GME Patient Safety Quality and Innovation Symposium

Background:The gold standard for determining carotid artery stenosis is based on percent stenosis and symptomatic status. Few studies have assessed plaque morphology as an additive tool for stroke prediction. Our goal was to create a predictive model and risk score for 30-day stroke and death inclusive of plaque morphology.Methods:Patients with a CT angiography head/neck between 2010-2021 at a single institution and a diagnosis of carotid artery stenosis were included in our analysis. Each CT was used to create a 3D image of carotid plaque based off image recognition software. A stepwise backward regression was used to select variables for inclusion in our prediction models. Model discrimination was assessed with receiver operating characteristic curves (AUC). Additionally, calibration was performed and the model with the least Akaike Information Criterion (AIC) was selected. The risk score was modeled from the Framingham Study. Primary outcome was mortality and stroke.Results:We created three models to predict mortality/stroke from 366 patients: model A using only clinical variables, model B using only plaque morphology and model C using both clinical and plaque morphology variables. Model A used age, sex, PAD, hyperlipidemia, BMI, COPD, and history of TIA/stroke and had an AUC of 0.737 and AIC of 285.4. Model B used perivascular adipose tissue volume, lumen area, calcified volume, and target lesion length and had an AUC of 0.644 and AIC of 304.8. Finally, model C combined both clinical and software variables of age, sex, matrix volume, history of TIA/stroke, BMI, perivascular adipose tissue, lipid rich necrotic core, COPD and hyperlipidemia and had an AUC of 0.759 and the least AIC of 277.6 (Figure 1).Conclusions:Our study demonstrates that combining both clinical factors and plaque morphology creates the best predication of a patient’s risk for all-cause mortality and stroke from carotid artery stenosis. Additionally, we found that for patients with even 3 points in our risk score have a 20% chance of stroke/death. Further prospective studies are needed to validate our findings.