Stroke: A new model to help predict which patients are suitable for carotid endarterectomy

The purpose of carotid endarterectomy (CEA) is to prevent long-term strokes and should be performed on patients who may be the most beneficial in reducing the risk of stroke
.

It is recommended that asymptomatic patients who have recently experienced stroke or transient ischemic attack (TIA) related to ipsilateral high stenosis receive CEA on the basis of drug therapy

prevention

Since there have been no patients with symptoms related to carotid artery stenosis recently, the absolute benefits of CEA have become smaller due to the improvement of medical preventive treatment
.

The net benefit depends not only on the long-term reduction of stroke risk, but also on the risk of CEA procedures

Current guidelines recommend that the risk of stroke or death within 30 days for symptomatic patients is <6%, asymptomatic patients <3%, and patients with a life expectancy of 5 years should consider CEA
.

Due to improvements in medical treatment, the 30-day risk threshold of stroke or death for symptomatic patients may be reduced to 4%, and for asymptomatic patients to 2%

Risk prediction models may help inform patients of the risks of surgery, and may provide personalized risk estimates by considering some characteristics of patients and diseases11
.

Before implementing a prognostic risk prediction model in clinical practice, it needs to be externally validated in the contemporary patient population receiving CEA

In this way, dMichiel HF Poorthui and others at Utrecht University in the Netherlands explored the existing risk prediction models for post- CEA procedural stroke or death, and externally verified these models in the contemporary large-scale CEA patient registry in the United States
.

Explore the existing risk prediction models for procedural stroke or death after CEA , and externally validate these models in the large-scale CEA patient registry in the United States
.

Stroke

They conducted a systematic search for predictive models of procedural results after CEA in MEDLINE and EMBASE
.

These models were validated with data from patients who received CEA in the National Surgery Quality Improvement Program of the American College of Surgeons (2011-2017)

After screening 788 reports, 15 studies described 17 predictive models included
.

Nine studies were developed in a population that included asymptomatic and symptomatic patients, 2 were in the symptomatic population, and 5 were in the asymptomatic population

The C statistic for all patients is between 0.
52 and 0.
64, for symptomatic patients is between 0.
51 and 0.
59, and for asymptomatic patients is between 0.
49 and 0.
58
.

The Ontario Carotid Endarterectomy Registry risk model (Ontario Carotid Endarterectomy Registry risk model) includes symptomatic status, diabetes , heart failure, and contralateral occlusion as predictors.
Its C statistic is 0.
64, which is one of the predictive and observed risks.
The consistency between the two is the best
.

diabetes

The model found that 4.
5% of symptomatic patients and 2.
1% of asymptomatic patients had surgery risk exceeding the recommended threshold
.

The significance of this study lies in the discovery: Among 17 externally validated prediction models, the risk model of the Ontario Carotid Endarterectomy Registry has the most reliable prediction of procedural stroke or death after CEA , allowing patients Understanding the procedural hazards will help focus the CEA on the patients who will benefit most from them
.

The risk model of the Ontario Carotid Endarterectomy Registry has the most reliable prediction of procedural stroke or death after CEA

Original source:
Poorthuis MHF, Herings RAR, Dansey K, et al.

External Validation of Risk Prediction Models to Improve Selection of Patients for Carotid Endarterectomy.
Stroke.
Published online October 12, 2021:STROKEAHA.
1 20.
032527.

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