Abstract WMP46: Frequency of High-Risk Features and Stroke Risk in Asymptomatic Carotid Atherosclerosis: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The recommended treatment of asymptomatic carotid atherosclerosis is best medical therapy since the 1% annual risk of stroke is lower than the risk of stroke from revascularization. Specific imaging features may identify patients at increased risk of stroke and optimize the risk-benefit ratio of carotid surgery. To assess the relevance and feasibility of such approach, we aimed to summarize available data on the frequency of high-risk features and the related risk of stroke in patients with asymptomatic carotid atherosclerosis. Methods: A search of Pubmed and Ovid-Embase identified prospective studies reporting findings of carotid plaque imaging and incidence of stroke in patients with asymptomatic carotid atherosclerosis. Prevalence of high-risk features and incidence of ipsilateral ischemic events were pooled using random-effect meta-analysis. Results: Thirty-five studies enrolling 5808 participants with asymptomatic carotid atherosclerosis of various grades were included. The pooled prevalence (95% CI) of high-risk features on plaque imaging was 28.8 (18.8 - 38.7). The prevalence of neovascularization was 53.5% (45.2 - 61.8), echolucency 40.0% (30.8 - 49.6), lipid-rich necrotic core 35.7% (24.1 - 48.1), thin or ruptured fibrous cap 27.5% (14.2 - 43.3), silent brain infarcts 27.0% (15.3 - 40.5), impaired cerebrovascular reserve 25.9% (10.3 - 45.5), intraplaque hemorrhage 19.2% (13.9 - 25.1), microembolic signals 14.4% (8.9 - 20.8), and ulceration 13.5% (1.3 - 34.0). In 15 cohort studies enrolling 4215 participants, the mean duration of follow-up was 3.5 years (2.0 - 4.6). The pooled incidence of ipsilateral ischemic events was 2.7 per 100 person-years (1.6 - 4.0). This incidence was higher in patients with a high-risk feature (4.9%, 2.3 - 8.2) than in those without (0.9%, 0.2 - 1.8) with an odds ratio of 4.6 (2.3 - 9.3). Conclusion: High-risk features on imaging are frequent in asymptomatic carotid atherosclerosis and associated with a fourfold increase in the annual risk of ipsilateral ischemic events. A risk-oriented selection of patients with asymptomatic carotid atherosclerosis prior to randomization in revascularization trials appears relevant and may be a strategy to prevent stroke in asymptomatic carotid atherosclerosis.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".