Correlation of von Willebrand factor and platelets with acute ischemic stroke etiology and revascularization outcome: an immunohistochemical study
Bibliographic record
Abstract
BACKGROUND: Platelets and von Willebrand factor (vWF) are key components of acute ischemic stroke (AIS) emboli. We aimed to investigate the CD42b (platelets)/vWF expression, its association with stroke etiology and the impact these components may have on the clinical/procedural parameters. METHODS: test were performed as appropriate. RESULTS: The mean CD42b and VWF content in clots was 44.3% and 21.9%, respectively. There was a positive correlation between platelets and vWF (r=0.64, p<0.001**). We found a significantly higher vWF level in the other determined etiology (p=0.016*) and cryptogenic (p=0.049*) groups compared with cardioembolic etiology. No significant difference in CD42b content was found across the etiology subtypes. CD42b/vWF patterns were significantly associated with stroke etiology (p=0.006*). The peripheral pattern was predominant in atherosclerotic clots (36.4%) while the clustering (patchy) pattern was significantly associated with cardioembolic and cryptogenic origin (66.7% and 49.8%, respectively). The clots corresponding to other determined etiology showed mainly a diffuse pattern (28.1%). Two types of platelets were distinguished within the CD42b-positive clusters in all emboli: vWF-positive platelets were observed at the center, surrounded by vWF-negative platelets. Thrombolysis correlated with a high platelet content (p=0.03*). vWF-poor and peripheral CD42b/vWF pattern correlated with first pass effect (p=0.03* and p=0.04*, respectively). CONCLUSIONS: The vWF level and CD42b/vWF distribution pattern in emboli were correlated with AIS etiology and revascularization outcome. Platelet content was associated with response to thrombolysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".