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Record W2621671248 · doi:10.1136/bmj.j2376

Serum uric acid levels and multiple health outcomes: umbrella review of evidence from observational studies, randomised controlled trials, and Mendelian randomisation studies

2017· review· en· W2621671248 on OpenAlexaff
Xue Li, Xiangrui Meng, Maria Timofeeva, Ioanna Tzoulaki, Konstantinos K. Tsilidis, John P. A. Ioannidis, Harry Campbell, Evropi Τheodoratou

Bibliographic record

VenueBMJ · 2017
Typereview
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsCentre for Global Health Research
FundersChina Scholarship CouncilCancer Research UK
KeywordsObservational studyMedicineMeta-analysisRandomized controlled trialSystematic reviewMendelian randomizationMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

<b>Objective</b> To map the diverse health outcomes associated with serum uric acid (SUA) levels. <b>Design</b> Umbrella review. <b>Data sources</b> Medline, Embase, Cochrane Database of Systematic Reviews, and screening of citations and references. <b>Eligibility criteria</b> Systematic reviews and meta-analyses of observational studies that examined associations between SUA level and health outcomes, meta-analyses of randomised controlled trials that investigated health outcomes related to SUA lowering treatment, and Mendelian randomisation studies that explored the causal associations of SUA level with health outcomes. <b>Results</b> 57 articles reporting 15 systematic reviews and144 meta-analyses of observational studies (76 unique outcomes), 8 articles reporting 31 meta-analyses of randomised controlled trials (20 unique outcomes), and 36 articles reporting 107 Mendelian randomisation studies (56 unique outcomes) met the eligibility criteria. Across all three study types, 136 unique health outcomes were reported. 16 unique outcomes in meta-analyses of observational studies had P&lt;10<sup>-6</sup>, 8 unique outcomes in meta-analyses of randomised controlled trials had P&lt;0.001, and 4 unique outcomes in Mendelian randomisation studies had P&lt;0.01. Large between study heterogeneity was common (80% and 45% in meta-analyses of observational studies and of randomised controlled trials, respectively). 42 (55%) meta-analyses of observational studies and 7 (35%) meta-analyses of randomised controlled trials showed evidence of small study effects or excess significance bias. No associations from meta-analyses of observational studies were classified as convincing; five associations were classified as highly suggestive (increased risk of heart failure, hypertension, impaired fasting glucose or diabetes, chronic kidney disease, coronary heart disease mortality with high SUA levels). Only one outcome from randomised controlled trials (decreased risk of nephrolithiasis recurrence with SUA lowering treatment) had P&lt;0.001, a 95% prediction interval excluding the null, and no large heterogeneity or bias. Only one outcome from Mendelian randomisation studies (increased risk of gout with high SUA levels) presented convincing evidence. Hypertension and chronic kidney disease showed concordant evidence in meta-analyses of observational studies, and in some (but not all) meta-analyses of randomised controlled trials with respective intermediate or surrogate outcomes, but they were not statistically significant in Mendelian randomisation studies. <b>Conclusion</b> Despite a few hundred systematic reviews, meta-analyses, and Mendelian randomisation studies exploring 136 unique health outcomes, convincing evidence of a clear role of SUA level only exists for gout and nephrolithiasis.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.168
metaresearch head score (Gemma)0.404
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.168
Threshold uncertainty score0.889

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1680.404
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0230.018
Bibliometrics0.0280.028
Science and technology studies0.0020.003
Scholarly communication0.0100.010
Open science0.0070.005
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.803
GPT teacher head0.576
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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

Citations403
Published2017
Admission routes1
Has abstractyes

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Same venueBMJSame topicGout, Hyperuricemia, Uric AcidFrench-language works237,207