Estimation of cardiovascular risk and detection of subclinical carotid atheromatosis in patients with diabetes without a history of cardiovascular disease

• Main Authors: Walter Masson, Salvador De Francesca, Micaela Molinero, Daniel Siniawski, Andrés Mulassi, Frank Espinoza Morales, Melina Huerin, Martín Lobo, Graciela Molinero
• Format: Article
• Language: English
• Published: Brazilian Society of Endocrinology and Metabolism 2017-02-01
• Series: Archives of Endocrinology and Metabolism
• Subjects: Diabetes; cardiovascular risk estimation; carotid atherosclerotic plaque
• Online Access: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2359-39972017000200122&lng=en&tlng=en

ABSTRACT Objectives Cardiovascular risk estimated by several scores in patients with diabetes mellitus without a cardiovascular disease history and the association with carotid atherosclerotic plaque (CAP) were the aims of this study. Materials and methods Cardiovascular risk was calculate using United Kingdom Prospective Diabetes Study (UKPDS) risk engine, Framingham risk score for cardiovascular (FSCV) and coronary disease (FSCD), and the new score (NS) proposed by the 2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol. Ultrasound was used to assess CAP occurrence. A receiver operating characteristic (ROC) analysis was performed. Results One hundred seventy patients (mean age 61.4 ± 11 years, 58.8% men) were included. Average FSCV, FSCD and NS values were 33.6% ± 21%, 20.6% ± 12% and 24.8% ± 18%, respectively. According to the UKPDS score, average risk of coronary disease and stroke were 22.1% ± 16% and 14.3% ± 19% respectively. Comparing the risks estimated by the different scores a significant correlation was found. The prevalence of CAP was 51%, in patients with the higher scores this prevalence was increased. ROC analysis showed a good discrimination power between subjects with or without CAP. Conclusion The cardiovascular risk estimated was high but heterogenic. The prevalence of CAP increased according to the strata of risk. Understanding the relationship between CAP and scores could improve the risk estimation in subjects with diabetes.