Dataset Information

Carotid atherosclerosis does not predict coronary, vertebral, or aortic atherosclerosis in patients with acute stroke symptoms.

ABSTRACT: The purpose of this study was to determine whether significant atherosclerotic disease in the carotid arteries predicts significant atherosclerotic disease in the coronary arteries, vertebral arteries, or aorta in patients with symptoms of acute ischemic stroke.Atherosclerotic disease was imaged using CT angiography in a prospective study of 120 consecutive patients undergoing emergent CT evaluation for symptoms of stroke. Using a comprehensive CT angiography protocol that captured the carotid arteries, coronary arteries, vertebral arteries, and aorta, we evaluated these arteries for the presence and severity of atherosclerotic disease. Significant atherosclerotic disease was defined as >50% stenosis in the carotid, coronary, and vertebral arteries, or >or=4 mm thickness and encroaching in the aorta. Presence of any and significant atherosclerotic disease was compared in the different types of arteries assessed.Of these 120 patients, 79 had CT angiography examinations of adequate image quality and were evaluated in this study. Of these 79 patients, 33 had significant atherosclerotic disease. In 26 of these 33 patients (79%), significant disease was isolated to 1 type of artery, most often to the coronary arteries (N=14; 54%). Nonsignificant atherosclerotic disease was more systemic and involved multiple arteries.Significant atherosclerotic disease in the carotid arteries does not predict significant atherosclerotic disease in the coronary arteries, vertebral arteries, or aorta in patients with symptoms of acute ischemic stroke. Significant atherosclerotic disease is most often isolated to 1 type of artery in these patients, whereas nonsignificant atherosclerotic disease tends to be more systemic.

SUBMITTER: Adraktas DD

PROVIDER: S-EPMC2941092 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Carotid atherosclerosis does not predict coronary, vertebral, or aortic atherosclerosis in patients with acute stroke symptoms.

Adraktas Dionesia D DD Brasic Natasha N Furtado Andre D AD Cheng Su-Chun SC Ordovas Karen K Chun Kimberly K Chien Jeffrey D JD Schaeffer Sarah S Wintermark Max M

Stroke 20100701 8

<h4>Background and purpose</h4>The purpose of this study was to determine whether significant atherosclerotic disease in the carotid arteries predicts significant atherosclerotic disease in the coronary arteries, vertebral arteries, or aorta in patients with symptoms of acute ischemic stroke.<h4>Methods</h4>Atherosclerotic disease was imaged using CT angiography in a prospective study of 120 consecutive patients undergoing emergent CT evaluation for symptoms of stroke. Using a comprehensive CT a ...[more]

PMID: 20595672

Similar Datasets

Project description:Identifying the likelihood of a patient having coronary artery disease (CAD) at the time of emergency department (ED) presentation with chest pain could reduce the need for stress testing or coronary imaging after myocardial infarction (MI) has been excluded. The authors aimed to determine if a novel cardiac biomarker consisting of plasma cholesteryl ester (CE) levels typically derived from the activity of the enzyme acyl-CoA:cholesterol acyltransferase (ACAT2) are predictive of CAD in a clinical model.A single-center prospective cohort design enrolled participants with symptoms of acute coronary syndrome (ACS) undergoing coronary computed tomography angiography (CCTA) or invasive angiography. Plasma samples were analyzed for CE composition with mass spectrometry. The primary endpoint was any CAD determined at angiography. Multivariable logistic regression analyses were used to estimate the relationship between the sum of the plasma concentrations from cholesteryl palmitoleate (16:1) and cholesteryl oleate (18:1) (defined as ACAT2-CE) and the presence of CAD. The added value of ACAT2-CE to the model was analyzed comparing the C-statistics and integrated discrimination improvement (IDI).The study cohort was composed of 113 participants with a mean (± standard deviation [SD]) age of 49 (±11.7) years, 59% had CAD at angiography, and 23% had an MI within 30 days. The median (interquartile range [IQR]) plasma concentration of ACAT2-CE was 938 ?mol/L (IQR = 758 to 1,099 ?mol/L) in patients with CAD and 824 ?mol/L (IQR?= 683 to 998 ?mol/L) in patients without CAD (p = 0.03). When considered with age, sex, and the number of conventional CAD risk factors, ACAT2-CE levels were associated with a 6.5% increased odds of having CAD per 10 ?mol/L increase in concentration. The addition of ACAT2-CE significantly improved the C-statistic (0.89 vs. 0.95, p = 0.0035) and IDI (0.15, p < 0.001) compared to the reduced model. In the subgroup of low-risk observation unit patients, the CE model had superior discrimination compared to the Diamond-Forrester classification (IDI = 0.403, p < 0.001).Plasma levels of ACAT2-CE have strong potential to predict a patient's likelihood of having CAD when considered in a clinical model but not when used alone. In turn, a clinical model containing ACAT2-CE could reduce the need for cardiac imaging after the exclusion of MI.

