Volume of carotid artery ulceration as a predictor of cardiovascular events

BACKGROUND AND PURPOSE: Previous studies have shown the presence of ulceration in atherosclerotic plaque either by categorizing the plaque as complex (irregular morphology with ulcers) or smooth or by quantifying the number of ulcers observed in a specific region of interest. The aim of this study was to quantify carotid total ulcer volume by 3-dimensional ultrasound to investigate the relationship of total ulcer volume to vascular events (strokes, transient ischemic attack, myocardial infarction, revascularization, or death because of cardiovascular reasons). METHODS: In total, 349 at-risk subjects provided written informed consent to carotid 3-dimensional ultrasound and were analyzed for ulcerations. Ulcer volume was defined as a distinct discontinuity in an atherosclerotic plaque, with a volume≥1.00 mm3 as measured using manual segmentation. The sum of the volumes of all ulcers seen in both carotids was the total ulcer volume. Participants were monitored for ≤5 years for outcomes, including cardiovascular events and death. RESULTS: Kaplan-Meier survival analysis showed that subjects with total ulcer volume≥5 mm3 experienced a significantly higher risk of developing stroke, transient ischemic attack, or death (P=0.009) and of developing stroke/transient ischemic attack/death/myocardial infarction/revascularization (P=0.017). Lower ulcer volumes did not predict events nor did ulcer depth. CONCLUSIONS: Volume of carotid ulceration on 3-dimensional ultrasound predicts cardiovascular events. In addition to improving risk stratification, ulceration is a potential therapeutic target

SPARKLE (Subtypes of ischaemic stroke classification system), Incorporating measurement of carotid plaque burden: A new validated tool for the classification of ischemic stroke subtypes

Background: Previous classification systems of acute ischemic stroke (Causative Classification System, CCS, of acute ischemic stroke, Trial of Org 10172 in Acute Stroke Treatment, TOAST) established the diagnosis of large artery disease (LAD) based on the presence or absence of carotid stenosis. However, carotid plaque burden is a stronger predictor of cardiovascular risk than stenosis. Our objective was to update definitions of ischemic stroke subtypes to improve the detection of LAD and to assess the validity and reliability of a new classification system: SPARKLE (Subtypes of Ischaemic Stroke Classification System). Methods: In a retrospective review of clinical research data, we compared three stroke subtype classifications: CCS, TOAST and SPARKLE. We analyzed a random sample of 275 patients presenting with minor stroke or transient ischemic attack (TIA) in an Urgent TIA Clinic in London, Ont., Canada, between 2002 and 2012. Results: There was substantial overall agreement between SPARKLE and CCS (κ = 0.75), with significant differences in the rate of detection of LAD, cardioembolic and undetermined causes of stroke or TIA. The inter-rater reliability of SPARKLE was substantial (κ = 0.76) and the intra-rater reliability was excellent (κ = 0.91). Conclusion: SPARKLE is a valid and reliable classification system, providing advantages compared to CCS and TOAST. The incorporation of plaque burden into the classification of LAD increases the proportion of cases attributable to LAD and reduces the proportion classified as being of \u27undetermined\u27 etiology. © 2014 S. Karger AG, Basel

Progression of carotid plaque volume predicts cardiovascular events

BACKGROUND AND PURPOSE: Carotid ultrasound evaluation of intima-media thickness (IMT) and plaque burden has been used for risk stratification and for evaluation of antiatherosclerotic therapies. Increasing evidence indicates that measuring plaque burden is superior to measuring IMT for both purposes. We compared progression/regression of IMT, total plaque area (TPA), and total plaque volume (TPV) as predictors of cardiovascular outcomes. METHODS: IMT, TPA, and TPV were measured at baseline in 349 patients attending vascular prevention clinics; they had TPA of 40 to 600 mm(2) at baseline to qualify for enrollment. Participants were followed up for ≤5 years (median, 3.17 years) to ascertain vascular death, myocardial infarction, stroke, and transient ischemic attacks. Follow-up measurements 1 year later were available in 323 cases for IMT and TPA, and in 306 for TPV. RESULTS: Progression of TPV predicted stroke, death or TIA (Kaplan-Meier logrank P=0.001), stroke/death/MI (P=0.008) and Stroke/Death/TIA/Myocardial infarction (any Cardiovascular event) (P=0.001). Progression of TPA weakly predicted Stroke/Death/TIA (P=0.097) but not stroke/death/MI (P=0.59) or any CV event (P=0.143); likewise change in IMT did not predict Stroke/Death/MI (P=0.13) or any CV event (P=0.455 ). In Cox regression, TPV progression remained a significant predictor of events after adjustment for coronary risk factors (P=0.001) but change in TPA did not. IMT change predicted events in an inverse manner; regression of IMT predicted events (P=0.004). CONCLUSIONS: For assessment of response to antiatherosclerotic therapy, measurement of TPV is superior to both IMT and TPA

Predictive value for cardiovascular events of common carotid intima media thickness and its rate of change in individuals at high cardiovascular risk - Results from the PROG-IMT collaboration.

