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Record W3164817217 · doi:10.1177/1759720x211016661

Hyperuricemia, urate-lowering therapy, and kidney outcomes: a systematic review and meta-analysis

2021· review· en· W3164817217 on OpenAlexaboutno aff
Gaurav Sharma, Abhishek Dubey, Nilesh Nolkha, Jasvinder A. Singh

Bibliographic record

VenueTherapeutic Advances in Musculoskeletal Disease · 2021
Typereview
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHyperuricemiaMeta-analysisInternal medicineUric acidIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Contradictory evidence exists for association of hyperuricemia and kidney function. To investigate the association of hyperuricemia and kidney function decline (hyperuricemia question) and effect of urate-lowering therapies (ULTs) on kidney function (ULT question), we performed a systematic review and meta-analysis. Methods: MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and CINAHL were searched from inception to July 2020. We selected observational studies for the hyperuricemia question and controlled trials for the ULT question. Two investigators independently assessed study eligibility and abstracted the data. Risk of bias was assessed using the Newcastle–Ottawa Scale and Cochrane risk of bias tool. Meta-analysis was done using the inverse variance method and random effect model. We estimated odds ratio (OR), hazard ratio (HR), risk ratio (RR), and the mean difference (MD). Evidence certainty was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Results: Of 12,037 studies screened, 131 studies with 3,414,226 patients were included. Hyperuricemia was associated with a significant risk of rapid estimated glomerula filtration rate (eGFR) decline ⩾3 ml/min per 1.73 m 2 per year (OR 1.38, 95% CI 1.20–1.59; low certainty), albuminuria (OR/HR 1.94, 95% CI 1.34–2.79; very low certainty), chronic kidney disease (OR/HR 2.13, 95% CI 1.74–2.61; very low certainty), and kidney failure (HR 1.53, 95% CI 1.18–1.99; very low certainty). Compared with control, ULT use for ⩾1 year was associated with significantly more improved eGFR (MD 1.81 ml/min per 1.73 m 2 , 95% CI 0.26–3.35; very low certainty), serum creatinine (MD −0.33 mg/dl, 95% CI −0.47 to −0.19; low certainty), and proteinuria (MD −5.44 mg/day, 95% CI −8.49 to −2.39; low certainty), but no difference in kidney failure. Conclusion: Hyperuricemia is associated with worsening eGFR, albuminuria, chronic kidney disease, and kidney failure. ULT use for ⩾1 year may improve kidney function. Registration: The protocol was registered at PROSPERO database, CRD42015013859.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.795
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.005
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.388
Teacher spread0.324 · 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; both teacher heads agree on what is shown here.

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

Citations42
Published2021
Admission routes1
Has abstractyes

Explore more

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