Project description:BACKGOUND:The inability to detect premature atherosclerosis significantly hinders implementation of personalized therapy to prevent coronary heart disease. A comprehensive understanding of arterial protein networks and how they change in early atherosclerosis could identify new biomarkers for disease detection and improved therapeutic targets. METHODS:Here we describe the human arterial proteome and proteomic features strongly associated with early atherosclerosis based on mass spectrometry analysis of coronary artery and aortic specimens from 100 autopsied young adults (200 arterial specimens). Convex analysis of mixtures, differential dependent network modeling, and bioinformatic analyses defined the composition, network rewiring, and likely regulatory features of the protein networks associated with early atherosclerosis and how they vary across 2 anatomic distributions. RESULTS:The data document significant differences in mitochondrial protein abundance between coronary and aortic samples (coronary>>aortic), and between atherosclerotic and normal tissues (atherosclerotic<<normal), and major alterations in tumor necrosis factor, insulin receptor, peroxisome proliferator-activated receptor-?, and peroxisome proliferator-activated receptor-? protein networks, as well, in the setting of early disease. In addition, a subset of tissue protein biomarkers indicative of early atherosclerosis was shown to predict anatomically defined coronary atherosclerosis when measured in plasma samples in a separate clinical cohort (area under the curve=0.92 [0.83-0.96]), thereby validating the use of human tissue proteomics to discover relevant plasma biomarkers for clinical applications. In addition to the specific proteins and pathways identified here, the publicly available data resource and the analysis pipeline used illustrate a strategy for interrogating and interpreting the proteomic architecture of tissues that may be relevant for other chronic diseases characterized by multicellular tissue phenotypes. CONCLUSIONS:The human arterial proteome can be viewed as a complex network whose architectural features vary considerably as a function of anatomic location and the presence or absence of atherosclerosis. The data suggest important reductions in mitochondrial protein abundance in early atherosclerosis and also identify a subset of plasma proteins that are highly predictive of angiographically defined coronary disease.

Project description:BackgroundSoluble Tumor Necrosis Factor Weak Inducer of Apoptosis (sTWEAK) has been proposed as a novel biomarker of cardiovascular disease risk. This study compares levels of sTWEAK, sCD163 and the sCD163/sTWEAK ratio in HIV-infected and uninfected patients and their associations with cardiovascular and inflammatory factors.MethodsThe data for our analysis come from 274 HIV-infected adults and 59 controls. HIV participants were on stable antiretroviral therapy (ART). Wilcoxon-Mann-Whitney tests were used for comparing markers between HIV-infected participants with HIV viral load <50 copies/mL (aviremic group), HIV-infected participants with detectable viremia (HIV-1 RNA ≥50 copies/mL; viremic group) and HIV negative participants. Multivariable quantile regression analyses were used to assess associations of sTWEAK and sCD163 with other markers of inflammation and carotid intima-media thickness (cIMT).ResultsOverall, 74% of participants were male; 59% were African-Americans; median age was 40 years and CD4 595 cells/mm3. Overall, HIV-infected participants had reduced sTWEAK and increased sCD163 levels compared to HIV-uninfected participants (p = 0.0001 for both markers). In addition, these biomarkers were significantly different between HIV-infected viremic and aviremic patients (p ≤ 0.01 for both markers). In multivariable models, sTWEAK and sCD163 in aviremic patients were significantly correlated with common carotid artery IMT (p ≤ 0.05). In HIV-infected aviremic participants, sTWEAK and sCD163 were both associated with IL-6, CD14 + CD16 + monocytes (p ≤ 0.02); additionally, sCD163 was associated with D-dimer- (β = -69.5, 0.05), VCAM (β = 72.4, p = 0.05), TNF RI (β = 91.1, p < 0.01), and TNF RII (β = 87.8, p < 0.01).ConclusionsHIV-infected participants showed increased systemic inflammatory and monocyte activation markers. Soluble CD163 and sTWEAK levels were associated with carotid intima-media thickness.

