Predictive Factors Driving Positive Awake Test in Carotid Endarterectomy Using Machine Learning

Juliana Pereira-Macedo, Ana Daniela Pias, Luís Duarte-Gamas, Piotr Myrcha, José P. Andrade, Nuno António, Ana Marreiros, João Rocha-Neves

Research output: Contribution to journalArticlepeer-review

Abstract

OBJECTIVES
Positive neurologic awake testing during the carotid cross-clamping may be present in around 8% of patients undergoing carotid endarterectomy (CEA). The present work aimed to assess the accuracy of an artificial intelligence (AI)-powered risk calculator in predicting intraoperative neurologic deficits (IND).

METHODS
Data was collected from carotid interventions performed between January 2012 and January 2023 under regional anesthesia. Patients with IND were selected along with consecutive controls without IND in a case-control study design. A predictive model for IND was developed using machine learning (ML), specifically Extreme Gradient Boosting (XGBoost) model, and its performance was assessed and compared to an existing predictive model. Shapley Additive exPlanations (SHAP) analysis was employed for the model interpretation.

RESULTS
Among 216 patients, 108 experienced IND during CEA. The AI-based predictive model achieved a robust area under the curve (AUC) of 0.82, with an accuracy of 0.71. High body mass index (BMI) increased contralateral carotid stenosis, and a history of limb paresis or plegia were significant IND risk factors. Elevated preoperative platelet and haemoglobin levels were associated with reduced IND risk.

CONCLUSIONS
This AI model provides precise IND prediction in CEA, enabling tailored interventions for high-risk patients and ultimately improving surgical outcomes. BMI, contralateral stenosis, and selected blood parameters emerged as pivotal predictors, bringing significant advancements to decision-making in CEA procedures. Further validation in larger cohorts is essential for broader clinical implementation.
Original languageEnglish
Pages (from-to)110-121
Number of pages12
JournalAnnals of vascular surgery
Volume111
Early online date22 Nov 2024
DOIs
Publication statusPublished - Feb 2025

Keywords

  • Carotid stenosis
  • intraoperative neurologic deficits
  • perioperative stroke
  • regional anesthesia

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