Changes in central arterial stiffness during lower body negative pressure
Bibliographic record
Abstract
In order to examine the influence of lower body negative pressure (LBNP) on central arterial stiffness, nine participants were exposed to consecutive 15 min stages of LBNP at increasing intensities (−20, −40, −60, and −80 mm Hg) until pre‐syncope. Carotid‐femoral pulse wave velocity (cPWV), and continuous measures of heart rate (HR), and systolic (SBP) and mean arterial blood pressure (MAP) were recorded at each stage. SBP low frequency band power (SBPLF) and the HRV low to high frequency band power ratio (LF/HF HRV) served as surrogate indicators of sympathovagal tone. T‐tests were used to compare changes in cPWV, HR, SBPLF, LF/HF HRV, and MAP from baseline to the maximum tolerated LBNP stage (LBNPmax). Delta scores (baseline to LBNP max) were calculated and Pearson correlation used to examine the relationship between cPWV and HR, SBPLF, or LF/HF HRV. cPWV, HR, SBPLF, and LF/HF HRV increased from baseline to LBNPmax (cPWV +294.07 ± 220.98, p = 0.004; HR +26.00 ± 17.34 bpm, p = 0.002; SBPLF +7.89 ± 9.94, p = 0.044; LF/HF/ HRV +6.62 ± 4.45, p = 0.002), while MAP did not change. cPWV was not significantly related to HR, SBPLF, or HF/LF HRV. In conclusion, it appears that central arterial stiffness increases during LBNP but is not related to HR, MAP, or indirect indicators of sympathovagal tone. Supported by the National Sciences and Engineering Research Council of Canada.
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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 | 0.000 | 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".