Association of Circulating Platelet Extracellular Vesicles and Pulse Wave Velocity with Cardiovascular Risk Estimation
Bibliographic record
Abstract
Elevated circulating platelet-derived extracellular vesicles (EVs) have been reported in conditions associated with thrombotic risk. The present study aimed to assess the relationship between circulating platelet-derived EV levels, cardiovascular risk stratification and vascular organ damage, as assessed by pulse wave velocity (PWV). A total of 92 patients were included in the present analysis. Platelet EV were evaluated by flow cytometry (CD41+/Annexin v+). The cardiovascular risk was determined using the 2021 ESC guideline stratification and SCORE2 and SCORE-OP. PWV was performed as a surrogate to assess macrovascular damage. Risk stratification revealed significant group differences in EV levels (ANOVA, p = 0.04). Post hoc analysis demonstrated significantly higher levels of EVs in the very high-risk group compared with the young participants (12.53 ± 8.69 vs. 7.51 ± 4.67 EV/µL, p = 0.03). Linear regression models showed SCORE2 and SCORE-OP (p = 0.04) was a predictor of EV levels. EVs showed a significant association with macrovascular organ damage measured by PWV (p = 0.01). PWV progressively increased with more severe cardiovascular risk (p < 0.001) and was also associated with SCORE2 and SCORE-OP (p < 0.001). Within the pooled group of subjects with low to moderate risk and young participants (<40 years), those with EV levels in the highest tertile had a trend towards higher nocturnal blood pressure levels, fasting glucose concentration, lipid levels, homocysteine and PWV. Levels of platelet-derived EVs were highest in those patients with very high CV risk. Within a pooled group of patients with low to moderate risk, an unfavourable cardiometabolic profile was present with higher EV levels.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".