Transcranial Doppler Emboli Identifies Asymptomatic Carotid Patients at High Stroke Risk: Why This Technique Should be Used More Widely
Bibliographic record
Abstract
With modern intensive medical therapy, the annual risk of ipsilateral stroke in asymptomatic carotid stenosis (ACS) is now ∼0.5%. Therefore, even the relative low risks reported from the Carotid Revascularization Endarterectomy versus Stenting Trial (CREST) trial do not justify routine intervention in most (90%) of the patients with ACS. It is therefore necessary to identify the ∼10% to15% of patients with ACS who have a stroke risk high enough to justify intervention. Transcranial Doppler (TCD) embolus detection has been shown in 2 prospective studies (one with 468 patients and the other with 467 patients) to identify patients at high risk and distinguish them from those who would be better served by medical therapy. There is no valid reason why carotid intervention should be carried out in ACS without first identifying that the patient's risk of stroke is higher than the risk of intervention. The best validated way to do this is by TCD embolus detection, and the cost of TCD equipment and training is approximately the same as the cost of 2 carotid stenting procedures in the United States. This procedure should be used more widely.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".