Burden and Disease Characteristics of Patients with Psoriatic Arthritis: A Population-based Cross-sectional Study
Bibliographic record
Abstract
OBJECTIVE: To describe the prevalence and treatment regimes, disease characteristics, and comorbid diseases among patients with psoriatic arthritis (PsA) in Denmark. METHODS: All Danish individuals aged ≥ 18 years with rheumatologist-diagnosed PsA were linked in nationwide administrative registers. RESULTS: Among 4.7 million individuals in Denmark, 10,577 patients with PsA had been diagnosed by a rheumatologist. A female predominance (54.5-59.8%) was seen among patients with PsA, and about half of the patients (53.0%) had received no treatment or treatment only with nonsteroidal antiinflammatory drugs/systemic corticosteroids, while 32.9% had received nonbiological disease-modifying antirheumatic drugs (DMARD) and 14.1% had been treated with biologicals. Cutaneous psoriasis was recorded in 66.2-72.3% of patients with PsA, and patients with severe PsA had the highest prevalences of distal interphalangeal arthropathy, spondylitis, and arthritis mutilans. Smoking and comorbid diseases such as hypertension, diabetes, depression, and anxiety were seen frequently in patients with PsA, but did not significantly differ across severities of PsA. CONCLUSION: Disease burden appeared to be significant in patients with PsA across all severities. A considerable proportion of patients with PsA did not receive active antipsoriatic treatment, and about 1 out of 3 patients was not diagnosed with psoriasis. Cutaneous symptoms of psoriasis in patients with PsA might be either underreported or undertreated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| 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".