Outcomes of Care Among Patients With Gout in Europe: A Cross-sectional Survey
Bibliographic record
Abstract
OBJECTIVE: To assess health- and patient-centered outcomes in gout across Europe, and explore patient-, care-, and country-level characteristics associated with these outcomes. METHODS: Patients with self-reported physician-diagnosed gout from 14 European countries completed an online survey. Multivariable mixed-effect logistic and linear regressions were computed for health outcomes (gout flare recurrence) and patient-centered outcomes (patient satisfaction with current medication, and unaddressed goals), accounting for clustering within countries. The role of patient-, care-, and country-level factors was explored. RESULTS: Participants included 1029 patients, predominantly diagnosed by a general practitioner (GP). One or more gout flares were reported by 70% of patients and ≥ 3 flares by 32%. Gout patients reported 1.1 ± 1.2 unaddressed goals, and 80% were satisfied with current medication. Patients with ≥ 3 and ≥ 1 flares were less likely to be treated with urate-lowering therapy (ULT) (OR 0.52, 95% CI 0.39-0.70 and OR 0.38, 95% CI 0.28-0.53, respectively), but more likely to have regular physician visits (OR 2.40, 95% CI 1.79-3.22 and OR 1.77, 95% CI 1.30-2.41). Three or more gout flares were also associated with lower satisfaction (OR 0.39, 95% CI 0.28-0.56) and more unaddressed goals (β 0.36, 95% CI 0.19-0.53). Notwithstanding, the predicted probability of being satisfied was still between 57% and 75% among patients with ≥ 3 flares but who were not receiving ULT. Finally, patients from wealthier and Northern European countries more frequently had ≥ 3 gout flares. CONCLUSION: Across Europe, many patients with gout remain untreated despite frequent reported flares. Remarkably, a substantial proportion of them were still satisfied with gout management. A better understanding of patients' satisfaction and its role in physicians' gout management decisions is warranted to improve quality of care and gout outcomes across Europe.
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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 | 0.002 | 0.004 |
| 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) | 0.001 | 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".