Refining Long-Term Prediction of Cardiovascular Risk in Diabetes - The VILDIA Score.

ABSTRACT: Cardiovascular risk assessment in patients with diabetes relies on traditional risk factors. However, numerous novel biomarkers have been found to be independent predictors of cardiovascular disease, which might significantly improve risk prediction in diabetic patients. We aimed to improve prediction of cardiovascular risk in diabetic patients by investigating 135 evolving biomarkers. Based on selected biomarkers a clinically applicable prediction algorithm for long-term cardiovascular mortality was designed. We prospectively enrolled 864 diabetic patients of the LUdwigshafen RIsk and Cardiovascular health (LURIC) study with a median follow-up of 9.6 years. Independent risk factors were selected using bootstrapping based on a Cox regression analysis. The following seven variables were sel

SUBMITTER: Goliasch G 

PROVIDER: S-EPMC5498499 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature