Circulating platelet‐derived extracellular vesicles correlate with night‐time blood pressure and vascular organ damage and may represent an integrative biomarker of vascular health
Bibliographic record
Abstract
Elevated office blood pressure (BP) has previously been associated with increased levels of circulating extracellular vesicles (EVs). The present study aimed to assess the relationship between levels of platelet derived EVs, ambulatory BP parameters, and pulse wave velocity as a marker of macrovascular organ damage. A total of 96 participants were included in the study. Platelet-derived extracellular vesicles (pEVs) were evaluated by flow cytometry (CD41+/Annexin v+). BP evaluation included unobserved automated office BP and ambulatory BP monitoring. Carotid-femoral pulse wave velocity (PWV) was measured as a marker of macrovascular damage. pEVs correlated with nocturnal systolic BP (r = 0.31; p = .003) and nocturnal dipping (r = -0.29; p = .01) in univariable analysis. Multivariable regression models confirmed robustness of the association of EVs and nocturnal blood pressure (p = .02). In contrast, systolic office, 24h- and daytime-BP did not show significant associations with pEVs. No correlations were found with diastolic BP. Circulating pEVs correlated with pulse wave velocity (r = 0.25; p = .02). When comparing different hypertensive phenotypes, higher levels of EVs and PWV were evident in patients with sustained hypertension compared to patients with white coat HTN and healthy persons. Circulating platelet derived EVs were associated with nocturnal BP, dipping, and PWV. Given that average nocturnal BP is the strongest predictor of CV events, platelet derived EVs may serve as an integrative marker of vascular health, a proposition that requires testing in prospective clinical trials.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".