The Relationship Between Uric Acid and Mortality in Hemodialysis Patients
Bibliographic record
Abstract
INTRODUCTION: Uric acid, the end product of purine metabolism, is an antioxidant molecule. Both low and high serum uric acid levels are associated with increased mortality. The aim is to investigate the relationship between serum uric acid levels and mortality in hemodialysis patients. METHODS: This retrospective study was conducted on hemodialysis patients in Hatay, Turkey, between 2010 and 2023. Records were reviewed, and serum uric acid levels, other laboratory tests, and hemodialysis duration were noted. Patients on hemodialysis for at least 3 months were included. A p-value of less than 0.05 was considered statistically significant. FINDINGS: A total of 3443 hemodialysis patients were included. The average age was 64.39 ± 13.57 years (minimum: 18 years, maximum: 90 years), and 58% were male. The mean serum uric acid level was 6.23 ± 1.43 mg/dL (range: 0.1-16). The prevalence of hyperuricemia was 39.3%, and hypouricemia was 0.2%. The median parathyroid hormone (PTH) value was lower in the group with a serum uric acid level ≤ 4 mg/dL (p < 0.001) and higher in the group with a serum uric acid level > 7 mg/dL (p < 0.001). There were significant differences in mortality among the study groups (p < 0.001). Subgroup analyses revealed that the mortality rate was higher in the patient group with serum uric acid levels ≤ 4 mg/dL and lower in the group with serum uric acid levels > 7 mg/dL (p < 0.001). DISCUSSION: Low serum uric acid levels have been associated with increased mortality; this may be because serum uric acid is an indicator of nutritional status. Higher serum uric acid levels were associated with higher PTH levels; further studies are needed to elucidate the causal relationship. Low serum uric acid levels were associated with an increased risk of cerebrovascular disease.
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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 | 0.001 | 0.001 |
| 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".