevention 5-year RCT of a novel therapy on top of statins versus statins alone were then computed by using the projected incidences. Yearly costs per included participant of $6,000 to $9,000 and of $500/$600 per screened nonparticipant were assumed.ResultsCAC of >400, present in 15% to 23% participants, consistently identified the subgroups with highest 5-year incident events and outperformed the other features yielding the smallest projected sample size, ranging 33% to 58% lower than using risk estimations alone for participant selection. CAC of >400 also yielded the lowest projected RCT costs, at least $40 million lower than using risk estimations alone. CAC of >100 showed the second-best performance in most scenarios.ConclusionsHigh CAC scores used as study entry criteria can improve the efficiency and feasibility of primary prevention RCTs evaluating the incremental efficacy of novel add-on therapies.     

Relationship Between Coronary Artery Calcium and Atherosclerosis Progression Among Patients With Suspected Coronary Artery Disease

BackgroundAmong symptomatic patients, it remains unclear whether a coronary artery calcium (CAC) score alone is sufficient or misses a sizeable burden and progressive risk associated with obstructive and nonobstructive atherosclerotic plaque.ObjectivesAmong patients with low to high CAC scores, our aims were to quantify co-occurring obstructive and nonobstructive noncalcified plaque and serial progression of atherosclerotic plaque volume.MethodsA total of 698 symptomatic patients with suspected coronary artery disease (CAD) underwent serial coronary computed tomographic angiography (CTA) performed 3.5 to 4.0 years apart. Atherosclerotic plaque was quantified, including by compositional subgroups. Obstructive CAD was defined as ≥50% stenosis. Multivariate linear regression models were used to measure atherosclerotic plaque progression by CAC scores. Cox proportional hazard models estimated CAD event risk (median of 10.7 years of follow-up).ResultsAcross baseline CAC scores from 0 to ≥400, total plaque volume ranged from 30.4 to 522.4 mm³ (P < 0.001) and the prevalence of obstructive CAD increased from 1.4% to 49.1% (P < 0.001). Of those with a 0 CAC score, 97.9% of total plaque was noncalcified. Among patients with baseline CAC <100, nonobstructive CAD was prevalent (40% and 89% in CAC scores of 0 and 1-99), with plaque largely being noncalcified. On the follow-up coronary CTA, volumetric plaque growth (P < 0.001) and the development of new or worsening stenosis (P < 0.001) occurred more among patients with baseline CAC ≥100. Progression varied compositionally by baseline CAC scores. Patients with no CAC had disproportionate growth in noncalcified plaque, and for every 1 mm³ increase in calcified plaque, there was a 5.5 mm³ increase in noncalcified plaque volume. By comparison, patients with CAC scores of ≥400 exhibited disproportionate growth in calcified plaque with a volumetric increase 15.7-fold that of noncalcified plaque. There was a graded increase in CAD event risk by the CAC with rates from 3.3% for no CAC to 21.9% for CAC ≥400 (P < 0.001).ConclusionsCAC imperfectly characterizes atherosclerotic disease burden, but its subgroups exhibit pathogenic patterns of early to advanced disease progression and stratify long-term prognostic risk.     

Coronary Artery Calcium for Risk Stratification of Sudden Cardiac Death: The Coronary Artery Calcium Consortium

