Predictors of macrovascular disease in patients with type 2 diabetes mellitus.
OBJECTIVE
To assess the importance of classic and nonclassic risk factors in the development of coronary artery disease (CAD) or cerebrovascular disease (CVD) in patients with type 2 diabetes mellitus (DM).


METHODS
In this community-based, prospective cohort study, quantitative measurements for cholesterol, triglycerides (TGs), glucose, and lipoprotein(a) detected as a sinking pre-beta-lipoprotein band on electrophoresis were obtained from 1968 through 1982 from 449 patients who were free of CAD and CVD but had type 2 DM. Demographic data and covariables obtained were age, body mass index, duration of diabetes, sex, smoking, and hypertension. The relationship of individual continuous factors to the development of CAD and CVD as well as multivariate models were evaluated with use of the Cox proportional hazards model. The primary outcome was to determine which risk factors are associated with development of CAD or CVD in patients with type 2 DM.


RESULTS
After a mean follow-up of 13 years, 216 CAD and 115 CVD events had developed. The hazard ratio estimates with 95% confidence intervals (CIs) for CAD after multivariate analysis were significant for age, 1.45 (95% CI, 1.27-1.67); fasting glucose levels at enrollment, 1.63 (95% CI, 1.17-2.25); smoking, 1.45 (95% CI, 1.10-1.91); and TGs, 1.49 (95% CI, 1.15-1.92). The hazard ratio estimates for CVD were significant for age, 1.95 (95% CI, 1.59-2.38); hypertension, 1.89 (95% CI, 1.30-2.74); fasting glucose levels at enrollment, 1.69 (95% CI, 1.06-2.70); and smoking, 1.57 (95% CI, 1.07-2.30).


CONCLUSIONS
In diabetic patients, age, fasting glucose levels, smoking, and TG levels are independent risk factors for development of CAD events. Age, hypertension, glucose, and smoking predicted development of CVD events.
Abu-Lebdeh
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Division of Endocrinology, Metabolism, Nutrition and Internal Medicine, Mayo Clinic, Rochester, Minn 55905, USA. abulebdeh.haitham@mayo.edu
Hodge
D O
DO
Nguyen
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D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D001786:Blood Glucose / Q000032:analysis; D015992:Body Mass Index; D002561:Cerebrovascular Disorders / Q000209:etiology*; D002784:Cholesterol / Q000097:blood; D003327:Coronary Disease / Q000209:etiology*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000150:complications*; D005260:Female; D006801:Humans; D006973:Hypertension / Q000150:complications; D017270:Lipoprotein(a) / Q000097:blood; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects; D013997:Time Factors; D014280:Triglycerides / Q000097:blood
D001786:Blood Glucose; D017270:Lipoprotein(a); D014280:Triglycerides; D002784:Cholesterol