Aortic Root Calcification: A Possible Imaging Biomarker of Coronary Atherosclerosis

Clinical impact of cardiovascular calcifications on stroke incidence in primary prevention: analysis in NADESICO study

The utility of assessment of cardiovascular calcifications for predicting stroke incidence remains unclear. This study assessed the relationship between cardiovascular calcifications including coronary artery calcification (CAC), aortic valve (AVC), and aortic root (ARC) assessed by coronary computed tomography (CT) and stroke incidence in patients with suspected CAD. In this multicenter prospective cohort study, 1187 patients suspected of CAD who underwent coronary CT were enrolled. Cardiovascular events including stroke were documented. Hazard ratio (HR) and confidence interval (CI) were assessed by Cox proportional hazard model adjusted for the Framingham risk score. C statistics for stroke incidence were also examined by models including cardiovascular calcifications. A total of 980 patients (mean age, 65 ± 7 years; females, 45.8%) were assessed by the CAC, AVC, and ARC Agatston scores. During a median follow-up of 4.0 years, 19 patients developed stroke. Cox proportional hazard model showed severe CAC (Agatston score ≥ 90th percentile [580.0 value]) and presence of AVC and ARC were associated with stroke incidence (HR; 10.33 [95% CI; 2.08-51.26], 3.08 [1.19-7.98], and 2.75 [1.03-7.30], respectively). C statistic in the model with CAC and AVC severity for predicting stroke incidence was 0.841 (95% CI; 0.761-0.920), which was superior to the model with CAC alone (0.762 [95% CI; 0.665-0.859], P < 0.01). CAC, AVC, and ARC were associated with stroke incidence in patients suspected of CAD. Assessment of both CAC and AVC may be useful for prediction of stroke incidence.

Efficacy of Diagnostic Testing of Suspected Coronary Artery Disease: A Contemporary Review

BACKGROUND

Coronary artery disease (CAD) is a highly prevalent condition which can lead to myocardial ischemia as well as acute coronary syndrome. Early diagnosis of CAD can improve patient outcomes through guiding risk factor modification and treatment modalities.

SUMMARY

Testing for CAD comes with increased cost and risk; therefore, physicians must determine which patients require testing, and what testing modality will offer the most useful data to diagnose patients with CAD. Patients should have an initial risk stratification for pretest probability of CAD based on symptoms and available clinical data. Patients with a pretest probability less than 5% should receive no further testing, while patients with a high pretest probability should be considered for direct invasive coronary angiography. In patients with a pretest probability between 5 and 15%, coronary artery calcium score and or exercise electrocardiogram can be obtained to further risk stratify patients to low-risk versus intermediate-high-risk. Intermediate-high-risk patients should be tested with coronary computed tomography angiography (preferred) versus positron emission tomography or single photon emission computed tomography based on their individual patient characteristics and institutional availability.

KEY MESSAGES

This comprehensive review aimed to describe the available CAD testing modalities, detail their risks and benefits, and propose when each should be considered in the evaluation of a patient with suspected CAD.

Effects of nutritional status on serum fetuin-A level

Fetuin-A is a glycoprotein structured molecule which is mostly released by the liver. As a multifunctional protein, fetuin-A has positive effects on health such as calcification, cardiovascular diseases and tumor development processes with various mechanisms, whereas it plays a negative role in the processes of obesity, diabetes and fatty liver disease. There are a large number of studies reporting that serum fetuin-A levels are affected by several dietary factors. It is reported in some of these studies that several nutrients increase fetuin-A release, while some others have adverse effects. It is put forward that some nutrients such as dairy products, curcumin, niacin, palmitate, coffee and alcohol consumption decrease fetuin-A level, and dietary omega-3 fatty acids intake may increase fetuin-A concentration. In addition, it is indicated that high blood glucose levels increase hepatic fetuin-A release by activating extracellular signal-regulated kinase 1/2 enzymes and increased plasma free fatty acids do the same effect by increasing NF-_KB activity. Despite these studies in the literature, there is not any review evaluating fetuin-A, chronic diseases and nutrition together. Therefore, in this study, the relationship between serum fetuin levels and some diseases and the effects of nutrients on fetuin A levels were investigated with possible mechanisms.