BackgroundCoronary artery calcium (CAC) is a marker of plaque burden. Whether CAC improves risk stratification for incident sudden cardiac death (SCD) beyond atherosclerotic cardiovascular disease (ASCVD) risk factors is unknown.ObjectivesSCD is a common initial manifestation of coronary heart disease (CHD); however, SCD risk prediction remains elusive.MethodsThe authors studied 66,636 primary prevention patients from the CAC Consortium. Multivariable competing risks regression and C-statistics were used to assess the association between CAC and SCD, adjusting for demographics and traditional risk factors.ResultsThe mean age was 54.4 years, 33% were women, 11% were of non-White ethnicity, and 55% had CAC >0. A total of 211 SCD events (0.3%) were observed during a median follow-up of 10.6 years, 91% occurring among those with baseline CAC >0. Compared with CAC = 0, there was a stepwise higher risk (P trend < 0.001) in SCD for CAC 100 to 399 (subdistribution hazard ratio [SHR]: 2.8; 95% CI: 1.6-5.0), CAC 400 to 999 (SHR: 4.0; 95% CI: 2.2-7.3), and CAC >1,000 (SHR: 4.9; 95% CI: 2.6-9.9). CAC provided incremental improvements in the C-statistic for the prediction of SCD among individuals with a 10-year risk <7.5% (ΔC-statistic = +0.046; P = 0.02) and 7.5% to 20% (ΔC-statistic = +0.069; P = 0.003), which were larger when compared with persons with a 10-year risk >20% (ΔC-statistic = +0.01; P = 0.54).ConclusionsHigher CAC burden strongly associates with incident SCD beyond traditional risk factors, particularly among primary prevention patients with low-intermediate risk. SCD risk stratification can be useful in the early stages of CHD through the measurement of CAC, identifying patients most likely to benefit from further downstream testing.     

Deep Learning of Coronary Calcium Scores From PET/CT Attenuation Maps Accurately Predicts Adverse Cardiovascular Events

BackgroundAssessment of coronary artery calcium (CAC) by computed tomographic (CT) imaging provides an accurate measure of atherosclerotic burden. CAC is also visible in computed tomographic attenuation correction (CTAC) scans, always acquired with cardiac positron emission tomographic (PET) imaging.ObjectivesThe aim of this study was to develop a deep-learning (DL) model capable of fully automated CAC definition from PET CTAC scans.MethodsThe novel DL model, originally developed for video applications, was adapted to rapidly quantify CAC. The model was trained using 9,543 expert-annotated CT scans and was tested in 4,331 patients from an external cohort undergoing PET/CT imaging with major adverse cardiac events (MACEs) (follow-up 4.3 years), including same-day paired electrocardiographically gated CAC scans available in 2,737 patients. MACE risk stratification in 4 CAC score categories (0, 1-100, 101-400, and >400) was analyzed and CAC scores derived from electrocardiographically gated CT scans (standard scores) by expert observers were compared with automatic DL scores from CTAC scans.ResultsAutomatic DL scoring required <6 seconds per scan. DL CTAC scores provided stepwise increase in the risk for MACE across the CAC score categories (HR up to 3.2; P < 0.001). Net reclassification improvement of standard CAC scores over DL CTAC scores was nonsignificant (−0.02; 95% CI: −0.11 to 0.07). The negative predictive values for MACE of zero CAC with standard (85%) and DL CTAC (83%) CAC scores were similar (P = 0.19).ConclusionsDL CTAC scores predict cardiovascular risk similarly to standard CAC scores quantified manually by experienced operators from dedicated electrocardiographically gated CAC scans and can be obtained almost instantly, with no changes to PET/CT scanning protocol.     

CAC for Risk Stratification Among Individuals With Hypertriglyceridemia Free of Clinical Atherosclerotic Cardiovascular Disease

ObjectivesIn this study, we sought to evaluate whether the coronary artery calcium (CAC) score can enhance current paradigms for risk stratification among individuals with hypertriglyceridemia in primary prevention. The eligibility criteria for icosapent ethyl (IPE) were used as case example.BackgroundRecent trials of atherosclerotic cardiovascular disease (ASCVD) risk-reduction therapies for individuals with hypertriglyceridemia without clinical ASCVD restricted enrollment to participants with diabetes or various other risk factors. These criteria were mirrored in the Food and Drug Administration product label for IPE.MethodsWe pooled 2,345 participants with triglycerides 150 to <500 mg/dL (or >178-<500 mg/dL if not on a statin) and without clinical ASCVD from MESA, CARDIA, the Dallas Heart Study, and the Heinz Nixdorf Recall study. We evaluated the incidence of ASCVD events overall, by IPE eligibility (as defined in the product label), and further stratified by CAC scores (0, >0-100, >100). The number needed to treat for 5 years (NNT₅) to prevent 1 event was estimated among IPE-eligible participants, assuming a 21.8% relative risk reduction with IPE. In exploratory analyses, the NNT₅ was also estimated among noneligible participants.ResultsThere was marked heterogeneity in CAC burden overall (45% CAC 0; 24% CAC >100) and across IPE eligibility strata. Overall, 17% of participants were eligible for IPE and 11.9% had ASCVD events within 5 years. Among participants eligible for IPE, 38% had CAC >100, and their event rates were markedly higher (15.9% vs 7.2%) and the NNT₅ 2.2-fold lower (29 vs 64) than those of the 25% eligible participants with CAC 0. Among the 83% participants not eligible for IPE, 20% had CAC >100, and their 5-year incidence of ASCVD (13.9%) was higher than the overall incidence among IPE-eligible participants.ConclusionsCAC can improve current risk stratification and therapy allocation paradigms among individuals with hypertriglyceridemia without clinical ASCVD. Future trials of risk-reduction therapies in hypertriglyceridemia could use CAC >100 to enroll a high-risk study sample, with implications for a larger target population.     

