High cardiovascular event rates in patients with asymptomatic carotid stenosis: the REACH registry*
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Data on current cardiovascular event rates in patients with asymptomatic carotid artery stenosis (ACAS) are sparse. We compared the 1-year outcomes of patients with ACAS > or =70% versus patients without ACAS in an international, prospective cohort of outpatients with or at risk of atherothrombosis. METHODS: The Reduction of Atherothrombosis for Continued Health Registry enrolled patients with either > or =3 atherothrombotic risk factors or established atherothrombotic disease. We investigated the 1-year follow-up data of patients for whom physicians reported presence/absence of ACAS at the time of inclusion. RESULTS: Compared with patients without ACAS (n = 30 329), patients with ACAS (n = 3164) had higher age- and sex-adjusted 1-year rates of transient ischaemic attack (3.51% vs. 1.61%, P < 0.0001), non-fatal stroke (2.65% vs. 1.75%, P = 0.0009), fatal stroke (0.49% vs. 0.26%, P = 0.04), cardiovascular death (2.29% vs. 1.52%, P = 0.002), the composite end-point cardiovascular death/myocardial infarction/stroke (6.03% vs. 4.29%, P < 0.0001) and bleeding events (1.41% vs. 0.81%, P = 0.002). In patients with ACAS, Cox regression analyses identified history of cerebrovascular ischaemic events as most important predictor of future stroke (HR 3.21, 95% CI 1.82-5.65, P < 0.0001). CONCLUSION: Asymptomatic carotid artery stenosis was associated with high 1-year rates of cardiovascular and cerebrovascular ischaemic events. Stroke was powerfully predicted by prior cerebrovascular ischaemic events.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".