IMPACT OF BODY POSITION ON ARTERIAL STIFFNESS OF ELASTIC AND MUSCULAR ARTERIES
Bibliographic record
Abstract
Objective: Arterial stiffness is assessed through determination of pulse wave velocity (PWV) over an arterial segment of interest. Measurements are traditionally done in a supine position, which is both practical for high quality arterial pressure wave recordings, and the stability of pressure exerted on the arterial wall along the arterial path. The aim of this project was to study the effect of body position on the stiffness of elastic and muscular arteries. Design and method: This study was conducted with healthy adults. Aortic (cf-PWV) and brachial stiffness (CR-PWV) were repeatedly measured in three different positions (supine, 30̊ and 60̊) using the Complior Analyse. Brachial blood pressure (Mobil-O-graph) was also measured in each position. Generalized Estimating Equations in SPSS were performed to establish changes of PWV between positions. Results: In 23 healthy individuals (65% female, mean age of 36±15 years, and mean systolic (SBP) and diastolic blood pressures (DBP) of 120±2 mmHg and 76±2 mmHg, respectively), CF-PWV increased progressively with body tilting (8.7 (CI95% = 8.0–9.4) m/s supine, 9.4 (CI95% = 8.8–10.0) m/s at 30̊ and 9.5 (CI95% = 8.8–10.1) m/s at 60̊) (p<0.001)). On the other hand, CR-PWV didn’t significantly change with body tilting (8.7 (CI95% = 8.0–9.3) m/s supine, 8.8 (CI95% = 8.0–9.6) m/s at 30̊ and 8.9 (CI95% = 8.1–9.6) m/s at 60̊). SBP didn’t significantly change with body tilting (120 (CI95% = 116-125) mmHg supine, 121 (CI95% = 116–125) mmHg at 30̊ and 122 (CI95% = 117-126) mmHg at 60̊), while DBP increased (76 (CI95% = 71-80) mmHg supine, 78 (CI95% = 73–83) mmHg at 30̊ (p<0.022) and 81 (CI95% = 77-85) mmHg at 60̊ (p<0.001)). Heart rate also increased with body tilting (68 (CI95% = 64–72) BPM supine, 69 (CI95% = 65–73) BPM at 30̊ and 77 (CI95% = 72–82) BPM at 60̊ (p<0.001)). Conclusions: These preliminary results show that elastic and muscular arteries tend to react differently to body positions, without significant changes in arterial stiffness of medium muscular arteries in the arm.
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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 | 0.000 | 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".