Determinants of Progression of Aortic Stiffness in Hemodialysis Patients
Bibliographic record
Abstract
Aortic stiffness is associated with increased cardiovascular mortality in patients with chronic kidney disease. However, the rate of progression of arterial stiffness and the role of cardiovascular risk factors in the progression of arterial stiffness has never been established in a longitudinal study. In a prospective, longitudinal, observational study, carotid-femoral pulse wave velocity and carotid-radial pulse wave velocity were assessed in 109 hemodialysis patients at baseline and after a mean follow-up of 1.2 years. We examined the impact of age, atherosclerotic cardiovascular disease, diabetes mellitus, dialysis vintage, and pentosidine (a well-characterized, advanced glycation end products) on the rate of progression of aortic stiffness. The annual rate of changes in carotid-femoral pulse wave velocity and carotid-radial pulse wave velocity were 0.84 m/s per year (95% confidence interval, 0.50-1.12 m/s per year) and -0.66 m/s per year (95% confidence interval, -0.85 to -0.47 m/s per year), respectively. Older subjects, and patients with diabetes mellitus or atherosclerotic cardiovascular disease had higher aortic stiffness at baseline, however, the rate of progression of aortic stiffness was only determined by plasma pentosidine levels (P=0.001). The degree of baseline aortic stiffness was a significant determinant of the regression of brachial stiffness (P<0.001) suggesting that the regression of brachial stiffness occurs in response to central aortic stiffness. These findings suggest that traditional cardiovascular risk factors may play some role in the progression of aortic stiffness before development of advanced chronic kidney disease, and that the enhanced rate of progression of aortic stiffness in chronic kidney disease patients on dialysis are probably determined by more specific chronic kidney disease-related risk factors such as advanced-glycation end products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".