An insulin resistance syndrome (IRS) score was developed based on clinical risk factors in adults with childhood-onset type 1 diabetes in the Epidemiology of Diabetes Complications (EDC) Study and was validated using euglycemic-hyperinsulinemic clamp studies. Hypertension, waist-to-hip ratio (WHR), triglyceride and HDL cholesterol levels, family history of type 2 diabetes, and glycemic control were risk factors used to define the score. A score of 1 (lowest likelihood IRS) to 3 (highest likelihood IRS) was assigned for each risk f a c t o r. Eligible subjects (n = 24) were recruited from the EDC cohort based on tertile of IRS score. Subjects received an overnight insulin infusion to normalize glucose levels, then underwent a 3-h euglycemic-hyperinsulinemic (60 mU · m -2 · min -1 ) clamp. Glucose disposal rate (GDR) was determined during the last 30 min of the clamp. The GDR differed significantly by IRS group (9.65 ± 2.99, 8.02 ± 1.39, and 5.68 ± 2.16 m g · k g -1 · m i n -1 , P < 0.01). The GDR was inversely correlated with the IRS score (r = -0.64, P < 0.01). Using linear regression, the combination of risk factors that yielded the highest adjusted r 2 value (0.57, P < 0.001) were WHR, hypertension, and HbA 1 . This study found that clinical risk factors can be used to identify subjects with type 1 diabetes who are insulin resistant, and it provides validation of a score based on clinical factors to determine the extent of insulin resistance in type 1 diabetes. This score will be applied to the entire EDC population in future studies to determine the effect of insulin resistance on complications. D i a b e t e s 4 9 :6 2 6-632, 2000

OBJECTIVE -To determine the independent risk factors for coronary artery disease (CAD) in type 1 diabetes by type of CAD at first presentation. RESEARCH DESIGN AND METHODS-This is a historical prospective cohort study of 603 patients with type 1 diabetes diagnosed before 18 years of age between 1950 and 1980. The mean age and duration of diabetes at baseline were 28 (range 8 -47) and 19 years (7-37), respectively, and patients were followed for 10 years. Patients with prevalent CAD were excluded from the study. Electrocardiogram (ECG) ischemia was defined by Minnesota Code (MC) 1.3, 4.1-3, 5.1-3, or 7.1; angina was determined by Pittsburgh Epidemiology of Diabetes Complications (EDC) study physician diagnosis; and hard CAD was determined by angiographic stenosis Ն50%, revascularization procedure, Q waves (MC 1.1-1.2), nonfatal myocardial infarction (MI), or CAD death.RESULTS -A total of 108 incident CAD events occurred during the 10-year follow-up: 17 cases of ECG ischemia, 49 cases of angina, and 42 cases of hard CAD (5 CAD deaths, 25 nonfatal MI or major Q waves, and 12 revascularization or Ն50% stenosis). Blood pressure, lipid levels, inflammatory markers, renal disease, and peripheral vascular disease showed a positive gradient across the groups of no CAD, angina, and hard CAD (P Ͻ 0.01, trend analysis, all variables), although estimated glucose disposal rate (eGDR) and physical activity showed inverse associations (P Ͻ 0.01, trend analysis, both variables). In addition, depressive symptomatology predicted angina (P ϭ 0.016), whereas HbA 1 showed no association with subsequent CAD.CONCLUSIONS -These data suggest that although the standard CAD risk factors are still operative in type 1 diabetes, greater glycemia does not seem to predict future CAD events. In addition, depressive symptomatology predicts angina and insulin resistance (eGDR) predicts hard CAD end points. Diabetes Care 26:1374 -1379, 2003B oth type 1 and type 2 diabetes increase the risk of coronary artery disease (CAD) (1). However, the reasons underlying this are largely unknown, although renal disease (2) and the standard CAD risk factors seem important (3). The role of glycemic control is controversial; two studies (3,4) suggest little relationship to CAD, although others report such an association (5).Although it has been an accepted practice to consider all CAD manifestations together, because they are believed to be linked by the same underlying atherosclerosis, important differences have been noted in the Pittsburgh Epidemiology of Diabetes Complications (EDC) study of type 1 diabetes. This study suggested somewhat distinct pathophysiologic mechanisms; for example, depressive symptomatology was more related to morbidity than mortality (3).To further address these issues, risk factors, including glycemic control, for angina, ischemic electrocardiogram (ECG), and hard CAD (myocardial infarction [MI], CAD death, or angiographically proven stenosis) were investigated in this prospective study of type 1 diabetes using, for the first time, the ...

OBJECTIVE -To estimate the prevalence and incidence of congestive heart failure (CHF) in populations with and without type 2 diabetes and to identify risk factors for diabetes-associated CHF.RESEARCH DESIGN AND METHODS -We searched the inpatient and outpatient electronic medical records of 9,591 individuals diagnosed with type 2 diabetes before 1 January 1997 and those of an age-and sex-matched control group without diabetes for a diagnosis of CHF. Among those without a baseline diagnosis of CHF, we searched forward for 30 months for incident cases of CHF. We constructed multiple logistic regression models to identify risk factors for both prevalent and incident CHF.RESULTS -CHF was prevalent in 11.8% (n ϭ 1,131) of diabetic subjects and 4.5% (n ϭ 435) of control subjects at baseline. We observed incident cases of CHF in 7.7% of diabetic subjects free of CHF at baseline (650 of 8,460) and in 3.4% of control subjects (314 of 9,156). In diabetic subjects, age, diabetes duration, insulin use, ischemic heart disease, and elevated serum creatinine were independent risk factors for both prevalent and incident CHF. Better glycemic control at baseline, and improved glycemic and blood pressure control at follow-up predicted the development of CHF.CONCLUSIONS -Despite controlling for age, duration of diabetes, presence of ischemic heart disease, and presence of hypertension, insulin use was associated with both prevalent and incident CHF. Why insulin use and better glycemic control both at baseline and follow-up independently predicted CHF deserves further study.

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The prevalence of being overweight in type 1 diabetes remains lower than that in the general population. Moderate weight gain did not adversely affect the cardiovascular risk profile in the setting of improved glycemic control.

Early and frequent follow-up by physicians--especially lipid testing--was associated with improved adherence to lipid-lowering therapy. A randomised prospective study is needed to determine whether this relationship is causal.

We conclude that a family history of type 2 diabetes is a risk factor for CAD in type 1 diabetic subjects. This supports the concept that insulin resistance may contribute to development of CAD in type 1 diabetes.