Comparing Risk Scores in the Prediction of Coronary and Cardiovascular Deaths: Coronary Artery Calcium Consortium

ObjectivesThis study compared risk discrimination for the prediction of coronary heart disease (CHD) and cardiovascular disease (CVD) deaths for the Pooled Cohort Equations (PCE), the MESA (Multi-Ethnic Study of Atherosclerosis) Risk Score (with and without coronary artery calcium [CAC]), and of simple addition of CAC to the PCE.BackgroundThe PCE predict 10-year risk of atherosclerotic CVD events, and the MESA Risk Score predicts risk of CHD. Their comparative performance for the prediction of fatal events is poorly understood.MethodsWe evaluated 53,487 patients ages 45 to 79 years from the CAC Consortium, a retrospective cohort study of asymptomatic individuals referred for clinical CAC scoring. Risk discrimination was measured using C-statistics.ResultsMean age was 57 years, 35% were women, and 39% had CAC of 0. There were 421 CHD and 775 CVD deaths over a mean 12-year follow-up. In the overall study population, discrimination with the MESA Risk Score with CAC and the PCE was almost identical for both outcomes (C-statistics: 0.80 and 0.79 for CHD death, 0.77 and 0.78 for CVD death, respectively). Addition of CAC to the PCE improved risk discrimination, yielding the largest C-statistics. The MESA Risk Score with CAC and the PCE plus CAC showed the best discrimination among the 45% of patients with 5% to 20% estimated risk. Secondary analyses by estimated CVD risk strata showed modestly improved risk discrimination with CAC also among low- and high-estimated risk groups.ConclusionsOur findings support the current guideline recommendation to use, among available risk scores, the PCE for initial risk assessment and to use CAC for further risk assessment in a broad borderline and intermediate risk group. Also, in select individuals at low or high estimated risk, CAC modestly improved discrimination. Studies in unselected populations will lead to further understanding of the potential value of tools combining risk scores and CAC for optimal risk assessment.     

Advances in Coronary Computed Tomographic Angiographic Imaging of Atherosclerosis for Risk Stratification and Preventive Care

The diagnostic evaluation of coronary artery disease is undergoing a dramatic transformation with a new focus on atherosclerotic plaque. This review details the evidence needed for effective risk stratification and targeted preventive care based on recent advances in automated measurement of atherosclerosis from coronary computed tomography angiography (CTA). To date, research findings support that automated stenosis measurement is reasonably accurate, but evidence on variability by location, artery size, or image quality is unknown. The evidence for quantification of atherosclerotic plaque is unfolding, with strong concordance reported between coronary CTA and intravascular ultrasound measurement of total plaque volume (r >0.90). Statistical variance is higher for smaller plaque volumes. Limited data are available on how technical or patient-specific factors result in measurement variability by compositional subgroups. Coronary artery dimensions vary by age, sex, heart size, coronary dominance, and race and ethnicity. Accordingly, quantification programs excluding smaller arteries affect accuracy for women, patients with diabetes, and other patient subsets. Evidence is unfolding that quantification of atherosclerotic plaque is useful to enhance risk prediction, yet more evidence is required to define high-risk patients across varied populations and to determine whether such information is incremental to risk factors or currently used coronary computed tomography techniques (eg, coronary artery calcium scoring or visual assessment of plaque burden or stenosis). In summary, there is promise for the utility of coronary CTA quantification of atherosclerosis, especially if it can lead to targeted and more intensive cardiovascular prevention, notably for those patients with nonobstructive coronary artery disease and high-risk plaque features. The new quantification techniques available to imagers must not only provide sufficient added value to improve patient care, but also add minimal and reasonable cost to alleviate the financial burden on our patients and the health care system.     

