Endothelial dysfunction, carotid artery plaque burden, and conventional exercise-induced myocardial ischemia as predictors of coronary artery disease prognosis

<p>Abstract</p> <p>Background</p> <p>While both flow-mediated vasodilation (FMD) in the brachial artery (BA), which measures endothelium-dependent vasodilatation, and intima-media thickness (IMT) in the carotid artery are correlated with the prognosis of coronary artery disease (CAD), it is not clear which modality is a better predictor of CAD. Furthermore, it has not been fully determined whether either of these modalities is superior to conventional ST-segment depression on exercise stress electrocardiogram (ECG) as a predictor. Thus, the goal of the present study was to compare the predictive value of FMD, IMT, and stress ECG for CAD prognosis.</p> <p>Methods and Results</p> <p>A total of 103 consecutive patients (62 ± 9 years old, 79 men) with clinically suspected CAD had FMD and nitroglycerin-induced dilation (NTG-D) in the BA, carotid artery IMT measurement using high-resolution ultrasound, and exercise treadmill testing. The 73 CAD patients and 30 normal coronary patients were followed for 50 ± 15 months. Fifteen patients had coronary events during this period (1 cardiac death, 2 non-fatal myocardial infarctions, 3 acute heart failures, and 9 unstable anginas). On Kaplan-Meier analysis, only FMD and stress ECG were significant predictors for cardiac events.</p> <p>Conclusion</p> <p>Brachial endothelial function as reflected by FMD and conventional exercise stress testing has comparable prognostic value, whereas carotid artery plaque burden appears to be less powerful for predicting future cardiac events.</p

Association of iron overload based quantitative T2* MRI technique and carotid intima-media thickness in patients with beta-thalassemia: A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Body iron status has been implicated in atherosclerotic cardiovascular disease. The main hypothesis is that high iron status is associated with increased risk of atherosclerosis. We investigated the potential role of iron as an additional risk factor promoting atherosclerosis among beta-thalassemic patients.</p> <p>Methods</p> <p>In this cross-sectional study, the liver iron load was assessed by quantitative T2* MRI technique and intima-media thickness (IMT) of the common carotid artery by high-resolution ultrasound among 119 patients (62 male, 57 female) with beta-thalassemia (major and intermediate) whose age ranged from 10 to 50 years with a mean of 25.6 years. The patients were divided into three groups according to the severity of iron loading, obtained by T2*MRI technique: group I (normal), group II (mild) and group III (moderate and severe) iron load.</p> <p>For elimination of the effect of age on carotid IMT values, the patients also were divided into four age groups (10-19 y, 20-29 y, 30-39 y and 40-50 y). Mean carotid IMT based on the severity of iron loading were compared at different age groups, using one way ANOVA analysis for assessing the effect of iron loading on carotid IMT. Pearson's coefficient of correlation were used to assess the degree of correlation between studied variables (liver T2*, IMT, age).</p> <p>Results</p> <p>There were significant differences in mean carotid IMT based on the severity of iron loading at different age groups, with P = 0.003 at 20-29 y, P = 0.006 at 30-39 y and p = 0.037 at 40-50 y. Age (p = 0.001) and liver T2*(p = 0.003) had significant correlation with mean carotid IMT independently.</p> <p>At the age group of 10-19 years, there were not significant differences in mean carotid IMT based on the liver iron loading (p = 0.661).</p> <p>No significant differences also are seen in mean carotid IMT between male and female (p = 0.41).</p> <p>Conclusions</p> <p>This study identified a relationship between body iron status and carotid IMT. This relationship support to the hypothesis of a link between body iron load and atherosclerosis.</p

Standardized ultrasound evaluation of carotid stenosis for clinical trials: University of Washington Ultrasound Reading Center

<p>Abstract</p> <p>Introduction</p> <p>Serial monitoring of patients participating in clinical trials of carotid artery therapy requires noninvasive precision methods that are inexpensive, safe and widely available. Noninvasive ultrasonic duplex Doppler velocimetry provides a precision method that can be used for recruitment qualification, pre-treatment classification and post treatment surveillance for remodeling and restenosis. The University of Washington Ultrasound Reading Center (UWURC) provides a uniform examination protocol and interpretation of duplex Doppler velocity measurements.</p> <p>Methods</p> <p>Doppler waveforms from 6 locations along the common carotid and internal carotid artery path to the brain plus the external carotid and vertebral arteries on each side using a Doppler examination angle of 60 degrees are evaluated. The UWURC verifies all measurements against the images and waveforms for the database, which includes pre-procedure, post-procedure and annual follow-up examinations. Doppler angle alignment errors greater than 3 degrees and Doppler velocity measurement errors greater than 0.05 m/s are corrected.</p> <p>Results</p> <p>Angle adjusted Doppler velocity measurements produce higher values when higher Doppler examination angles are used. The definition of peak systolic velocity varies between examiners when spectral broadening due to turbulence is present. Examples of measurements are shown.</p> <p>Discussion</p> <p>Although ultrasonic duplex Doppler methods are widely used in carotid artery diagnosis, there is disagreement about how the examinations should be performed and how the results should be validated. In clinical trails, a centralized reading center can unify the methods. Because the goals of research examinations are different from those of clinical examinations, screening and diagnostic clinical examinations may require fewer velocity measurements.</p

Automatic identification of variables in epidemiological datasets using logic regression

textabstractBackground: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies