Association of Nail Psoriasis With Disease Activity Measures and Impact in Psoriatic Arthritis: Data From the Corrona Psoriatic Arthritis/Spondyloarthritis Registry
Bibliographic record
Abstract
Objective To examine the association of nail psoriasis with disease activity, quality of life, and work productivity in patients with psoriatic arthritis (PsA). Methods All patients with PsA who enrolled in the Corrona PsA/Spondyloarthritis Registry between March 2013 and October 2018 and had data on physician-reported nail psoriasis were included and stratified by presence vs absence of nail psoriasis at enrollment. Patient demographics, disease activity, quality of life (QOL), and work productivity at enrollment were compared between patients with vs without nail psoriasis usingt-tests or Wilcoxon rank-sum tests for continuous variables and chi-square or Fisher exact tests for categorical variables. Results Of the 2841 patients with PsA included, 1152 (40.5%) had nail psoriasis and 1689 (59.5%) did not. Higher proportions of patients with nail psoriasis were male (51.9% vs 44.1%) and disabled from working (12.3% vs 7.8%) compared with patients without nail psoriasis (allP< 0.05). Patients with nail psoriasis had higher disease activity than those without nail psoriasis, including higher tender and swollen joint counts, worse Disease Activity Index for Psoriatic Arthritis and Psoriatic Arthritis Disease Activity Score values, and increased likelihood of having enthesitis and dactylitis (allP< 0.05). Patients with nail psoriasis had worse pain, fatigue, and work and activity impairment than those without nail psoriasis (allP< 0.05). Conclusion Patients with PsA who have nail psoriasis had worse disease activity, QOL, and work productivity than those without nail involvement, emphasizing the importance of identification and management of nail disease in patients with 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".