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Diabetes 53:434-440, 2004
© 2004 by the American Diabetes Association, Inc.
Electrocardiographic Repolarization Complexity and Abnormality Predict All-Cause and Cardiovascular Mortality in Diabetes
The Strong Heart Study
1 Department of Medicine, Division of Cardiology, Cornell Medical Center, New York, New York
2 College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma
3 University of Arizona, Tucson, Arizona
4 Medlantic Research Institute, Washington, DC
Type 2 diabetes is associated with increased risk of cardiovascular (CV) and all-cause mortality. Although electrocardiographic measures of repolarization abnormality and complexity stratify risk in the general population, their prognostic value in diabetes has not been well characterized. Digital electrocardiogram (ECG) readings were acquired for 994 American Indians with type 2 diabetes. ST segment depression (STD) 
50 µV and rate-corrected QT interval (QTc) >460 ms were examined as measures of repolarization abnormality. The principal component analysis (PCA) of the ratio of the second to first eigenvalues of the T-wave vector (PCA ratio) (>32.0% in women and >24.6% in men) was examined as a measure of repolarization complexity on the ECG. After a mean follow-up of 4.7 ± 1.0 years, there were 56 CV deaths and 155 deaths from all causes. In univariate analyses, STD, QTc, and the PCA ratio predicted CV and all-cause mortality. After multivariate adjustment for age, sex, and other risk factors, STD (hazard ratio 3.68, 95% CI 1.70–7.96) and PCA ratio (2.61, 1.33–5.13) remained predictive of CV mortality and both STD (2.36, 1.38–4.02) and QTc (2.03, 1.32–3.12) predicted all-cause mortality. Computerized ECG measures of repolarization abnormality and complexity predict CV and all-cause mortality in type 2 diabetes, supporting their use to identify high-risk individuals with diabetes.
Address correspondence and reprint requests to Peter M. Okin, MD, Weill Medical College of Cornell University, 525 E. 68th St., New York, NY 10021. E-mail: pokin{at}med.cornell.edu
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