P153 Radial-finger Pulse Wave Velocity as a Measure of Microvascular Stiffness: Feasibility and Response to Nitroglycerin
Bibliographic record
Abstract
Abstract Background/Objectives We previously demonstrated a different regional stiffness response of elastic and muscular arteries after the administration of nitroglycerin, leading to an alteration of aortic-brachial stiffness gradient. Regional stiffness of smaller arteries may respond differently to vasodilation drugs. The objectives of this study were 1- to assess the feasibility of measuring arterial stiffness of the hand, i.e. radial-finger pulse wave velocity (RF-PWV) using piezoelectric sensors, and 2- to measure RF-PWV and its response to nitroglycerin. Methods This exploratory study was conducted in 11 healthy participants (55% were men, mean age was 33.6 ± 10.6 yrs). Piezoelectric sensors (Complior) were placed simultaneously on carotid and radial arteries, and tip of the third finger, to obtain carotid-radial PWV (CR-PWV) and RF-PWV (in triplicates), before and after 4 minutes of 0.4 mg NTG sublingual spray. Results Visually, pressure curves at the finger and detection of the foot of the wave were obtained with a similar quality than radial and carotid pressure curves. The RF-PWV intra-session coefficient of variation was 7.3%. At baseline, mean CR-PWV and RF-PWV were respectively of 9.07 ± 1.24 m/s and 4.80 ± 1.42 m/s. After NTG, CR-PWV decreased (7.75 ± 1.32 m/s) and RF-PWV increased (6.75 ± 2.58 m/s), both significantly ( p < 0.01). Conclusion This first attempt to measure small arteries stiffness shows that it is possible to measure hand PWV. Again, we observed opposite changes in regional stiffness of different vascular territories with a vasodilator drug. These results may open up the path to a better understanding of microcirculation consequences of an altered stiffness gradient.
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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 | 0.006 | 0.002 |
| 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".