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Record W2573445550 · doi:10.3899/jrheum.160792

Sex-specific Relationship of Serum Uric Acid with All-cause Mortality in Adults with Normal Kidney Function: An Observational Study

2017· article· en· W2573445550 on OpenAlexvenueno aff
Eunjeong Kang, Seung-Sik Hwang, Dong Ki Kim, Kook‐Hwan Oh, Kwon Wook Joo, Yon Su Kim, Hajeong Lee

Bibliographic record

VenueThe Journal of Rheumatology · 2017
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineRenal functionUric acidMortality rateObservational studyHyperuricemiaGastroenterology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.116
GPT teacher head0.326
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations32
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of RheumatologySame topicGout, Hyperuricemia, Uric AcidFrench-language works237,207