Absence of Microemboli on Transcranial Doppler Identifies Low-Risk Patients With Asymptomatic Carotid Stenosis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Carotid endarterectomy clearly benefits patients with symptomatic severe stenosis (SCS), but the risk of stroke is so low for asymptomatic patients (ACS) that the number needed to treat is very high. We studied transcranial Doppler (TCD) embolus detection as a method for identifying patients at higher risk who would have a lower number needed to treat. METHODS: Patients with carotid stenosis of > or =60% by Doppler ultrasound who had never been symptomatic (81%) or had been asymptomatic for at least 18 months (19%) were studied with TCD embolus detection for up to 1 hour on 2 occasions a week apart; patients were followed for 2 years. RESULTS: 319 patients were studied, age (standard deviation) 69.68 (9.12) years; 32 (10%) had microemboli at baseline (TCD+). Events were more likely to occur in the first year. Patients with microemboli were much more likely to have microemboli 1 year later (34.4 versus 1.4%; P<0.0001) and were more likely to have a stroke during the first year of follow-up (15.6%, 95% CI, 4.1 to 79; versus 1%, 95% CI, 1.01 to 1.36; P<0.0001). CONCLUSIONS: Our findings indicate that TCD- ACS will not benefit from endarterectomy or stenting unless it can be done with a risk <1%; TCD+ may benefit as much as SCS if their surgical risk is not higher. These findings suggest that ACS should be managed medically with delay of surgery or stenting until the occurrence of symptoms or emboli.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".