Coronary Artery Calcium Versus Pooled Cohort Equations Score for Primary Prevention Guidance: Randomized Feasibility Trial

ObjectivesThis study sought to determine the feasibility of performing an extensive randomized outcomes trial comparing a coronary artery calcium (CAC)- versus a pooled cohort equations (PCE) risk score–based strategy for initiating statin therapy for primary atherosclerotic cardiovascular disease (ASCVD) prevention.BackgroundStatin therapy is standard for the primary prevention of ASCVD in subjects at increased risk. National guidelines recommend using the American College of Cardiology/American Heart Association PCE risk score to guide a statin recommendation. Whether guidance by a CAC score is equivalent or superior is unknown.MethodsCorCal (Effectiveness of a Proactive Cardiovascular Primary Prevention Strategy, With or Without the Use of Coronary Calcium Screening, in Preventing Future Major Adverse Cardiac Events) was a randomized trial consenting 601 patients without known ASCVD, diabetes, or prior statin therapy recruited from primary care clinics and randomized to CAC- (n = 302) or PCE guidance (n = 299) of statin initiation for primary prevention. Enrolled subjects and their physicians made final treatment decisions. Primary outcomes compared the proportion of statin recommendations received and subject adherence over 1 year between CAC- and PCE-arm subjects. Modeled medical costs, adverse effects, and low-density lipoprotein–cholesterol (LDL-C) were additional measures of interest.ResultsSubjects were well matched, and 540 (89.9%) completed entry testing and received a protocol-based recommendation. A statin was recommended in 101 (35.9%) CAC-arm and 124 (47.9%) PCE-arm subjects (P = 0.005). Compared to PCE-based recommendations, CAC-arm subjects were reclassified from statin to no statin in 36.0% and from no statin to statin in 5.6% of cases, resulting in a total reclassification of 20.6%. Physicians accepted the study-dictated recommendation to start a statin in 88.1% of CAC-arm vs 75.0% of PCE-arm subjects (P = 0.01). Patient-reported adherence to this recommendation at 3 months was 62.2% vs 42.2%, respectively (P = 0.009). At 1 year, statin adherence remained superior, LDL-C levels were lower, estimated costs were similar or reduced in CAC subjects, and few events occurred.ConclusionsCAC guidance may be a more efficient, personalized, cost-effective, and motivating approach to statin initiation and maintenance in primary prevention. This feasibility phase of CorCal should be regarded as hypothesis-generating with respect to cardiovascular outcomes, which is being addressed in a large, longer-term outcomes trial. (Effectiveness of a Proactive Cardiovascular Primary Prevention Strategy, With or Without the Use of Coronary Calcium Screening, in Preventing Future Major Adverse Cardiac Events [CorCal]; NCT03439267)     

Coronary Calcium to Rule Out Obstructive Coronary Artery Disease in Patients With Acute Chest Pain

