Aspirin and Statin Therapy for Nonobstructive Coronary Artery Disease: Five-year Outcomes from the CONFIRM Registry

Purpose: In this cohort study, 5-year data from the Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry (ie, CONFIRM) were examined to identify associations of baseline aspirin and statin use with mortality, major adverse cardiovascular events (MACE), and myocardial infarction (MI) in individuals without substantial (≥50%) stenosis. Materials and methods: In this prospective cohort study, all participants in the registry underwent coronary CT angiography and were classified as having no detectable coronary plaque or having nonobstructive coronary artery disease (CAD) (1%-49% stenosis). Participants with obstructive (≥50%) stenosis were excluded from analysis. The study commenced in June 2003 and was completed in March 2016. All unadjusted and risk-adjusted analyses utilized the Cox proportional hazard model with hospital sites modeled using shared frailty. Results: A total of 6386 participants with no detectable plaque or with nonobstructive CAD were included (mean age, 56.0 years ± 13.3 [SD], 52% men). The mean follow-up period was 5.66 years ± 1.10. Nonobstructive CAD (n = 2815, 44% of all participants included in the study) was associated with a greater risk of all-cause mortality (10.6% [298 of 2815] vs 4.8% [170 of 3571], P < .001) compared to those without CAD (n = 3571, 56%). Baseline aspirin and statin use was documented for 1415 and 1429 participants, respectively, with nonobstructive CAD, and for 1560 and 1565 participants without detectable plaque, respectively. In individuals with nonobstructive CAD, baseline aspirin use was not associated with a reduction in MACE (10.9% [102 of 936] vs 14.7% [52 of 355], P = .06), all-cause mortality (9.6% [95 of 991] vs 10.9% [46 of 424], P = .468), or MI (4.4% [41 of 936] vs 6.2% [22 of 355], P = .18). On multivariate risk-adjusted analysis, baseline statin use was associated with a lower rate of MACE (hazard ratio, 0.59; 95% CI: 0.40, 0.87; P = .007). Neither therapy improved clinical outcomes for participants with no detectable plaque. Conclusion: In participants with nonobstructive CAD, baseline use of statins, but not of aspirin, was associated with improved clinical outcomes. Neither therapy was associated with benefit in participants without plaque.Keywords: Aspirin, Statin, Coronary Artery Disease, CT Angiography, Nonobstructive Coronary Artery DiseaseClinical trial registration no. NCT01443637 Supplemental material is available for this article.ope

Deep Learning-Based Stenosis Quantification From Coronary CT Angiography

Background: Coronary computed tomography angiography (CTA) allows quantification of stenosis. However, such quantitative analysis is not part of clinical routine. We evaluated the feasibility of utilizing deep learning for quantifying coronary artery disease from CTA. Methods: A total of 716 diseased segments in 156 patients (66 ± 10 years) who underwent CTA were analyzed. Minimal luminal area (MLA), percent diameter stenosis (DS), and percent contrast density difference (CDD) were measured using semi-automated software (Autoplaque) by an expert reader. Using the expert annotations, deep learning was performed with convolutional neural networks using 10-fold cross-validation to segment CTA lumen and calcified plaque. MLA, DS and CDD computed using deep-learning-based approach was compared to expert reader measurements. Results: There was excellent correlation between the expert reader and deep learning for all quantitative measures (r=0.984 for MLA; r=0.957 for DS; and r=0.975 for CDD, p<0.001 for all). The expert reader and deep learning method was not significantly different for MLA (median 4.3 mm2 for both, p=0.68) and CDD (11.6 vs 11.1%, p=0.30), and was significantly different for DS (26.0 vs 26.6%, p<0.05); however, the ranges of all the quantitative measures were within inter-observer variability between 2 expert readers. Conclusions: Our deep learning-based method allows quantitative measurement of coronary artery disease segments accurately from CTA and may enhance clinical reporting.ope

Is metabolic syndrome predictive of prevalence, extent, and risk of coronary artery disease beyond its components? Results from the multinational coronary CT angiography evaluation for clinical outcome: an international multicenter registry (CONFIRM)

