From Psoriasis to Psoriatic Arthritis: Insights from Imaging on the Transition to Psoriatic Arthritis and Implications for Arthritis Prevention
Bibliographic record
Abstract
PURPOSE OF REVIEW: To describe the recent advances in the field towards the prevention and early recognition of Psoriatic Arthritis (PsA). RECENT FINDINGS: Defining the preclinical phase of PsA remains challenging since up to 50% of subjects with psoriasis have subclinical imaging enthesopathy, but many of these do not progress to PsA. Nevertheless, there is evidence that subjects with subclinical imaging enthesopathy are at increased risk of developing PsA. In recent years, it has been shown that both PsA and anti-citrullinated protein antibodies (ACPA) positive rheumatoid arthritis (RA) are characterized by a subclinical phase of non-specific or brief duration arthralgia with shared imaging features accounting for joint symptomatology. Sonographically determined tenosynovitis and enthesitis are the key imaging features present in non-specific PsO arthralgia that are at risk of future PsA development. Furthermore, the early phases of PsA are complicated by factors including body mass index (BMI), which is a risk factor for PsA, but BMI is also associated with imaging abnormalities on enthesopathy. Fully disentangling these clinical and imaging factors will be important for enrichment for imminent PsA so that disease prevention strategies can be investigated. Psoriasis patients with arthralgia have a higher prevalence of tenosynovitis and imaging enthesopathy is at higher risk of transitioning to overt 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".