ObjectivesThis study aimed to evaluate the ability of coronary artery calcium (CAC) as an initial diagnostic tool to rule out obstructive coronary artery disease (CAD) in a very large registry of patients presenting to the emergency department (ED) with acute chest pain (CP) who were at low to intermediate risk for acute coronary syndrome (ACS).BackgroundIt is not yet well established whether CAC can be used to rule out obstructive CAD in the ED setting.MethodsWe included patients from the Baptist Health South Florida Chest Pain Registry presenting to the ED with CP at low to intermediate risk for ACS (Thrombolysis In Myocardial Infarction risk score ≤2, normal/nondiagnostic electrocardiography, and troponin levels) who underwent CAC and coronary computed tomography angiography (CCTA) procedures for evaluation of ACS. To assess the diagnostic accuracy of CAC testing to diagnose obstructive CAD and identify the need for coronary revascularization during hospitalization, we estimated sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV).ResultsOur study included 5,192 patients (mean age: 53.5 ± 10.8 years; 46% male; 62% Hispanic). Overall, 2,902 patients (56%) had CAC = 0, of which 135 (4.6%) had CAD (114 [3.9%] nonobstructive and 21 [0.7%] obstructive). Among those with CAC >0, 23% had obstructive CAD. Sensitivity, specificity, PPV, and NPV of CAC testing to diagnose obstructive CAD were 96.2%, 62.4%, 22.4%, and 99.3%, respectively. The NPV for identifying those who needed revascularization was 99.6%. Among patients with CAC = 0, 11 patients (0.4%) underwent revascularization, and the number needed to test with CCTA to detect 1 patient who required revascularization was 264.ConclusionsIn a large population presenting to ED with CP at low to intermediate risk, CAC = 0 was common. CAC = 0 ruled out obstructive CAD and revascularization in more than 99% of the patients, and <5% with CAC = 0 had any CAD. Integrating CAC testing very early in CP evaluation may be effective in appropriate triage of patients by identifying individuals who can safely defer additional testing and more invasive procedures.     

Targeted Coronary Artery Calcium Screening in High-Risk Younger Individuals Using Consumer Genetic Screening Results

ObjectivesThe goal of this study was to assess the utility of a genetic risk score (GRS) in targeted coronary artery calcium (CAC) screening among young individuals.BackgroundEarly CAC screening and preventive therapy may reduce long-term risk of a coronary heart disease (CHD) event. However, identifying younger individuals at increased risk remains a challenge. GRS for CHD are age independent and can stratify individuals on various risk trajectories.MethodsUsing 142 variants associated with CHD events, we calculated a GRS in 1,927 individuals in the CARDIA (Coronary Artery Risk Development in Young Adults) cohort (aged 32 to 47 years) and 6,600 individuals in the MESA (Multi-Ethnic Study of Atherosclerosis) cohort (aged 44 to 87 years). We assessed GRS utility to predict CAC presence in the CARDIA cohort and stratify individuals of varying risk for CAC presence over the lifetime in both cohorts.ResultsThe GRS predicted CAC presence in CARDIA males. It was not predictive in CARDIA females, which had a CAC prevalence of 6.4%. In combined analysis of the CARDIA and MESA cohorts, the GRS was predictive of CAC in both males and females and was used to derive an equation for the age at which CAC probability crossed a predetermined threshold. When assessed in combination with traditional risk factors, the GRS further stratified individuals. For individuals with an equal number of traditional risk factors, probability of CAC reached 25% approximately 10 years earlier for those in the highest GRS quintile compared to the lowest.ConclusionsThe GRS may be used to target high-risk younger individuals for early CAC screening.     

Impacto de los tratamientos hipolipemiantes en los resultados cardiovasculares según la puntuación de calcio coronario. Revisión sistemática y metanálisis

Introduction and objectivesCoronary artery calcium (CAC) score improves the accuracy of risk stratification for atherosclerotic cardiovascular disease (ASCVD) events compared with traditional cardiovascular risk factors. We evaluated the interaction of coronary atherosclerotic burden as determined by the CAC score with the prognostic benefit of lipid-lowering therapies in the primary prevention setting.MethodsWe reviewed the MEDLINE, EMBASE, and Cochrane databases for studies including individuals without a previous ASCVD event who underwent CAC score assessment and for whom lipid-lowering therapy status stratified by CAC values was available. The primary outcome was ASCVD. The pooled effect of lipid-lowering therapy on outcomes stratified by CAC groups (0, 1-100, > 100) was evaluated using a random effects model.ResultsFive studies (1 randomized, 2 prospective cohort, 2 retrospective) were included encompassing 35 640 individuals (female 38.1%) with a median age of 62.2 [range, 49.6-68.9] years, low-density lipoprotein cholesterol level of 128 (114-146) mg/dL, and follow-up of 4.3 (2.3-11.1) years. ASCVD occurrence increased steadily across growing CAC strata, both in patients with and without lipid-lowering therapy. Comparing patients with (34.9%) and without (65.1%) treatment exposure, lipid-lowering therapy was associated with reduced occurrence of ASCVD in patients with CAC > 100 (OR, 0.70; 95%CI, 0.53-0.92), but not in patients with CAC 1-100 or CAC 0. Results were consistent when only adjusted data were pooled.ConclusionsAmong individuals without a previous ASCVD, a CAC score > 100 identifies individuals most likely to benefit from lipid-lowering therapy, while undetectable CAC suggests no treatment benefit.Full English text available from:www.revespcardiol.org/en     