Although metabolic syndrome is associated with increased risk of cardiovascular disease and events, its added prognostic value beyond its components remains unknown. This study compared the prevalence, severity of coronary artery disease (CAD), and prognosis of patients with metabolic syndrome to those with individual metabolic syndrome components. The study cohort consisted of 27125 consecutive individuals who underwent ≥ 64-detector row coronary CT angiography (CCTA) at 12 centers from 2003 to 2009. Metabolic syndrome was defined as per NCEP/ATP III criteria. Metabolic syndrome patients (n = 690) were matched 1:1:1 to those with 1 component (n = 690) and 2 components (n = 690) of metabolic syndrome for age, sex, smoking status, and family history of premature CAD using propensity scoring. Major adverse cardiac events (MACE) were defined by a composite of myocardial infarction (MI), acute coronary syndrome, mortality and late target vessel revascularization. Patients with 1 component of metabolic syndrome manifested lower rates of obstructive 1-, 2-, and 3-vessel/left main disease compared to metabolic syndrome patients (9.4% vs 13.8%, 2.6% vs 4.5%, and 1.0% vs 2.3%, respectively; p 0.05). At 2.5 years, metabolic syndrome patients experienced a higher rate of MACE compared to patients with 1 component (4.4% vs 1.6%; p = 0.002), while no difference observed compared to individuals with 2 components (4.4% vs 3.2% p = 0.25) of metabolic syndrome. In conclusion, Metabolic syndrome patients have significantly greater prevalence, severity, and prognosis of CAD compared to patients with 1 but not 2 components of metabolic syndrome.ope

Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data

Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how these differing plaque composition profiles impact plaque progression. Patients with coronary atherosclerotic plaque (n = 947; median age, 62 years; 59% male) were enrolled from a prospective multi-national registry of consecutive patients who underwent serial coronary computed tomography angiography (median inter-scan duration, 3.3 years). K-means clustering applied to the percent volume of each plaque component and identified 4 clusters of patients with distinct plaque composition. Cluster 1 (n = 52), which comprised mainly fibro-fatty plaque with a significant necrotic core (median, 55.7% and 16.0% of the total plaque volume, respectively), showed the least total plaque volume (PV) progression (+ 23.3 mm3), with necrotic core and fibro-fatty PV regression (- 5.7 mm3 and - 5.6 mm3, respectively). Cluster 2 (n = 219), which contained largely fibro-fatty (39.2%) and fibrous plaque (46.8%), showed fibro-fatty PV regression (- 2.4 mm3). Cluster 3 (n = 376), which comprised mostly fibrous (62.7%) and calcified plaque (23.6%), showed increasingly prominent calcified PV progression (+ 21.4 mm3). Cluster 4 (n = 300), which comprised mostly calcified plaque (58.7%), demonstrated the greatest total PV increase (+ 50.7mm3), predominantly increasing in calcified PV (+ 35.9 mm3). Multivariable analysis showed higher risk for plaque progression in Clusters 3 and 4, and higher risk for adverse cardiac events in Clusters 2, 3, and 4 compared to that in Cluster 1. Unsupervised clustering algorithms may uniquely characterize patient phenotypes with varied atherosclerotic plaque profiles, yielding distinct patterns of progressive disease and outcome.ope

Development and External Validation of a Deep Learning Algorithm for Prognostication of Cardiovascular Outcomes

BACKGROUND AND OBJECTIVES: We aim to explore the additional discriminative accuracy of a deep learning (DL) algorithm using repeated-measures data for identifying people at high risk for cardiovascular disease (CVD), compared to Cox hazard regression. METHODS: Two CVD prediction models were developed from National Health Insurance Service-Health Screening Cohort (NHIS-HEALS): a Cox regression model and a DL model. Performance of each model was assessed in the internal and 2 external validation cohorts in Koreans (National Health Insurance Service-National Sample Cohort; NHIS-NSC) and in Europeans (Rotterdam Study). A total of 412,030 adults in the NHIS-HEALS; 178,875 adults in the NHIS-NSC; and the 4,296 adults in Rotterdam Study were included. RESULTS: Mean ages was 52 years (46% women) and there were 25,777 events (6.3%) in NHIS-HEALS during the follow-up. In internal validation, the DL approach demonstrated a C-statistic of 0.896 (95% confidence interval, 0.886-0.907) in men and 0.921 (0.908-0.934) in women and improved reclassification compared with Cox regression (net reclassification index [NRI], 24.8% in men, 29.0% in women). In external validation with NHIS-NSC, DL demonstrated a C-statistic of 0.868 (0.860-0.876) in men and 0.889 (0.876-0.898) in women, and improved reclassification compared with Cox regression (NRI, 24.9% in men, 26.2% in women). In external validation applied to the Rotterdam Study, DL demonstrated a C-statistic of 0.860 (0.824-0.897) in men and 0.867 (0.830-0.903) in women, and improved reclassification compared with Cox regression (NRI, 36.9% in men, 31.8% in women). CONCLUSIONS: A DL algorithm exhibited greater discriminative accuracy than Cox model approaches. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02931500.ope

