4.7 Article

Predictors of Mortality Over 8 Years in Type 2 Diabetic Patients Translating Research Into Action for Diabetes (TRIAD)

Journal

DIABETES CARE
Volume 35, Issue 6, Pages 1301-1309

Publisher

AMER DIABETES ASSOC
DOI: 10.2337/dc11-2281

Keywords

-

Funding

  1. Centers for Disease Control and Prevention (Division of Diabetes Translation)
  2. National Institute of Diabetes and Digestive and Kidney Diseases
  3. Biostatistics and Economic Modeling Core of the Michigan Diabetes Research and Training Center [P60DK020572]

Ask authors/readers for more resources

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, tower income, smoking, insulin treatment, nephropathy, history of dyslipidemia, higher LDL cholesterol, angina/myocardial infarction/other coronary disease/coronary angioplasty/bypass, congestive heart failure, aspirin, beta-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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available