Primary Prevention Trial Designs Using Coronary Imaging: A National Heart,Lung, and Blood Institute Workshop

Coronary artery calcium (CAC) is considered a useful test for enhancing risk assessment in the primary prevention setting. Clinical trials are under consideration. The National Heart, Lung, and Blood Institute convened a multidisciplinary working group on August 26 to 27, 2019, in Bethesda, Maryland, to review available evidence and consider the appropriateness of conducting further research on coronary artery calcium (CAC) testing, or other coronary imaging studies, as a way of informing decisions for primary preventive treatments for cardiovascular disease. The working group concluded that additional evidence to support current guideline recommendations for use of CAC in middle-age adults is very likely to come from currently ongoing trials in that age group, and a new trial is not likely to be timely or cost effective. The current trials will not, however, address the role of CAC testing in younger adults or older adults, who are also not addressed in existing guidelines, nor will existing trials address the potential benefit of an opportunistic screening strategy made feasible by the application of artificial intelligence. Innovative trial designs for testing the value of CAC across the lifespan were strongly considered and represent important opportunities for additional research, particularly those that leverage existing trials or other real-world data streams including clinical computed tomography scans. Sex and racial/ethnic disparities in cardiovascular disease morbidity and mortality, and inclusion of diverse participants in future CAC trials, particularly those based in the United States, would enhance the potential impact of these studies.     

Interplay of Risk Factors and Coronary Artery Calcium for CHD Risk in Young Patients

ObjectivesThe aim of this study was to examine prevalence, predictors, and impact of coronary artery calcium (CAC) across different risk factor burdens on the prevalence of obstructive coronary artery disease (CAD) and future coronary heart disease (CHD) risk in young patients.BackgroundThe interplay of risk factors and CAC for predicting CHD in young patients aged ≤45 years is not clear.MethodsThe study included 3,691 symptomatic patients (18-45 years of age) from the WDHR (Western Denmark Heart Registry) undergoing coronary computed tomographic angiography. CHD events were myocardial infarction and late revascularization.ResultsDuring a median of 4.1 years of follow-up, 57 first-time CHD events occurred. In total, 3,180 patients (86.1%) had CAC = 0 and 511 patients (13.9%) had CAC >0. Presence of CAC increased with number of risk factors (odds ratio: 4.5 [95% CI: 2.7-7.3] in patients with >3 vs 0 risk factors). The prevalence of obstructive CAD at baseline and the rate of future CHD events increased in a stepwise manner with both higher CAC and number of risk factors. The CHD event rate was lowest at 0.5 (95% CI: 0.1-3.6) per 1,000 person-years in patients with 0 risk factors and CAC = 0. Among patients with >3 risk factors, the event rate was 3.1 (95% CI: 1.0-9.7) in patients with CAC = 0 compared with 36.3 (95% CI: 17.3-76.1) in patients with CAC >10.ConclusionsIn young patients, there is a strong interplay between CAC and risk factors for predicting the presence of obstructive CAD and for future CHD risk. In the presence of risk factors, even a low CAC score is a high-risk marker. These results demonstrate the importance of assessing risk factors and CAC simultaneously when assessing risk in young patients.     

