By Scott M. Grundy (auth.), Scott M. Grundy (eds.)
In this up to date 5th variation of the Atlas of Atherosclerosis and Metabolic Syndrome (formerly the Atlas of Atherosclerosis), the editors have compiled a complete replace at the box of atherosclerosis. This four-color atlas comprises distinctive legends and large reference listings for countless numbers of illustrations, algorithms, schematics, and pictures. This re-creation focuses extra heavily on metabolic syndrome, in addition to comprehensively protecting many different themes together with diabetes and vascular chance, weight problems administration, nutritional matters, drug therapy, gender and ethnicity adjustments, etc. The remarkable, four-color layout mixed with the breadth of knowledge it comprises make this e-book a useful source for physicians, cardiologists, and all execs fascinated by the learn and therapy of atherosclerosis.
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This once again demonstrates that the metabolic syndrome is shown to be no better than the measurement of glucose alone for the prediction of diabetes and that the waist circumference cut-points suggested for ethnic South Asians in the IDF and ATP III definitions of the metabolic syndrome are inappropriate (ie, too high) for this population. The recommendation from this analysis was that evidence-based waist circumference cut-points for different ethnic groups should be developed. EGIR—European Group for the Study of Insulin Resistance; MetS—metabolic syndrome.
Relationship between obesity, insulin resistance, and coronary heart disease risk. J Am Coll Cardiol 2002, 40:937–943. 5. : Relationship between degree of obesity and in vivo insulin action in man. Am J Physiol 1985, 248 (3 Pt 1):E286–E291. 6. Alberti KG, Zimmet PZ: Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998, 15:539–553. 7. Einhorn D: ACE position statement on insulin resistance syndrome.
Is the metabolic syndrome a valid tool for predicting cardiovascular disease (CVD) and diabetes? To answer this question, the first step is to recognize that clinical definitions of the metabolic syndrome were not formulated for absolute or global risk prediction, for either diabetes or CVD. To do this, it would be necessary to incorporate all known risk factors, including age, sex, total cholesterol, tobacco use, family history, and physical activity and inactivity. Examples of absolute or global risk calculators include algorithms for short-term 40 Atlas of Atherosclerosis and Metabolic Syndrome (10–15-y) risk of CVD based on the Framingham study and diabetes risk algorithms (eg, Stern et al.