Serum Uric Acid Is Independently Associated with Metabolic Syndrome in Subjects with and without a Low Estimated Glomerular Filtration Rate
Bibliographic record
Abstract
OBJECTIVE: The relationship among serum uric acid (SUA), metabolic syndrome, and chronic kidney disease (CKD) is unclear. We examined whether SUA level is an independent risk factor for chronic kidney disease and whether the association between SUA and metabolic syndrome is affected by kidney function. METHODS: We analyzed 28,745 subjects (17,478 men, 11,267 women, age 20-49 yrs) who underwent health examinations at this hospital between 2000 and 2007. Hyperuricemia was defined as SUA level > 7.7 mg/dl in men or > 6.6 mg/dl in women. Kidney function was assessed by estimated glomerular filtration rate (eGFR) using the Modification of Diet in Renal Disease Study equation modified for Chinese subjects. Impaired renal function with low GFR was defined as eGFR < 90 ml/min/1.73 m(2). The UA-low GFR groups were defined according to the observed combination of hyperuricemia and low GFR: Group A (absence of both hyperuricemia and low GFR); Group B (presence of low GFR but no hyperuricemia); Group C (presence of hyperuricemia but not low GFR); and Group D (presence of both hyperuricemia and low GFR). RESULTS: The prevalence of hyperuricemia, metabolic syndrome, and impaired kidney function with low GFR was 20.3% (27.6% in men, 8.9% in women), 7.6% (10.6% in men, 3.0% in women), and 9.9% (11.6% in men, 7.1% in women), respectively. The Pearson correlation between SUA and eGFR was only -0.26 (-0.21 in men, -0.22 in women; p < 0.001). In men, the age-adjusted odds ratio (OR) of metabolic syndrome was 1.41 (Group B), 2.45 (Group C), and 2.58 (Group D) in comparison with Group A. In women, the age-adjusted OR of metabolic syndrome was 0.83 (Group B), 5.47 (Group C), and 3.31 (Group D) in comparison with Group A. CONCLUSION: Hyperuricemia is prevalent in the Taiwan population. Hyperuricemia is only weakly associated with renal function, but is strongly associated with metabolic syndrome with or without a low eGFR.
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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 | 0.000 | 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 | 0.001 |
| 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".