Influence of Disease Manifestations on Health-related Quality of Life in Early Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Psoriatic arthritis (PsA) is a multifaceted disease. Affecting joints, skin, entheses, and dactylitis, its effect on health-related quality of life (HRQOL) could be substantial. We aim to assess HRQOL in patients newly diagnosed with PsA and analyze its associations with disease manifestations. METHODS: Data collected at time of diagnosis from patients with PsA included in the Dutch south-west Early Psoriatic Arthritis cohort (DEPAR) study were used. HRQOL was assessed using 8 domains of the Medical Outcomes Study Short Form-36 (SF-36) questionnaire. Patients were classified based on primary manifestation in arthritis subtypes (i.e., mono-, oligo-, or polyarthritis) and other subtypes (i.e., enthesitis, dactylitis, and axial disease). In all patients, presence of arthritis, enthesitis, dactylitis, psoriasis, and chronic inflammatory back pain was determined. Multivariable linear regression was used to determine associations of PsA manifestations with HRQOL. RESULTS: Of 405 patients, primary manifestation was peripheral arthritis in 320 (78 monoarthritis, 151 oligoarthritis, and 91 polyarthritis), enthesitis in 37, axial disease in 9, and dactylitis in 39. Mean scores of SF-36 domains were lower than the Dutch reference population and similar across arthritis subtypes. A higher number of enthesitis locations and tender joints, and presence of chronic back pain, were independently associated with worse SF-36 scores. Psoriasis and dactylitis were not associated with worse scores. CONCLUSION: HRQOL was diminished in PsA at time of diagnosis compared to the Dutch reference population, and tender joints, enthesitis at clinical examination, and back pain as indicators of pain affected HRQOL.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".