Carotid endarterectomy (CEA) risk stratification for adverse events at one year follow-up: the role of preoperative functional capacity scores, age, BNP and hemoglobin
Abstract
The aim of the study was to evaluate combination of functional status tools (American Society of Anesthesiologists Physical Status Classification System (ASA PS)) status, Metabolic Equivalent of Task (METs), Revised Cardiac Risk Index for Pre-Operative Risk (RCRI) largely used in preoperative risk assessment with humoral variables in building powerful predictive models of Major Adverse Cardiac Cerebrovascular Events (MACCE) in a one-year follow-up after carotid endoarterectomy (CEA). All consecutive patients undergoing CEA during a 12-month period, were enrolled in this prospective observational study. Demographic data, functional capacity (FC) measured by risk stratification scores RCRI, ASA physical status, METs and preoperative levels of hemoglobin and Brain Natriuretic Peptide (Pro-BNP), coexisting comorbidities, have been collected. 201 consecutive patients undergoing CEA under local anesthesia (men 137 (68.16%), women 64 (31.84%)) with a median age of 75 years (Interquartile range (IQR) 67–80 years), Body mass index (BMI) median of 26.23 (IQR 24.4–28.89) were enrolled. Combination of all variables studied leave at a good one-year prognostic tool with AUC of 0.93 (Sensitivity (SEN) 46.6, Specificity (SPEC) 95.7). Preoperative hemoglobin correlate with Major Adverse Cardiac Cerebrovascular Events (MACCE) at 3 months (p = 0.018), while the preoperative BNP at 12 months shows correlation with adverse events (p = 0.004). Age has a significant correlation with adverse events at 12 months between demographic and anthropometric factors (p = 0.002). MACCE may adversely affect short- and long-term outcomes after CEA. Evaluation of preoperative functional capacity by RCRI, ASA physical status and METs combined with age and biomarkers such as pro-BNP and hemoglobin, may improve risk stratification in patients undergoing carotid surgery.
Subject
General Medicine,Applied Mathematics,General Engineering,General Medicine,General Materials Science,General Energy,General Medicine,Information Systems and Management,Information Systems,Software,General Medicine,General Medicine