Global Partnering Opportunities and Challenges of Psoriasis and Psoriatic Arthritis in Latin America: A Report from the GRAPPA 2010 Annual Meeting
Bibliographic record
Abstract
Documenting the disease burden of psoriasis and psoriatic arthritis (PsA) in Central and South America is difficult. The most conclusive data have come from the Iberoamerican Registry of Spondyloarthritis (RESPONDIA), which registered patients with a diagnosis of spondyloarthritis in a multinational, multicenter (Argentina, Brazil, Costa Rica, Chile, Mexico, Peru, Uruguay, Venezuela, Spain, and Portugal) cross-sectional study conducted between 2006 and 2007. Compared with elsewhere in the Western world, patients with PsA from RESPONDIA were older at study visit, at onset of symptoms, and at diagnosis of spondyloarthritis (SpA); had longer mean disease duration from onset of symptoms to diagnosis; and were more likely to have dactylitis, nail involvement, enthesitis, and peripheral arthritis in lower and upper extremities. It is critical to understand the biologic basis, estimate the disease burden, and determine the clinical treatment of PsA in Latin America. The Group for Research and Assessment of Psoriasis and PsA (GRAPPA) has an increasing number of members from this region. In a coordinated effort, GRAPPA, the Latin American Psoriasis and PsA Society (LAPPAS), and the Pan American League of Associations for Rheumatology (PANLAR) are supporting clinician researchers with educational initiatives in Latin America to understand these conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".