Carotid Endarterectomy: A Review
Bibliographic record
Abstract
BACKGROUND: Since the validation of carotid endarterectomy (CEA) as an effective means of stroke prevention, there has been renewed interest in its best indications and methods, as well as in how it compares to carotid angioplasty and stenting (CAS). This review examines these topics, as well as the investigation of carotid stenosis and the role of auditing and reporting CEA results. INVESTIGATION: Brain imaging with CT or MRI should be obtained in patients considered for CEA, in order to document infarction and rule out mass lesions. Carotid investigation begins with ultrasound and, if results agree with subsequent, good-quality MRA or CT angiography, treatment can be planned and catheter angiography avoided. An equally acceptable approach is to proceed directly from ultrasound to catheter angiography, which is still the gold-standard in carotid artery assessment. INDICATIONS: Appropriate patients for CEA are those symptomatic with transient ischemic attacks or nondisabling stroke due to 70-99% carotid stenosis; the maximum allowable stroke and death rate being 6%. Uncertain candidates for CEA are those with 50-69% symptomatic stenosis, and those with asymptomatic stenosis > or = 60% but, if selected carefully on the basis of additional risk factors (related to both the carotid plaque and certain patient characteristics), some will benefit from surgery. Asymptomatic patients will only benefit if surgery can be provided with exceptionally low major complication rates (3% or less). Inappropriate patients are those with less than 50% symptomatic or 60% asymptomatic stenosis, and those with unstable medical or neurological conditions. TECHNIQUES: Carotid endarterectomy can be performed with either regional or general anaesthesia and, for the latter, there are a number of monitoring techniques available to assess cerebral perfusion during carotid cross-clamping. While monitoring cannot be considered mandatory and no single monitoring technique has emerged as being clearly superior, EEG is most commonly used. "Eversion" endarterectomy is a variation in surgical technique, and there is some evidence that more widely practiced patch closure may reduce the acute risk of operative stroke and the longer-term risk of recurrent stenosis. CAROTID ANGIOPLASTY AND STENTING: Experience with this endovascular and less invasive procedure grows, and its technology continues to evolve. Some experienced therapists have reported excellent results in case series and a number of randomized trials are now underway comparing CAS to CEA. However, at this time it is premature to incorporate CAS into routine practice replacing CEA. AUDITING: It has been shown that auditing of CEA indications and results with regular feed-back to the operating surgeons can significantly improve the performance of this operation. Carotid endarterectomy auditing is recommended on both local and regional levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".