Diagnosis of Chronic Gout: Evaluating the American College of Rheumatology Proposal, European League Against Rheumatism Recommendations, and Clinical Judgment
Bibliographic record
Abstract
OBJECTIVE: Observation of monosodium urate (MSU) crystal is the gold standard for diagnosis of gout, but is rarely performed in daily clinical practice, and diagnosis is based on clinical judgment. Our aim was to identify clinical and paraclinical data included in the European League Against Rheumatism recommendations (EULARr) and American College of Rheumatology proposed criteria (ACRp) for diagnosis of gout in patients with chronic gout according to their attending rheumatologists. METHODS: This cross-sectional and multicenter study included consecutive patients from outpatient clinics with a diagnosis of gout by their attending rheumatologists according to their expertise. The frequency of each item from the ACRp and EULARr was determined. Possible combinations of the items that were frequent, clinically relevant, and simple to evaluate in daily practice were determined. RESULTS: We studied 549 patients (96% men), mean age 50 +/- 14 years. Analysis of MSU crystals was performed in 15%. We selected 7 clinical criteria and 1 laboratory measure because of their frequency, importance, and simplicity to obtain: current or past history of: > 1 attack of acute arthritis (93%); mono or oligoarthritis attacks (74%); rapid progression of pain and swelling (< 24 hours; 74%); podagra (70%); erythema (56%); unilateral tarsitis (33%); tophi (52%); and hyperuricemia (93%). The chronic gout diagnosis (CGD) proposal comprised >or= 4/8 of these; 88% of patients had the criteria of the CGD proposal while 75% had 6/11 ACRp criteria (p = 0.001). When analysis of MSU crystals was added, 90.1% (CGD) and 83.9% (ACRp) met the criteria (p = 0.004). CONCLUSION: Current or past history of >or= 4/8 CGD parameters is highly suggestive of chronic gout.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".