The Risk Stratification and Decision Support Systems in Surgical Management of Internal Carotid Artery Stenosis

Kapran Tatiana, Roman Vinogradov

Research Institute of Krasnodar Regional Hospital number 1 named in honour of S.V. Ochapovski, Krasnodar, Russia

Date, time and location: 2018.05.25 15:30, Congress Hall, 2F–B

Abstract

Objective: to determine the method of surgical management in patients with carotid artery stenosis.

Methods: This multicenter, non-randomized, retrospective study was held between 2010 and 2017. Overall, 2357 patients were included. Of 2357 patients, 1269 patients underwent carotid angioplasty with stent implantation (53.8%), 1088 patients underwent carotid endarterectomy (46.2%). We analyzed 58 risk factors which could have impact on periprocedural (stroke, transient ischemic attack, myocardial infarction, silent brain infarcts, death) and postprocedural endpoints (stroke, transient ischemic attack, myocardial infarction, death). Statistical analysis was performed with STATISTICA 10.0 (StatSoft Inc., USA) for Windows 10. We utilized factor analysis to study relationship between the variables. We also used classification tree and neural network methods on the basis of statistically significant dependent correlations.

Results: We determined 21 risk factors, containing baseline characteristics of patients, which have impact on the outcome of surgical intervention and on the choice of surgical management method. Strong correlation for stroke is determined for the risk factors: open-cell stent, low qualification of a surgeon, angioplasty in the setting of circular stenosis, previous stroke. These factors have impact on transient ischemic attack at a 30-day postoperative period: open-cell stent, previous stroke, low qualification of a surgeon, angioplasty in the setting of partial or circular stenosis, age > 80 years, carotid endarterectomy in the presence of contralateral occlusion of internal carotid artery. We developed risk score for stroke and death at a 30-day postoperative period if carotid artery surgery was performed.

Conclusions: We stratified risks for the complications which determine 30-day mortality after the surgical management of carotid artery stenosis. Using strong correlations and risk factors, we developed software allowing to predict complications in patients who need carotid revascularization. Also we developed software which recommends revascularization method with least possibility of complications and death. This information analysis forms decision support system in carotid artery surgery.