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Record W3049233926 · doi:10.3899/jrheum.200307

Febuxostat Use and Risks of Cardiovascular Disease Events, Cardiac Death, and All-cause Mortality: Metaanalysis of Randomized Controlled Trials

2020· review· en· W3049233926 on OpenAlexvenueno aff
Hao Deng, Bao Long Zhang, Tong Jin, Xiu Hong Yang, Hui Jin

Bibliographic record

VenueThe Journal of Rheumatology · 2020
Typereview
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFebuxostatRandomized controlled trialCause of deathInternal medicineDiseaseMeta-analysisCardiologyIntensive care medicineHyperuricemia

Abstract

fetched live from OpenAlex

Objective. To assess whether febuxostat use increases the risk of developing cardiovascular (CV) events, cardiac death, and all-cause mortalities. Methods. The relevant literature was searched in several databases including MEDLINE (PubMed, January 1, 1966–February 29, 2020), Web of Science, EMBASE (January 1, 1974–February 29, 2020), ClinicalTrials. gov, and Cochrane Central Register of Controlled Trials. Manual searches for references cited in the original studies and relevant review articles were also performed. All studies included in this metaanalysis were published in English. Results. In the end, 20 studies that met our inclusion criteria were included in our metaanalysis. Use of febuxostat was found not to be associated with an increased risk of all-cause mortality (RR 0.87, 95% CI 0.57–1.32,P= 0.51). Also, there was no association between febuxostat use and mortalities arising from CV diseases (CVD; RR 0.84, 95% CI 0.49–1.45,P= 0.53). The RR also revealed that febuxostat use was not associated with CVD events (RR 0.98, 95% CI 0.83–1.16,P= 0.83). Further, the likelihood of occurrence of CVD events was found not to be dependent on febuxostat dose (RR 1.04, 95% CI 0.84–1.30,P= 0.72). Conclusion. Febuxostat use is not associated with increased risks of all-cause mortality, death from CVD, or CVD events. Accordingly, it is a safe drug for the treatment of gout.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysishigh
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysishigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.032
metaresearch head score (Gemma)0.048
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.032
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.048
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0270.063
Bibliometrics0.0080.006
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.187
GPT teacher head0.396
Teacher spread0.208 · 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

Labeled directly by 2 models reading the full record.

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

Citations9
Published2020
Admission routes1
Has abstractyes

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