Arterial Stiffness, Pulse Pressure, and the Kidney
Bibliographic record
Abstract
Classical studies indicate that the contribution of kidneys to hypertension is almost exclusively related to the association between mean arterial pressure (MAP) and vascular resistance. Recent reports including estimates of glomerular filtration rate (GFR) have shown that pulse pressure (PP) and pulse wave velocity, 2 major indices of arterial stiffness, now emerge as significant predictors of cardiovascular risk and age-associated decline in GFR. Such findings are mainly observed in patients with hypertension and renal failure and in atherosclerotic subjects undergoing coronary angiography. In such patients, amplification of PP between ascending and terminal aorta at the renal site is constantly increased over 10mm Hg (P < 0.001), whereas MAP level remains continuously unmodified. This PP amplification is significantly associated with presence of proteinuria. Furthermore, increases in plasma creatinine and aortic stiffness are independently and positively correlated (P < 0.001) both in cross-sectional and longitudinal studies. All these relationships associating PP, arterial stiffness, and renal function are mainly observed in patients 60 years of age or older. Furthermore, in renal transplant patients and their donors, subjects have been recruited for evaluations of arterial stiffness and posttransplant decline in GFR. Determinants of GFR decline were evaluated 1 and 9 years after transplantation. The first year GFR decline was related to smoking and acute rejection, whereas the later was significantly and exclusively associated with donor age and aortic stiffness. Thus, in hypertensive humans, the observed association between PP and GFR suggests that the 2 parameters are substantially mediated by arterial stiffness, not exclusively by vascular resistance.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".