Glucose intolerance, insulin resistance and metabolic syndrome in patients with stable angina pectoris. Obesity predicts coronary atherosclerosis and dysglycemia. 2008

Aleksander Włodarczyk, and Krzysztof Strojek
Department of Cardiology, Provincial Specjalist Hospital No 4, Bytom, Poland. xolo28@poczta.onet.pl

BACKGROUND Disturbances of glucose regulation and other metabolic disorders, as part of metabolic syndrome, are important risk factors for atherosclerosis. Abnormal glucose metabolism is commonly observed in patients with acute coronary syndrome. However, there is no consistent evidence for subjects with stable angina. OBJECTIVE To investigate the prevalence of glucose metabolism in patients with stable coronary artery disease (CAD) documented angiographically and to assess correlations of metabolic profile and extent of atherosclerotic lesions. METHODS 100 consecutive non-diabetic patients with stable CAD referred to coronary angiography were studied. Total cholesterol and its fractions, triglycerides, uric acid and fasting insulin levels were determined. Oral glucose tolerance test (OGTT) and then coronary angiography were performed. All patients were divided into groups according to glucometabolic and coronary status and insulin resistance. The sum of all lesions in coronary vessels was calculated for each patient (CAD score). RESULTS After OGTT, 44% of patients presented disturbed glucose metabolism: 9% of patients had newly diagnosed diabetes and 35% patients were in the prediabetic state. There was no correlation between glycemic status and insulin resistance, and severity of coronary heart disease. Obesity, reflected by body mass index, waist circumference and waist-to-hip ratio, was a major metabolic disorder and independent predictor of the extent of coronary atherosclerosis and glucose intolerance. CONCLUSIONS Abnormal glucose regulation is very common in patients with stable CAD. Only obesity was the independent predictor of coronary atherosclerosis and dysglycemia. Other metabolic risk factors are target for prevention and treatment.

UI MeSH Term Description Entries
D007328 Insulin A 51-amino acid pancreatic hormone that plays a major role in the regulation of glucose metabolism, directly by suppressing endogenous glucose production (GLYCOGENOLYSIS; GLUCONEOGENESIS) and indirectly by suppressing GLUCAGON secretion and LIPOLYSIS. Native insulin is a globular protein comprised of a zinc-coordinated hexamer. Each insulin monomer containing two chains, A (21 residues) and B (30 residues), linked by two disulfide bonds. Insulin is used as a drug to control insulin-dependent diabetes mellitus (DIABETES MELLITUS, TYPE 1). Iletin,Insulin A Chain,Insulin B Chain,Insulin, Regular,Novolin,Sodium Insulin,Soluble Insulin,Chain, Insulin B,Insulin, Sodium,Insulin, Soluble,Regular Insulin
D007333 Insulin Resistance Diminished effectiveness of INSULIN in lowering blood sugar levels: requiring the use of 200 units or more of insulin per day to prevent HYPERGLYCEMIA or KETOSIS. Insulin Sensitivity,Resistance, Insulin,Sensitivity, Insulin
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009765 Obesity A status with BODY WEIGHT that is grossly above the recommended standards, usually due to accumulation of excess FATS in the body. The standards may vary with age, sex, genetic or cultural background. In the BODY MASS INDEX, a BMI greater than 30.0 kg/m2 is considered obese, and a BMI greater than 40.0 kg/m2 is considered morbidly obese (MORBID OBESITY).
D011044 Poland A country in central Europe, east of Germany. The capital is Warsaw. Polish People's Republic,Republic of Poland
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D001786 Blood Glucose Glucose in blood. Blood Sugar,Glucose, Blood,Sugar, Blood
D003324 Coronary Artery Disease Pathological processes of CORONARY ARTERIES that may derive from a congenital abnormality, atherosclerotic, or non-atherosclerotic cause. Arteriosclerosis, Coronary,Atherosclerosis, Coronary,Coronary Arteriosclerosis,Coronary Atherosclerosis,Left Main Coronary Artery Disease,Left Main Coronary Disease,Left Main Disease,Arterioscleroses, Coronary,Artery Disease, Coronary,Artery Diseases, Coronary,Atheroscleroses, Coronary,Coronary Arterioscleroses,Coronary Artery Diseases,Coronary Atheroscleroses,Left Main Diseases
D005260 Female Females

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