Back to Search
Start Over
Risk Prediction of Cardiovascular Disease in Type 2 Diabetes.
- Source :
- Diabetes Care; Oct2008, Vol. 31 Issue 10, p2038-2043, 6p, 2 Charts, 1 Graph
- Publication Year :
- 2008
-
Abstract
- OBJECTIVE -- Risk prediction models obtained in samples from the general population do not perform well in type 2 diabetic patients. Recently, 5-year risk estimates were proposed as being more accurate than 10-year risk estimates. This study presents a diabetes-specific equation for estimation of the absolute 5-year risk of first incident fatal/nonfatal cardiovascular disease (CVD) in type 2 diabetic patients with use of A1C and clinical characteristics. RESEARCH DESIGN AND METHODS -- The study was based on 11,646 female and male patients, aged 18-70 years, from the Swedish National Diabetes Register with 1,482 first incident CVD events based on 58,342 person-years with mean follow-up of 5.64 years. RESULTS -- This risk equation incorporates A1C, as in the UK Prospective Diabetes Study risk engine, and several clinical characteristics: onset age of diabetes, diabetes duration, sex, BMI, smoking, systolic blood pressure, and antihypertensive and lipid-reducing drugs. All predictors included were associated with the outcome (P < 0.0001, except for BMI P = 0.0016) with Cox regression analysis. Calibration was excellent when assessed by comparing observed and predicted risk. Discrimination was sufficient, with a receiver operator curve statistic of 0.70. Mean 5-year risk of CVD in ail patients was 12.0 ± 7.5%, whereas 54% of the patients had a 5-year risk ≥10%. CONCLUSIONS -- This more simplified risk equation enables 5-year risk prediction of CVD based on easily available nonlaboratory predictors in clinical practice and A1C and was elaborated in a large observational study obtained from the normal patient population aged up to 70 years. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01495992
- Volume :
- 31
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- Diabetes Care
- Publication Type :
- Academic Journal
- Accession number :
- 35061513
- Full Text :
- https://doi.org/10.2337/dc08-0662