CAROTID STENOSIS: A STUDY ON THE DIFFERENCE IN POST-SURGICAL INTERVENTION RISK FACTORS BETWEEN SYMPTOMATIC AND ASYMPTOMATIC PATIENTS

• Grant number: 25/08535-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2025
• End date: July 31, 2026
• Field of knowledge: Health Sciences - Medicine - Surgery
• Principal Investigator: Ana Terezinha Guillaumon
• Grantee: Rafael dos Reis Guilherme
• Host Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

**Introduction:** Cardiovascular diseases are the leading cause of global mortality in low- and middle-income countries. Atherosclerosis can lead to the formation of plaques in the carotid artery and subsequent stenosis, which is associated with an increased risk of ischemic strokes. Carotid stenosis has a global prevalence of 1.8% in men and 1.2% in women aged 30 to 79 years. Patients with this condition may present with either symptomatic or asymptomatic clinical features, and surgical interventions such as carotid endarterectomy (CEA) or carotid artery stenting (CAS) are indicated.**Objectives:** The primary objective is to identify factors influencing short-, medium-, and long-term morbidity and mortality in patients with carotid stenosis undergoing surgical intervention at the Hospital de Clínicas da UNICAMP. Secondarily, the study aims to develop a prognostic risk score for these patients.**Methods:** This is a retrospective observational study involving data from patients treated between 2014 and 2024 at the Hospital de Clínicas da UNICAMP and included in the Rheuni Group database, approved by the Research Ethics Committee under the number 026/2012. Patients aged 18 years or older with carotid stenosis and complete clinical records will be included. The risk factors evaluated include age, gender, degree of occlusion, clinical presentation, carotid clamping time, use of cerebral protection devices, and comorbidities.**Data Analysis:** Variables will be analyzed using univariate and multivariate statistics to identify independent factors associated with outcomes. Performance will be evaluated by the area under the curve (AUC), with significance defined as p<0.05. (AU)