Triglycerides and Residual Atherosclerotic Risk

BackgroundEven when low-density lipoprotein-cholesterol (LDL-C) levels are lower than guideline thresholds, a residual risk of atherosclerosis remains. It is unknown whether triglyceride (TG) levels are associated with subclinical atherosclerosis and vascular inflammation regardless of LDL-C.ObjectivesThis study sought to assess the association between serum TG levels and early atherosclerosis and vascular inflammation in apparently healthy individuals.MethodsAn observational, longitudinal, and prospective cohort study, including 3,754 middle-aged individuals with low to moderate cardiovascular risk from the PESA (Progression of Early Subclinical Atherosclerosis) study who were consecutively recruited between June 2010 and February 2014, was conducted. Peripheral atherosclerotic plaques were assessed by 2-dimensional vascular ultrasound, and coronary artery calcification (CAC) was assessed by noncontrast computed tomography, whereas vascular inflammation was assessed by fluorine-18 fluorodeoxyglucose uptake on positron emission tomography.ResultsAtherosclerotic plaques and CAC were observed in 58.0% and 16.8% of participants, respectively, whereas vascular inflammation was evident in 46.7% of evaluated participants. After multivariate adjustment, TG levels ≥150 mg/dl showed an association with subclinical noncoronary atherosclerosis (odds ratio [OR]: 1.35; 95% confidence interval [CI]: 1.08 to 1.68; p = 0.008). This association was significant for groups with high LDL-C (OR: 1.42; 95% CI: 1.11 to 1.80; p = 0.005) and normal LDL-C (OR: 1.85; 95% CI: 1.08 to 3.18; p = 0.008). No association was found between TG level and CAC score. TG levels ≥150 mg/dl were significantly associated with the presence of arterial inflammation (OR: 2.09; 95% CI: 1.29 to 3.40; p = 0.003).ConclusionsIn individuals with low to moderate cardiovascular risk, hypertriglyceridemia was associated with subclinical atherosclerosis and vascular inflammation, even in participants with normal LDL-C levels. (Progression of Early Subclinical Atherosclerosis [PESA]; NCT01410318)     

Risk Stratification With the Use of Coronary Computed Tomographic Angiography in Patients With Nonobstructive Coronary Artery Disease

ObjectivesThe purpose of this study was to develop a risk prediction model for patients with nonobstructive CAD.BackgroundAmong stable chest pain patients, most cardiovascular (CV) events occur in those with nonobstructive coronary artery disease (CAD). Thus, developing tailored risk prediction approaches in this group of patients, including CV risk factors and CAD characteristics, is needed.MethodsIn PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) computed tomographic angiography patients, a core laboratory assessed prevalence of CAD (nonobstructive 1% to 49% left main or 1% to 69% stenosis any coronary artery), degree of stenosis (minimal: 1% to 29%; mild: 30% to 49%; or moderate: 50% to 69%), high-risk plaque (HRP) features (positive remodeling, low-attenuation plaque, and napkin-ring sign), segment involvement score (SIS), and coronary artery calcium (CAC). The primary end point was an adjudicated composite of unstable angina pectoris, nonfatal myocardial infarction, and death. Cox regression analysis determined independent predictors in nonobstructive CAD.ResultsOf 2,890 patients (age 61.7 years, 46% women) with any CAD, 90.4% (n = 2,614) had nonobstructive CAD (mean age 61.6 yrs, 46% women, atherosclerotic cardiovascular disease [ASCVD] risk 16.2%). Composite events were independently predicted by ASCVD risk (hazard ratio [HR]: 1.03; p = 0.001), degree of stenosis (30% to 69%; HR: 1.91; p = 0.011), and presence of ≥2 HRP features (HR: 2.40; p = 0.008). Addition of ≥2 HRP features to: 1) ASCVD and CAC; 2) ASCVD and SIS; or 3) ASCVD and degree of stenosis resulted in a statistically significant improvement in model fit (p = 0.0036; p = 0.0176; and p = 0.0318; respectively). Patients with ASCVD ≥7.5%, any HRP, and mild/moderate stenosis had significantly higher event rates than those who did not meet those criteria (3.0% vs. 6.2%; p = 0.007).ConclusionsAdvanced coronary plaque features have incremental value over total plaque burden for the discrimination of clinical events in low-risk stable chest pain patients with nonobstructive CAD. This may be a first step to improve prevention in this cohort with the highest absolute risk for CV events.