Carotid ultrasound, blood lipids and waist determination can predict a future coronary revascularisation in the type 2 diabetic cohort

Abstract

The aim of the study was to identify incremental values of carotid ultrasound measurements (carotid plaques and stenosis) on the prediction of future coronary revascularization among type 2 diabetic patients. The second objective was to determine the predictive value of the assessment of blood lipids, BMI, abdominal obesity and the ankle-brachial index (ABI). Three hundred and thirty three (333) patients with type 2 diabetes and manifested coronary artery disease were randomly selected in a cohort prospective study. Univariate and multivariate logistic regression analyses were conducted to identify variables predictive of the need for future revascularization: percutaneus coronary interventions (PCI) or coronary bypass surgery (CABG) followed 24 months after the study starting point. The presence of arterial hypertension, hyperlipidemia, physical inactivity, intermittent claudication, the value of systolic pressure, BMI, waist and hip measurement, glycemia and blood lipid fraction (total cholesterol, HDL, LDL, non-HDL, triglycerides) were entered in a model. Ultrasound measurements: carotid IMT, presence of carotid plaques and stenosis, and ABI were also included in the analysis. Based on the univariate and multivariate findings, the presence of internal carotid artery (ICA) stenosis (OR 4,562, 95% CI 1,327-15,687), carotid plaque (OR 1,465, 95% CI 0,829-2,591), and increased waist measurement (OR 1,371, 95% CI 0,757-2,483) were found as significant independent predictors of future PCI. LDL and non HDL cholesterol were found to be factors independently associated with the need for future CABG by univariate analysis, which was not confirmed by multivariate analysis. In conclusion, the current study has provided an identification of predisposing factors for the future need of coronary revascularization among type 2 diabetic patients that permits risk stratification and may facilitate improved patient selection or optimization.