Comparison of the JNC7 and 2017 American College of Cardiology/American Heart Association Guidelines for the Management of Hypertension in Koreans: Analysis of Two Independent Nationwide Population-Based Studies

The optimal blood pressure (BP) guidelines in Asian populations have not been determined. We compared all-cause and cardiovascular mortality based on the Joint National Committee 7 (JNC7) and 2017 American College of Cardiology/American Heart Association (ACC/AHA) guidelines. The National Health Insurance System-National Health Screening Cohort (NHIS-HEALS) and Korea National Health and Nutrition Examination Survey (KNHANES) were utilized. BPs were classified into three groups according to each guideline, and survival rates were analyzed with Kaplan-Meier curves and log-rank tests. Hazard ratios (HRs) were calculated using multivariable cox regression analyses, and the discriminatory ability for clinical outcomes was assessed by Harrell's C-indexes. The JNC7 guidelines demonstrated a linear association between BP levels and survival outcomes. Adjusted HRs from the JNC7 guidelines differentiated the hypertension group (≥140/90) from the pre (130/80-139/89) and normal (<130 and <80) BP groups in clinical outcomes. In contrast, the 2017 ACC/AHA guidelines showed inconsistent survival outcomes according to BP classification (normal: <120 and <80, elevated: 120-129, and <80, and HTN: ≥130/80). According to Harrell's C-indexes, the JNC7 guidelines had greater discrimination ability in survival outcomes in the NHIS-HEALS dataset. Our results suggest that the JNC7 guidelines are more appropriate than the 2017 ACC/AHA guidelines in Korean populations.ope

The Change of Cardiovascular Parameters in Different Thyroid Function States in Patients with Differentiated Thyroid Cancer

Background and Objectives: Some patients with differentiated thyroid cancer experience short-term hypothyroidism in preparation for radioiodine (RAI) therapy. It is not clear whether short-term hypothyroidism induces clinically significant cardiac dysfunction. In this study, we evaluated the changes of cardiac function and B-type natriuretic peptide (BNP) during short-term hypothyroidism. Materials and Methods: The study was an 12-week controlled observational study. Nineteen female patients with differentiated thyroid cancer were recruited. Four patients had diabetes mellitus, and one of them had hypertension. All of them visited four times during the study period: on the 1st day after withdrawal of T4 (P1), on the 1st week after withdrawal of T4 (P2), on the 4th weeks after withdrawal of T4 (P3) and on the 8th weeks after RAI therapy (P4). The previous dose of T4 was given to each patient after RAI therapy. At the visiting, vital signs were checked and proBNP and echocardiography were performed. Results: During short-term hypothyroidism (P3), TSH was 136.5±48.8 mIU/L and heart rate decreased significantly during short-term hypothyroidism. Stroke volume and ejection fraction was significantly decreased at P3, but those were recovered after T4 administration. There was no diastolic dysfunction during the study. ProBNP was decreased at P3 (p=0.021), but all the values were in normal range. There were no signs and symptoms of heart failure and cardiac ischemia. Conclusion: Although short-term hypothyroidism induced systolic dysfunction, it didn’t induce the clinical problem. The withdrawal of thyroid hormone can safely be prescribed to patients with low cardiac riskope

Sex-based prognostic implications of nonobstructive coronary artery disease: results from the international multicenter CONFIRM study.

