Clinical applications of arterial stiffness; definitions and reference values
Bibliographic record
Abstract
Arterial stiffening is the most important cause of increasing systolic and pulse pressure, and for decreasing diastolic pressure beyond 40 years of age. Stiffening affects predominantly the aorta and proximal elastic arteries, and to a lesser degree the peripheral muscular arteries. While conceptually a Windkessel model is the simplest way to visualize the cushioning function of arteries, this is not useful clinically under changing conditions when effects of wave reflection become prominent. Many measures have been applied to quantify stiffness, but all are approximations only, on account of the nonhomogeneous structure of the arterial wall, its variability in different locations, at different levels of distending pressure, and with changes in smooth muscle tone. This article summarizes the methods and indices used to estimate arterial stiffness, and provides values from a survey of the literature, followed by recommendations of an international group of workers in the field who attended the First Consensus Conference on Arterial Stiffness, which was held in Paris during 2000, under the chairmanship of M.E. Safar and E.D. Frohlich.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".