Sex-specific Relationship of Serum Uric Acid with All-cause Mortality in Adults with Normal Kidney Function: An Observational Study
Bibliographic record
Abstract
OBJECTIVE: To explain the clinical effect of serum uric acid (SUA) levels as a risk factor for mortality, considering exclusion of kidney function. METHODS: and who received laboratory study and colonoscopy on the same day were excluded. RESULTS: SUA levels were higher in men than in women (5.7 ± 1.2 mg/dl for men and 4.2 ± 0.9 mg/dl for women, p < 0.001). During 12.3 ± 3.6 years of followup, 1402 deaths occurred among 27,490 participants. About 6.9% of men and 3.1% of women died. The overall mortality rate had a U-shaped association with SUA levels, a U-shaped association in men, and no association in women. There was a significant interaction of sex for the SUA-mortality association (p for interaction = 0.049); therefore, survival analysis was conducted by sex. In men, the lower SUA group had a higher mortality rate after adjustment (SUA ≤ 4.0 mg/dl, adjusted HR 1.413, 95% CI 1.158-1.724, p = 0.001) compared with the reference group (SUA 4.1-6.0 mg/dl). A higher SUA contributed to an insignificant increased mortality in men (> 8.0 mg/dl, adjusted HR 1.140, 95% CI 0.794-1.636, p = 0.479). Women failed to show any significant association between SUA and mortality. CONCLUSION: This study provided novel evidence that SUA-mortality association differed by sex. We demonstrated that a lower SUA was an independent risk factor for all-cause mortality in men with normal kidney function.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".