PURPOSE: To determine the clinical outcomes of women and men with nonobstructive coronary artery disease ( CAD coronary artery disease ) with coronary computed tomographic (CT) angiography data in patients who were similar in terms of CAD coronary artery disease risk factors, angina typicality, and CAD coronary artery disease extent and distribution. MATERIALS AND METHODS: Institutional review board approval was obtained for all participating sites, with either informed consent or waiver of informed consent. In a prospective international multicenter cohort study of 27 125 patients undergoing coronary CT angiography at 12 centers, 18 158 patients with no CAD coronary artery disease or nonobstructive (<50% stenosis) CAD coronary artery disease were examined. Men and women were propensity matched for age, CAD coronary artery disease risk factors, angina typicality, and CAD coronary artery disease extent and distribution, which resulted in a final cohort of 11 462 subjects. Nonobstructive CAD coronary artery disease presence and extent were related to incident major adverse cardiovascular events ( MACE major adverse cardiovascular events ), which were inclusive of death and myocardial infarction and were estimated by using multivariable Cox proportional hazards models. RESULTS: At a mean follow-up ± standard deviation of 2.3 years ± 1.1, MACE major adverse cardiovascular events occurred in 164 patients (0.6% annual event rate). After matching, women and men experienced identical annualized rates of myocardial infarction (0.2% vs 0.2%, P = .72), death (0.5% vs 0.5%, P = .98), and MACE major adverse cardiovascular events (0.6% vs 0.6%, P = .94). In multivariable analysis, nonobstructive CAD coronary artery disease was associated with similarly increased MACE major adverse cardiovascular events for both women (hazard ratio: 1.96 [95% confidence interval { CI confidence interval }: 1.17, 3.28], P = .01) and men (hazard ratio: 1.77 [95% CI confidence interval : 1.07, 2.93], P = .03). CONCLUSION: When matched for age, CAD coronary artery disease risk factors, angina typicality, and nonobstructive CAD coronary artery disease extent, women and men experience comparable rates of incident mortality and myocardial infarction.ope

Bayesian Estimation of Geometric Morphometric Landmarks for Simultaneous Localization of Multiple Anatomies in Cardiac CT Images

We propose a robust method to simultaneously localize multiple objects in cardiac computed tomography angiography (CTA) images. The relative prior distributions of the multiple objects in the three-dimensional (3D) space can be obtained through integrating the geometric morphological relationship of each target object to some reference objects. In cardiac CTA images, the cross-sections of ascending and descending aorta can play the role of the reference objects. We employed the maximum a posteriori (MAP) estimator that utilizes anatomic prior knowledge to address this problem of localizing multiple objects. We propose a new feature for each pixel using the relative distances, which can define any objects that have unclear boundaries. Our experimental results targeting four pulmonary veins (PVs) and the left atrial appendage (LAA) in cardiac CTA images demonstrate the robustness of the proposed method. The method could also be extended to localize other multiple objects in different applications.ope

Atherogenic index of plasma and the risk of advanced subclinical coronary artery disease beyond traditional risk factors: An observational cohort study

Background: Atherogenic lipoprotein profile of plasma is an important risk factor for atherosclerosis. The atherogenic index of plasma (AIP) has been suggested as a novel marker for atherosclerosis. Hypothesis: AIP is a useful marker of advanced subclinical coronary artery disease (CAD) in subjects without overt renal dysfunction. Methods: A total of 6928 subjects with estimated glomerular filtration rate > 60 mL/minutes/1.73 m2 evaluated by coronary computed tomography angiography (CCTA) for health check-up were included. The relation of AIP to advanced CAD (heavy coronary calcification, defined as coronary artery calcium score [CACS] >100 or obstructive coronary plaque [OCP], defined as plaque with >50% stenosis) was evaluated. Results: All participants were stratified into four groups based on AIP quartiles. The prevalence of CACS >100 (group I [lowest] 4.7% vs group II 7.0% vs group III 8.8% vs group IV 10.0%) and OCP (group I 3.7% vs group II 6.4% vs group III 8.8% vs group IV 10.9%) (all P 100 (odds ratio [OR] 1.057, 95% confidence interval (CI) 1.010 to 1.106, P = .017; relative risk (RR) 1.048, 95% CI 1.009-1.089, and P = .015) and OCP (OR 1.079, 95% CI 1.033-1.127, P = .001; RR 1.069, 95% CI 1.031-1.108, P 60 years, male sex, hypertension, diabetes mellitus, dyslipidaemia, obesity, and proteinuria. Conclusion: AIP is independently associated with advanced subclinical CAD beyond traditional risk factors.ope