RADIAL-FINGER PULSE WAVE VELOCITY: RESPONSE OF PERIPHERAL SMALLER ARTERIES TO NITROGLYCERIN
Bibliographic record
Abstract
Objective: 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. Peripheral smaller arteries may also respond differently to nitroglycerin. 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. Design and method: This study was conducted in 29 healthy participants (66% were women, mean age was 40.0 ± 15.1 yrs). Piezoelectric sensors (Complior) were place simultaneously on carotid and radial arteries, and tip of the index and/or third finger, to obtain carotid-radial PWV (CR-PWV) and RF-PWV. These measurements were repeated with a subgroup of 11 subjects after 4 minutes of 0.4mg NTG sublingual spray. Raw data were analyzed using Matlab to ensure good quality of signals and adequacy of the foot-to-foot method. Results: Visually, pressure curves at both fingers were obtained with an excellent quality, similar to radial and carotid pressure curves. Identification of the feet of the finger pulse waveforms was optimal with the second derivative algorithm. RF-PWV intra-session coefficient of variation was 7.3%. At baseline, mean CR-PWV and RF-PWV were respectively of 8.21 ± 1.44 m/sec and 4.65 ± 1.42m/sec. 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). However, stiffness of the whole upper limb (carotid-finger PWV) did not change significantly (7.37 ± 0.87 m/s vs 7.29 ± 1.08 m/s, p=0.605). Conclusions: This first attempt to measure regional stiffness of small arteries 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 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 | 0.002 |
| 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) | 0.002 | 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".