Axial Involvement in Psoriatic Arthritis: Effect on Peripheral Arthritis and Differential Features With Axial Spondyloarthritis in South America
Bibliographic record
Abstract
To the Editor: Reported data of axial involvement in psoriatic arthritis (PsA) are variable (25–70%). This variability is mainly linked to different ways of defining this feature. Gladman1 established that the prevalence of axial involvement in PsA was close to 50% and that it is associated with HLA-B27. Likewise, psoriasis (PsO) spondylitis, unlike ankylosing spondylitis (AS), is characterized by not having a greater preponderance of the male sex, greater skin involvement, and a less severe course.2 We carried out an observational, cross-sectional, single-center study. The objective of our study was to estimate the frequency of axial involvement in patients with a recent diagnosis of PsA in a rapid diagnostic circuit called Reuma-Check3 and to carry out a comprehensive characterization (clinical, laboratory, and images). We also aimed to analyze the effect of axial involvement on other manifestations, and finally, to compare all features with a group of patients with axial spondyloarthritis (axSpA), diagnosed in the same circuit (with the same evaluators and the same imaging and laboratory techniques) in the same period of time, who did not present current PsO or history of PsO. This observational study was approved by an institutional ethics committee and was conducted in accordance with the current Declaration …
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".