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Record W4298394637 · doi:10.3899/jrheum.220927

Long-Term Adherence to Urate-Lowering Therapy in Gout: A Glass Half Empty or a Glass Half Full?

2022· letter· en· W4298394637 on OpenAlexvenueno aff
Lindsay N. Helget, Ted R. Mikuls

Bibliographic record

VenueThe Journal of Rheumatology · 2022
Typeletter
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsnot available
Fundersnot available
KeywordsGoutMedicineFebuxostatAllopurinolProbenecidHyperuricemiaInternal medicineTophusBenzbromaroneMedical prescriptionIntensive care medicinePhysical therapyUric acidPharmacology

Abstract

fetched live from OpenAlex

Characterized by flares of intensely painful arthritis, gout is the most common type of inflammatory arthritis worldwide. National prevalence estimates approaching 4% translate to more than 9 million persons living with gout in the United States alone, with worldwide estimates reaching as high as 10% in some regions.1,2 The painful nature of gout flare often leads patients to seek acute care, which, in turn, results in increased healthcare costs in addition to decreased work attendance and productivity.3,4 Central to disease pathogenesis, hyperuricemia is a necessary (albeit insufficient) risk factor in gout development. Several highly effective and well-tolerated urate-lowering therapies (ULTs; eg, allopurinol, febuxostat, probenecid) are available for use and collectively provide the real potential of reducing or even preventing flares. Allopurinol, the most commonly used ULTs, is relatively inexpensive, retailing at approximately $20 to $30 per month in the US without insurance or even as little as $5 per month with select prescription programs.5 Although widely accessible and well tolerated by most, fewer than 50% of patients with a gout diagnosis are started on urate-lowering medications.6 Perhaps even more disheartening is the dismal number of patients who adhere to ULT once initiated. A retrospective cohort study of over 13,000 patients with gout recently initiated on allopurinol demonstrated that 57% of patients took their medication less than 80% of the time over the course of a year, and 68% of subjects did not reach a goal serum urate (SU) of < 6 mg/dL.7 A metaanalysis pooling data from 22 studies found that adherence (defined by a variety of methods including prescription claims, pill counts, self-report, and interview) was 47%. … Address correspondence to Dr. L.N. Helget, Assistant Professor of Medicine, Department of Internal Medicine, Division of Rheumatology and Immunology, 986270 Nebraska Medical Center, Omaha, NE 68198-6270, USA. Email: lindsay.helget{at}unmc.edu.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.003
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 head0.035
GPT teacher head0.300
Teacher spread0.265 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2022
Admission routes1
Has abstractyes

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