External Validation of Risk Prediction Models to Improve Selection of Patients for Carotid Endarterectomy

Michiel H F Poorthuis1, Reinier A R Herings2, Kirsten Dansey3

  • 1Department of Neurology (M.H.F.P.), University Medical Center Utrecht, the Netherlands.

Stroke
|October 12, 2021
PubMed

Insights

The Ontario Carotid Endarterectomy Registry risk model best predicts stroke or death after carotid endarterectomy (CEA). This tool helps identify patients most likely to benefit from CEA, improving procedural safety and outcomes.

Area of Science:

  • Vascular Surgery
  • Medical Decision Making
  • Health Outcomes Research

Background:

  • Carotid endarterectomy (CEA) offers net benefit when procedural stroke or death risk is low.
  • Guidelines recommend CEA for symptomatic stenosis if 30-day risks are <6% and asymptomatic stenosis if <3%.

Purpose of the Study:

  • Identify and externally validate prediction models for procedural stroke or death after CEA.
  • Assess the reliability of existing models in a large US patient cohort.

Main Methods:

  • Systematic search of MEDLINE and EMBASE for CEA prediction models.
  • External validation using 26,293 patients from the American College of Surgeons National Surgical Quality Improvement Program (2011-2017).
  • Assessed model discrimination (C statistics) and calibration; identified patients exceeding risk thresholds.

Main Results:

  • 17 prediction models were evaluated; 702 (2.7%) patients experienced stroke or death within 30 days.
  • C statistics ranged from 0.49 to 0.64, indicating variable predictive accuracy.
  • The Ontario Carotid Endarterectomy Registry model demonstrated the best performance (C statistic 0.64) and calibration.

Conclusions:

  • The Ontario Carotid Endarterectomy Registry risk model provides the most reliable predictions for post-CEA stroke or death.
  • This validated model can inform patient counseling on procedural risks.
  • It aids in focusing CEA towards patients who stand to gain the most benefit.
Abstract