Long-Term Follow-up of a Randomized Controlled Trial of Allopurinol Dose Escalation to Achieve Target Serum Urate in People With Gout
Bibliographic record
Abstract
OBJECTIVE: To determine the long-term use of and adherence to urate-lowering therapy (ULT), serum urate (SU) control, and self-reported flares in participants from a randomized controlled trial of allopurinol dose escalation, in order to achieve target SU concentration (< 0.36 mmol/L) in people with gout. METHODS: For surviving study participants, ULT dispensing and SU testing within the preceding 12 months was obtained by medical record review. A phone interview was conducted to determine self-reported flares and adherence. RESULTS: Over a mean follow-up of 6.5 (SD 2.5) years since enrollment, 60 out of 183 (33%) participants had died. Review of the 119 surviving participants showed that 98 (82%) were receiving allopurinol, 5 (4%) were receiving febuxostat, and 10 (8%) were not receiving ULT; for the remaining 6 (5.0%), ULT use could not be determined. In those receiving allopurinol, the mean dose was 28.1 (range -600 to 500) mg/day lower than at the last study visit; 49% were receiving the same dose, 18% were on a higher dose, and 33% were on a lower dose than at the last study visit. SU values were available for 86 of the 119 (72%) participants; 50 out of 86 (58%) participants had an SU concentration of < 0.36 mmol/L. Of the 89 participants who participated in the phone interview, 19 (21%) reported a gout flare in the preceding 12 months and 79 (89%) were receiving allopurinol; 71 (90%) of those receiving allopurinol reported 90% or greater adherence. CONCLUSION: Most of the surviving participants in the allopurinol dose escalation study had good real-world persistence with allopurinol, remained at target SU, and had a low number of self-reported flares.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".