Project description:ObjectivesPrediabetes is a major epidemic and is associated with adverse cardio-cerebrovascular outcomes. Early identification of patients who will develop rapid progression of atherosclerosis could be beneficial for improved risk stratification. In this paper, we investigate important factors impacting the prediction, using several machine learning methods, of rapid progression of carotid intima-media thickness in impaired glucose tolerance (IGT) participants.MethodsIn the Actos Now for Prevention of Diabetes (ACT NOW) study, 382 participants with IGT underwent carotid intima-media thickness (CIMT) ultrasound evaluation at baseline and at 15-18 months, and were divided into rapid progressors (RP, n = 39, 58 ± 17.5 μM change) and non-rapid progressors (NRP, n = 343, 5.8 ± 20 μM change, p < 0.001 versus RP). To deal with complex multi-modal data consisting of demographic, clinical, and laboratory variables, we propose a general data-driven framework to investigate the ACT NOW dataset. In particular, we first employed a Fisher Score-based feature selection method to identify the most effective variables and then proposed a probabilistic Bayes-based learning method for the prediction. Comparison of the methods and factors was conducted using area under the receiver operating characteristic curve (AUC) analyses and Brier score.ResultsThe experimental results show that the proposed learning methods performed well in identifying or predicting RP. Among the methods, the performance of Naïve Bayes was the best (AUC 0.797, Brier score 0.085) compared to multilayer perceptron (0.729, 0.086) and random forest (0.642, 0.10). The results also show that feature selection has a significant positive impact on the data prediction performance.ConclusionsBy dealing with multi-modal data, the proposed learning methods show effectiveness in predicting prediabetics at risk for rapid atherosclerosis progression. The proposed framework demonstrated utility in outcome prediction in a typical multidimensional clinical dataset with a relatively small number of subjects, extending the potential utility of machine learning approaches beyond extremely large-scale datasets.

Project description:Rationale: Epicardial adipose tissue (EAT) has been independently associated with non-calcified, high-risk coronary plaques in low-to intermediate risk subjects. Recently, a bidirectional communication was shown between EAT and diseased coronary arteries. In high-risk patients it is unknown whether quantitative measures of EAT can capture, and which molecular players are involved in this mutual interplay. Objective: In a high-risk population, we aimed to determine how the volume of EAT is linked to coronary artery disease (CAD) and to identify potential EAT-deregulated pathways in CAD patients specifically related to coronary artery calcification (CAC). Methods and Results: In a prospective cohort of 574 degenerative severe aortic stenosis patients referred to cardiac surgery, we quantified fat depots by computed tomography (CT) and performed a comparative quantitative proteomics of thoracic fat, including EAT, mediastinal (MAT) and subcutaneous (SAT) adipose tissues. We did not find an independent association of EAT volume with the severity, distribution and complexity of coronary stenosis in invasive coronary angiography. Although, EAT volume was correlated with high CAC, its cardiovascular risk factors-adjusted association was not significant. Taking as reference non-CAD matched-patients and compared to MAT and SAT, EAT proteomic signature of CAD was characterized by up-regulation of pro-calcifying annexins (Annexin A2, ANXA2), fatty acid binding transporters (FABP4) and inflammatory signaling proteins, and by down-regulation of fetuin-A and redox state regulatory enzymes. In EAT, ANXA2 regulation was positively correlated with CAC. EAT gene expression studies confirmed overexpression of ANXA2 and FABP4 in CAD, but no expression of FETUA was detected. Compared with non-CAD, fetuin-A circulating levels were higher in CAD, whereas no fetuin-A pericardial fluid differences were found. Conclusions: In this high-risk cohort, EAT presented an imbalance of pro-calcifying, pro-inflammatory and lipid transporters mediators. These local EAT-mediated regulatory mechanisms were not reflected by the CT volume of EAT alone.

Dataset Information

Carotid atherosclerosis does not predict coronary, vertebral, or aortic atherosclerosis in patients with acute stroke symptoms.

Publications

Carotid atherosclerosis does not predict coronary, vertebral, or aortic atherosclerosis in patients with acute stroke symptoms.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure