17 research outputs found
ACCF/ACR/SCCT/SCMR/ASNC/NASCI/SCAI/SIR 2006 Appropriateness Criteria for Cardiac Computed Tomography and Cardiac Magnetic Resonance Imaging⁎⁎Developed in accordance with the principles and methodology outlined by ACCF: Patel MR, Spertus JA, Brindis RG, Hendel RC, Douglas PS, Peterson ED, Wolk MJ, Allen JM, Raskin IE. ACCF proposed method for evaluating the appropriateness of cardiovascular imaging. J Am Coll Cardiol 2005;46:1606–13. A Report of the American College of Cardiology Foundation Quality Strategic Directions Committee Appropriateness Criteria Working Group, American College of Radiology, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, American Society of Nuclear Cardiology, North American Society for Cardiac Imaging, Society for Cardiovascular Angiography and Interventions, and Society of Interventional Radiology
Scout View X-Ray Attenuation Versus Weight-Based Selection of Reduced Peak Tube Voltage in Cardiac CT Angiography
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Noninvasive Cardiovascular Risk Assessment of the Asymptomatic Diabetic Patient: The Imaging Council of the American College of Cardiology.
Increased cardiovascular morbidity and mortality in patients with type 2 diabetes is well established; diabetes is associated with at least a 2-fold increased risk of coronary heart disease. Approximately two-thirds of deaths among persons with diabetes are related to cardiovascular disease. Previously, diabetes was regarded as a "coronary risk equivalent," implying a high 10-year cardiovascular risk for every diabetes patient. Following the original study by Haffner et al., multiple studies from different cohorts provided varying conclusions on the validity of the concept of coronary risk equivalency in patients with diabetes. New guidelines have started to acknowledge the heterogeneity in risk and include different treatment recommendations for diabetic patients without other risk factors who are considered to be at lower risk. Furthermore, guidelines have suggested that further risk stratification in patients with diabetes is warranted before universal treatment. The Imaging Council of the American College of Cardiology systematically reviewed all modalities commonly used for risk stratification in persons with diabetes mellitus and summarized the data and recommendations. This document reviews the evidence regarding the use of noninvasive testing to stratify asymptomatic patients with diabetes with regard to coronary heart disease risk and develops an algorithm for screening based on available data
Recommended from our members
Noninvasive Cardiovascular Risk Assessment of the Asymptomatic Diabetic Patient: The Imaging Council of the American College of Cardiology.
Increased cardiovascular morbidity and mortality in patients with type 2 diabetes is well established; diabetes is associated with at least a 2-fold increased risk of coronary heart disease. Approximately two-thirds of deaths among persons with diabetes are related to cardiovascular disease. Previously, diabetes was regarded as a "coronary risk equivalent," implying a high 10-year cardiovascular risk for every diabetes patient. Following the original study by Haffner et al., multiple studies from different cohorts provided varying conclusions on the validity of the concept of coronary risk equivalency in patients with diabetes. New guidelines have started to acknowledge the heterogeneity in risk and include different treatment recommendations for diabetic patients without other risk factors who are considered to be at lower risk. Furthermore, guidelines have suggested that further risk stratification in patients with diabetes is warranted before universal treatment. The Imaging Council of the American College of Cardiology systematically reviewed all modalities commonly used for risk stratification in persons with diabetes mellitus and summarized the data and recommendations. This document reviews the evidence regarding the use of noninvasive testing to stratify asymptomatic patients with diabetes with regard to coronary heart disease risk and develops an algorithm for screening based on available data