Is axial psoriatic arthritis distinct from ankylosing spondylitis with and without concomitant psoriasis?
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to compare patients with ankylosing spondylitis with psoriasis (ASP) and without psoriasis (AS), to axial PsA (axPsA) patients. METHODS: Two adult cohorts were recruited from the AS clinic: ASP and AS. These two cohorts were compared with two adult cohorts recruited from the PsA clinic: axPsA (radiographic sacroiliitis: ⩾bilateral grade 2 or unilateral grade 3 or 4); and Peripheral PsA. All patients were followed prospectively according to the same protocol. The demographic, clinical and radiographic variables were compared. Adjusted means were used to account for varying intervals between visits. A logistic regression was performed and adjusted for follow-up duration. RESULTS: There were 477 axPsA patients, 826 peripheral PsA, 675 AS and 91 ASP patients included. AS patients were younger (P < 0.001), more male and HLA-B*27 positive (76%, 72% vs 64%, P ⩽ 0.001, 82%, 75%, vs 19%, P = 0.001). They had more back pain at presentation (90%, 92% vs 19%, P = 0.001), worse axial disease activity scores (bath ankylosing spondylitis disease activity index: 4.1, 3.9 vs 3.5 P = 0.017), worse back metrology (bath ankylosing spondylitis metrology index: 2.9, 2.2 vs 1.8, P < 0.001), worse physician global assessments (2.4, 2.2 vs 2.1, P < 0.001), were treated more with biologics (29%, 21% vs 7%, P = 0.001) and had a higher grade of sacroiliitis (90%, 84% vs 51%, P < 0.001). Similar differences were detected in the comparison of ASP to axPsA and in a regression model. CONCLUSION: AS patients, with or without psoriasis, seem to be different demographically, genetically, clinically and radiographically from axPsA patients. axPsA seems to be a distinct entity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".