PsART-ID inception cohort: clinical characteristics, treatment choices and outcomes of patients with psoriatic arthritis
Bibliographic record
Abstract
OBJECTIVES: Our aim is to understand clinical characteristics, real-life treatment strategies, outcomes of early PsA patients and determine the differences between the inception and established PsA cohorts. METHODS: PsArt-ID (Psoriatic Arthritis- International Database) is a multicentre registry. From that registry, patients with a diagnosis of PsA up to 6 months were classified as the inception cohort (n==388). Two periods were identified for the established cohort: Patients with PsA diagnosis within 5-10 years (n = 328), ≥10 years (n = 326). Demographic, clinical characteristics, treatment strategies, outcomes were determined for the inception cohort and compared with the established cohorts. RESULTS: The mean (s.d.) age of the inception cohort was 44.7 (13.3) and 167/388 (43.0%) of the patients were male. Polyarticular and mono-oligoarticular presentations were comparable in the inception and established cohorts. Axial involvement rate was higher in the cohort of patients with PsA ≥10 years compared with the inception cohort (34.8% vs 27.7%). As well as dactylitis and nail involvement (P = 0.004, P = 0.001 respectively). Both enthesitis, deformity rates were lower in the inception cohort. Overall, 13% of patients in the inception group had a deformity. MTX was the most commonly prescribed treatment for all cohorts with 10.7% of the early PsA patients were given anti-TNF agents after 16 months. CONCLUSION: The real-life experience in PsA patients showed no significant differences in the disease pattern rates except for the axial involvement. The dactylitis, nail involvement rates had increased significantly after 10 years from the diagnosis and the enthesitis, deformity had an increasing trend over time.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".