Febuxostat improves endothelial function in hemodialysis patients with hyperuricemia: A randomized controlled study
Bibliographic record
Abstract
Endothelial dysfunction is often found in both hyperuricemia and hemodialysis patients. Recent studies have shown that treating hyperuricemia with allopurinol improves endothelial dysfunction. This study is performed to assess the effect of febuxostat on endothelial dysfunction in hemodialysis patients with hyperuricemia. We randomly assigned 53 hemodialysis patients with hyperuricemia to a febuxostat (10 mg daily) group and a control group and measured flow-mediated dilation, serum uric acid (UA) levels, systolic and diastolic blood pressure, malondialdehyde-modified low-density lipoprotein (MDA-LDL), and highly sensitive C-reactive protein (hsCRP) at baseline and at the end of a 4-week study period. Flow-mediated dilation increased from 5.3% ± 2.4% to 8.9% ± 3.6% in the febuxostat group but did not change significantly in the control group. Treatment with febuxostat resulted in a significant decrease in serum UA level and a significant decrease in MDA-LDL compared with baseline, but no significant difference was observed in hsCRP level or blood pressure. No significant differences were observed in the control group. Febuxostat improved endothelial dysfunction and reduced serum UA levels and oxidative stress in hemodialysis patients with hyperuricemia.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".