Are Target Urate and Remission Possible in Severe Gout? A Five-year Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Determine the proportion of patients achieving target serum urate (SU), defined as < 6 mg/dl for patients with non-severe gout and < 5 mg/dl for patients with severe gout, as well as the proportion of patients achieving remission after 5 years of followup. METHODS: Patients from the Gout Study Group (GRESGO) cohort were evaluated at 6-month intervals. Demographic and clinical data were obtained at baseline. Visits included assessments of serum urate, flares, tophus burden, health-related quality of life using the EQ-5D, activity limitations using the Health Assessment Questionnaire adapted for gout, and pain level and patient's global assessment using visual analog scales. Treatment for gout and associated diseases was prescribed according to guidelines and available drugs. RESULTS: Of 500 patients studied, 221 had severe gout (44%) and 279 had non-severe gout (56%) at baseline. No significant differences were observed across the study in percentages of severe gout versus non-severe gout patients achieving SU 6 mg/dl or 5 mg/dl. The highest proportion of patients achieving target SU (50-70%) and remission (39%) were found after 3-4 years of followup. In the fifth year, these proportions decreased and 28% of the patients were in remission, but only 40 patients remained in the study. None of the patients with severe gout achieved remission. CONCLUSION: In patients with severe gout, target SU was hard to achieve and remission was not possible. The main obstacles for target SU and gout remission include poor medication adherence, persistent tophi, and loss to followup.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".