The Psoriatic Arthritis Registry of Turkey: results of a multicentre registry on 1081 patients
Bibliographic record
Abstract
OBJECTIVE: The aim was to assess the characteristics of PsA, find out how well the disease is controlled in real life, demonstrate the treatments and identify the unmet needs. METHODS: The PsA registry of Turkey is a multicentre Web-based registry established in 2014 and including 32 rheumatology centres. Detailed data regarding demographics for skin and joint disease, disease activity assessments and treatment choices were collected. RESULTS: One thousand and eighty-one patients (64.7% women) with a mean (sd) PsA duration of 5.8 (6.7) years were enrolled. The most frequent type of PsA was polyarticular [437 (40.5%)], followed by oligoarticular [407 (37.7%)] and axial disease [372 (34.4%)]. The mean (sd) swollen and tender joint counts were 1.7 (3) and 3.6 (4.8), respectively. Of these patients, 38.6% were on conventional synthetic DMARD monotherapy, 7.1% were on anti-TNF monotherapy, and 22.5% were using anti-TNF plus conventional synthetic DMARD combinations. According to DAS28, 86 (12.4%) patients had high and 105 (15.2%) had moderate disease activity. Low disease activity was achieved in 317 (45.7%) patients, and 185 (26.7%) were in remission. Minimal disease activity data could be calculated in 247 patients, 105 of whom (42.5%) had minimal disease activity. The major differences among sexes were that women were older and had less frequent axial disease, more fatigue, higher HAQ scores and less remission. CONCLUSION: The PsA registry of Turkey had similarities with previously published registries, supporting its external validity. The finding that women had more fatigue and worse functioning as well as the high percentage of active disease state highlight the unmet need in treatment of PsA.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".