Algorithm for Diagnosing Cardiovascular Pathology in Diabetes Mellitus

Abstract

Introduction. The association of diabetes mellitus (DM) and cardiovascular diseases (CVD) is due to common pathophysiological processes that determine the prognosis and progression of both diseases. We studied the factors associated with the risk of developing cardiovascular pathology to create an algorithm for diagnosing it in patients diabetes mellitus. Patients and methods. A total of 449 patients (126 men and 323 women) with type 1 diabetes (133) and type 2 diabetes (316) were examined. The median age was 63 (53; 70) years. Serum cystatin C, C-reactive protein (CRP), homocysteine, interleukin-6 (IL-6), N-terminal natriuretic peptide (NTproBNP) and brain natriuretic peptide (BNP) levels, fibroblast growth factor (FGF-23) levels, tumor necrosis factor (TNF-α), chemokine MIG, endothelial growth factor (VEGF-A), chemokine RANTES were determined in all patients. Instrumental research methods included echocardiographic examination and ultrasound of the lower extremity and brachiocephalic arteries. Logistic regression and ROC analysis were used to assess the prognostic value of markers. Results. Cystatin C levels ≥0.96 mg/l were associated with increased natriuretic peptides in patients with diabetes and early stages of CKD (with GFR>60), IL-6 levels ≥2.13 mg/ml and FGF-23 ≥0.9 pmol/ l — with the risk of increasing natriuretic peptides, and IL-6 ≥0.9 pmol/l — with the risk of increase in left ventricular mass index. Based on the obtained results, we developed an algorithm for diagnosis of cardiovascular pathology in patients with diabetes mellitus. Conclusions. In the present study, we identified markers associated with the risk of adverse cardiovascular events in patients with diabetes and their diagnostic value.