Effect of sevelamer on aortic pulse wave velocity in patients on hemodialysis: A prospective observational study
Bibliographic record
Abstract
Aortic stiffening and aortic calcification are risk factors for cardiovascular events in hemodialysis (HD) patients, and these 2 risk factors are interrelated. Sevelamer decreases aortic calcification but its effect on aortic stiffness has not been investigated previously. Thirteen HD patients commencing sevelamer treatment and 13 matched controls were followed for 11 months. Aortic pulse wave velocity (PWV), augmentation index (AIx), and levels of inhibitors of vascular calcification (fetuin-A, matrix-GLA-protein, osteoprotegerin/RANKL) were measured at baseline and at the end of follow-up, and the differences between the groups were compared. Determinants of the changes in PWV during follow-up were assessed by multivariate linear regression. At baseline, PWV was 9.93 (2.10) m/s in sevelamer-treated patients and 9.20 (2.84) m/s in control patients (p=0.464). By the end of follow-up, PWV decreased by 0.83 (2.3) m/s in sevelamer-treated patients while it increased by 0.93 (1.88) m/s in controls (p=0.042). The direction of changes in AIx were similar, but not statistically significant. There were no significant differences in the levels of inhibitors of calcification either at baseline or during follow-up. In multivariate linear regression sevelamer treatment, diabetes, heart rate, and C-reactive protein were related to the change in PWV. These data suggest that sevelamer treatment is associated with an improvement in aortic stiffness in HD patients, but it does not seem to affect serum levels of inhibitors of vascular calcification.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".