Predictors of Mortality Over 8 Years in Type 2 Diabetic Patients
Translating Research Into Action for Diabetes (TRIAD)
- Laura N. McEwen, PHD1⇓,
- Andrew J. Karter, PHD2,
- Beth E. Waitzfelder, PHD3,
- Jesse C. Crosson, PHD4,
- David G. Marrero, PHD5,
- Carol M. Mangione, MD, MSPH6 and
- William H. Herman, MD, MPH1,7
- 1Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
- 2Kaiser Permanente, Division of Research, Oakland, California
- 3Kaiser Permanente, Center for Health Research, Honolulu, Hawaii
- 4Department of Family Medicine and Community Health, UMDNJ–Robert Wood Johnson Medical School, Somerset, New Jersey
- 5Indiana University Diabetes Translational Research Center, Indianapolis, Indiana
- 6University of California, Los Angeles, California
- 7Department of Epidemiology, University of Michigan, Ann Arbor, Michigan
- Corresponding author: Laura N. McEwen, .
OBJECTIVE To examine demographic, socioeconomic, and biological risk factors for all-cause, cardiovascular, and noncardiovascular mortality in patients with type 2 diabetes over 8 years and to construct mortality prediction equations.
RESEARCH DESIGN AND METHODS Beginning in 2000, survey and medical record information was obtained from 8,334 participants in Translating Research Into Action for Diabetes (TRIAD), a multicenter prospective observational study of diabetes care in managed care. The National Death Index was searched annually to obtain data on deaths over an 8-year follow-up period (2000–2007). Predictors examined included age, sex, race, education, income, smoking, age at diagnosis of diabetes, duration and treatment of diabetes, BMI, complications, comorbidities, and medication use.
RESULTS There were 1,616 (19%) deaths over the 8-year period. In the most parsimonious equation, the predictors of all-cause mortality included older age, male sex, white race, lower income, smoking, insulin treatment, nephropathy, history of dyslipidemia, higher LDL cholesterol, angina/myocardial infarction/other coronary disease/coronary angioplasty/bypass, congestive heart failure, aspirin, β-blocker, and diuretic use, and higher Charlson Index.
CONCLUSIONS Risk of death can be predicted in people with type 2 diabetes using simple demographic, socioeconomic, and biological risk factors with fair reliability. Such prediction equations are essential for computer simulation models of diabetes progression and may, with further validation, be useful for patient management.
This article contains Supplementary Data online at http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc11-2281/-/DC1.
- Received November 23, 2011.
- Accepted February 16, 2012.
- © 2012 by the American Diabetes Association.
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