Predictive Value of Soluble Intercellular Adhesion Molecule-1 for Risk of Ischemic Events in Individuals with Cerebrovascular Disease
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cellular adhesion molecules may play a critical role in the inflammatory process leading to atherosclerosis. The purpose of this study was to determine whether soluble intercellular adhesion molecule-1 (sICAM-1) is a predictor of future ischemic events in high-risk individuals and also whether it is associated with carotid artery stenosis. METHODS: We conducted a prospective study of sICAM-1 concentration in 3 groups: (1) subjects with recent (< 7 days) ischemic stroke or TIA, (2) asymptomatic subjects with carotid stenosis > or = 50% and (3) asymptomatic individuals with vascular risk factors. Subjects were followed for a minimum of 3 years. sICAM-1 levels were compared between the groups and correlated with the risk of ischemic events and the degree of carotid artery stenosis. RESULTS: We studied 275 subjects. Mean sICAM-1 levels were significantly higher in those with recent ischemic stroke or TIA compared to those with risk factors alone. During follow-up, ischemic events occurred almost nine times more frequently in subjects in group 1 compared to group 3. sICAM-1 concentration was not predictive of future ischemic events (OR 1.001, 95% CI 0.998-1.004). There was no significant association between sICAM-1 concentration and carotid artery stenosis (OR 1.001, 95% CI 0.999-1.004). CONCLUSIONS: Mean sICAM-1 levels were higher in subjects with recent cerebral ischemia. No association between sICAM-1 and carotid artery stenosis was observed. Neither baseline nor subsequent sICAM-1 levels were predictive of the risk of future ischemic 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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".