Variability in Urate-lowering Therapy Prescribing: A Gout, Hyperuricemia and Crystal-Associated Disease Network (G-CAN) Physician Survey
Bibliographic record
Abstract
To the Editor: Gout is common in people with chronic kidney disease (CKD) and its treatment is frequently suboptimal in this special population due to concerns over adverse events and/or efficacy of medications. There is controversy about the use of urate-lowering therapy (ULT) in those with CKD and lack of agreement about the dosing of allopurinol, the recommended first-line ULT1,2. The aim of this study was to determine real-world ULT prescribing patterns among a group of medical practitioners with an interest in gout. Members of the Gout, Hyperuricemia and Crystal-Associated Disease Network (G-CAN) were invited to participate in an online survey in May 2017. G-CAN is a multidisciplinary group (predominantly rheumatologists) with clinical/research interest in gout and crystalline arthritis. Ethical approval was not required for a professional online survey. Participants were asked for each stage of CKD … Address correspondence to Prof. L. Stamp, Department of Medicine, University of Otago Christchurch, PO Box 4345, Christchurch 8140, New Zealand. Email: Lisa.Stamp{at}cdhb.health.nz.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".