AIMS: Carotid intima media thickness (CIMT) predicts cardiovascular (CVD) events, but the predictive value of CIMT change is debated. We assessed the relation between CIMT change and events in individuals at high cardiovascular risk. METHODS AND RESULTS: From 31 cohorts with two CIMT scans (total n = 89070) on average 3.6 years apart and clinical follow-up, subcohorts were drawn: (A) individuals with at least 3 cardiovascular risk factors without previous CVD events, (B) individuals with carotid plaques without previous CVD events, and (C) individuals with previous CVD events. Cox regression models were fit to estimate the hazard ratio (HR) of the combined endpoint (myocardial infarction, stroke or vascular death) per standard deviation (SD) of CIMT change, adjusted for CVD risk factors. These HRs were pooled across studies. In groups A, B and C we observed 3483, 2845 and 1165 endpoint events, respectively. Average common CIMT was 0.79mm (SD 0.16mm), and annual common CIMT change was 0.01mm (SD 0.07mm), both in group A. The pooled HR per SD of annual common CIMT change (0.02 to 0.43mm) was 0.99 (95% confidence interval: 0.95-1.02) in group A, 0.98 (0.93-1.04) in group B, and 0.95 (0.89-1.04) in group C. The HR per SD of common CIMT (average of the first and the second CIMT scan, 0.09 to 0.75mm) was 1.15 (1.07-1.23) in group A, 1.13 (1.05-1.22) in group B, and 1.12 (1.05-1.20) in group C. CONCLUSIONS: We confirm that common CIMT is associated with future CVD events in individuals at high risk. CIMT change does not relate to future event risk in high-risk individuals

Forest plots of the HR of the combined endpoint per one SD of average mean CCA-IMT (with 95% CIs).

<p>Panel I: Group A (asymptomatic individuals with three or more CVD risk factors), HR adjusted for age, sex and annual mean CCA-IMT change (model 1). Panel II: Group A (asymptomatic individuals with three or more CVD risk factors), HR adjusted for age, sex, annual mean CCA-IMT change and other CVD risk factors (model 2). Panel III: Group B (asymptomatic individuals with carotid plaques), HR adjusted for age, sex and annual mean CCA-IMT change (model 1). Panel IV: Group B (asymptomatic individuals with carotid plaques), HR adjusted for age, sex, annual mean CCA-IMT change and other CVD risk factors (model 2). Panel V: Group C (individuals with previous CVD events), HR adjusted for age, sex and annual mean CCA-IMT change (model 1). Panel VI: Group C (individuals with previous CVD events), HR adjusted for age, sex, annual mean CCA-IMT change and other CVD risk factors (model 2).</p

Forest plots of the HR of the combined endpoint per one SD of annual mean CCA-IMT change (with 95% CIs).

<p>Panel I: Group A (asymptomatic individuals with three or more CVD risk factors), HR adjusted for age, sex and average mean CCA-IMT (model 1). Panel II: Group A (asymptomatic individuals with three or more CVD risk factors), HR adjusted for age, sex, average mean CCA-IMT and other CVD risk factors (model 2). Panel III: Group B (asymptomatic individuals with carotid plaques), HR adjusted for age, sex and average mean CCA-IMT (model 1). Panel IV: Group B (asymptomatic individuals with carotid plaques), HR adjusted for age, sex, average mean CCA-IMT and other CVD risk factors (model 2). Panel V: Group C (individuals with previous CVD events), HR adjusted for age, sex and average mean CCA-IMT (model 1). Panel VI: Group C (individuals with previous CVD events), HR adjusted for age, sex, average mean CCA-IMT and other CVD risk factors (model 2).</p

Meta-regression plot for the HR (combined endpoint) per SD of annual mean CCA-IMT change (model 1), by the correlation of baseline and follow-up common CIMT.

<p>The size of each circle represents the precision of the log HR.</p

Inclusion criteria.

<p>Inclusion criteria.</p

Cohorts and subsamples.

<p>Cohorts and subsamples.</p