Effect of vitamin D supplementation on endothelial dysfunction in <i>hemodialysis</i> patients
Bibliographic record
Abstract
INTRODUCTION: Patients with chronic kidney disease (CKD) commonly experience 25-hydroxyvitamin D3 (25-OH-D3) deficiency, and these patients have a higher incidence of cardiovascular diseases (CVDs) due to endothelial dysfunction (ED). The aim of our study was to investigate the effect of 25-OH-D3 deficiency and its supplementation on ED in patients with CKD. METHODS: Twenty-nine uremic patients on dialysis and 20 healthy controls were evaluated for ED by high-resolution Doppler ultrasonography of the brachial artery. In addition, 25-OH-D3-deficient patients (25-OH-D3 < 30 nmol/L) with CKD and healthy controls were evaluated for ED before and after 8 weeks of oral vitamin D (cholecalciferol, 50,000 units) treatment. All subjects were evaluated for percent flow-mediated dilatation (%FMD), percent endothelium-independent nitroglycerin-induced vasodilatation (%NID), and bilateral carotid intima-media thickness (CIMT). FINDINGS: Patients on dialysis had lower %FMD and %NID 6.11 [2.27-12.74] and 10.96 [5.43-16.4], respectively, than controls 15.84 [8.19-22.49] and 21.74 [12.49-29.4], respectively (P < 0.05). Patients on dialysis had higher left and right CIMT (0.79 ± 0.15 and 0.78 ± 0.14, respectively) than controls (0.60 ± 0.09 and 0.59 ± 0.09, respectively; P < 0.05). In 25-OH-D3-deficient patients with CKD, after vitamin D treatment, %FMD was significantly increased in dialysis patients (10.25 [7.8-12.8]) compared to before supplementation (5.4 [2.77-6.15]; P < 0.001). DISCUSSION: These results indicated that dialysis patients had significantly lower blood 25-OH-D3 levels and higher CIMT than healthy subjects. In addition, vitamin D supplementation improved ED and increased %FMD in dialysis patients. Our findings suggest that vitamin D supplementation in dialysis patients might prevent CVD.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".