Отдаленные исходы плановых эндоваскулярных вмешательств на коронарных артериях

Abstract

to analyze long-term outcomes and to develop a model for determining the risk of long-term adverse сardiovascular events after elective percutaneous coronary interventions (PCI). We included in this study 148 patients, sent from 2009 to 2011 for routine endovascular intervention for chronic ischemic heart disease on the background of stenotic coronary artery atherosclerosis. Outcomes of interventions were assessed over 6 years after the index PCI by analyzing medical records and telephone interviews. The primary composite endpoint of the study was major adverse cardiovascular event (MACE), including cardiovascular death, acute coronary syndrome (ACS), acute cerebrovascular accident (CVA). Cardiovascular death was registered in 10.6 %, acute coronary syndrome occurred in 34.4 %, stroke - in 6.6 % of patients. Overall MAСE occurred in 40.4 % of patients. Patients with MACE were initially significantly more likely to have chronic obstructive pulmonary disease (16.4 vs. 4.4 %, p=0.02), multifocal atherosclerosis (32.8 vs. 17.8 %, p=0.034). They were initially more often diagnosed with atrial fibrillation (AF) (23 vs. 7.8 %, p=0.016) and were more likely to have family history of cardiovascular disease (50.8 vs. 24.4 %, p=0.0009). They had significantly higher levels of CRP before PCI (6 (5-11.5) vs. 5 (4.7) mg/L, p=0.034) and restenosis of previously installed stent (8.2 vs. 1.1 %, p=0.04). Most significant predictors of MACE identified using stepwise logistic regression and included in the developed model were: family history of cardiovascular disease, treatment with statins at time of PCI, initial level of postprandial blood glucose, high risk of contrast induced nephropathy (CIN) (11-15 points on Mehran CIN risk score). AUC values for the found model was 0.852 [95 % CI 0.749-0.956]. The use of our model in patients with the upcoming PCI with the aim of stratifying the risk of long-term adverse cardiovascular events allows to identify groups of patients, who require the timely administration of more active follow-up strategies, through the use of simple clinical characteristics.