Statin therapy and levels of hemostatic factors in a healthy population: the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: HMG-CoA reductase inhibitors (statins) reduce the risk of venous thromboembolism (VTE) in healthy people. Statins reduce levels of inflammation biomarkers; however, the mechanism for the reduction in VTE risk is unknown. AIM: In a large cohort of healthy people, we studied associations of statin use with plasma hemostatic factors related to VTE risk. METHODS: Cross-sectional analyses were performed in the Multi-Ethnic Study of Atherosclerosis (MESA), a cohort study of 6814 healthy men and women aged 45-84 years, free of clinical cardiovascular disease at baseline; 1001 were using statins at baseline. Twenty-three warfarin users were excluded. Age, race and sex-adjusted mean hemostatic factor levels were compared between statin users and non-users, and multivariable linear regression models were used to assess associations of statin use with hemostatic factors, adjusted for age, race/ethnicity, education, income, aspirin use, hormone replacement therapy (in women), and major cardiovascular risk factors. RESULTS: Participants using statins had lower adjusted levels of D-dimer (- 9%), C-reactive protein (- 21%) and factor VIII (- 3%) than non-users (P < 0.05). Homocysteine and von Willebrand factor levels were non-significantly lower with statin use. Higher fibrinogen (2%) and plasminogen activator inhibitor-1 (22%) levels were observed among statin users than among non-users (P < 0.05). Further adjustment for LDL and triglyceride levels did not attenuate the observed differences in these factors with statin use. CONCLUSIONS: Findings of lower D-dimer, FVIII and C-reactive protein levels with statin use suggest hypotheses for mechanisms whereby statins might lower VTE risk. A prospective study or clinical trial linking these biochemical differences to VTE outcomes in statin users and non-users is warranted.

Prediction and classification of cardiovascular disease risk in older adults with diabetes.

AIMS/HYPOTHESIS: We sought to derive and validate a cardiovascular disease (CVD) prediction algorithm for older adults with diabetes, and evaluate the incremental benefit of adding novel circulating biomarkers and measures of subclinical atherosclerosis. METHODS: As part of the Cardiovascular Health Study (CHS), a population-based cohort of adults aged ≥65 years, we examined the 10 year risk of myocardial infarction, stroke and cardiovascular death in 782 older adults with diabetes, in whom 265 events occurred. We validated predictive models in 843 adults with diabetes, who were followed for 7 years in a second cohort, the Multi-Ethnic Study of Atherosclerosis (MESA); here 71 events occurred. RESULTS: The best fitting standard model included age, smoking, systolic blood pressure, total and HDL-cholesterol, creatinine and the use of glucose-lowering agents; however, this model had a C statistic of 0.64 and poorly classified risk in men. Novel biomarkers did not improve discrimination or classification. The addition of ankle-brachial index, electrocardiographic left ventricular hypertrophy and internal carotid intima-media thickness modestly improved discrimination (C statistic 0.68; p = 0.002) and classification (net reclassification improvement [NRI] 0.12; p = 0.01), mainly in those remaining free of CVD. Results were qualitatively similar in the MESA, with a change in C statistic from 0.65 to 0.68 and an NRI of 0.09 upon inclusion of subclinical disease measures. CONCLUSIONS/INTERPRETATION: Standard clinical risk factors and novel biomarkers poorly discriminate and classify CVD risk in older adults with diabetes. The inclusion of subclinical atherosclerotic measures modestly improves these features, but to develop more robust risk prediction, a better understanding of the pathophysiology and determinants of CVD in this patient group is needed.

Differentiation of myocardial scar from potential pitfalls and artefacts in delayed enhancement MRI.

Delayed enhancement cardiac magnetic resonance (DE-CMR) imaging is used increasingly to identify and quantify focal myocardial scar. Our objective is to describe factors used in the interpretation of DE-CMR images and to highlight potential pitfalls and artefacts that mimic myocardial scar. Inversion recovery gradient recalled echo sequence is commonly accepted as the standard of reference for DE-CMR. There are also alternative sequences that can be performed in a single breath-hold or with free breathing. Radiologists need to be aware of factors affecting image quality, and potential pitfalls and artefacts that may generate focal hyperintense areas that mimic myocardial scar.