Axial psoriatic arthritis in patients not fulfilling the back pain entry features of the ASAS Classification Criteria for Axial Spondyloarthritis: findings from the ATTRACT Study
Bibliographic record
Abstract
OBJECTIVE: Application of the ASAS classification criteria for axSpA in classifying axPsA is a topic of debate. In this study, we aimed to determine the prevalence of axPsA in patients with psoriasis and back pain who do not meet the entry pain features of the ASAS classification criteria. METHODS: Patients reporting late-onset back pain (LoBP, after the age of 45) or non-chronic back pain (NcBP, lasting less than months) in the DCS screening tool were included in a group termed 'non-ASAS back pain' (non-ASAS/BP). They underwent clinical/instrumental assessment aimed at axPsA diagnosis and were compared with those patients fulfilling both of two ASAS entry pain features at the screening (ASAS/BP). RESULTS: After rheumatological evaluation, 50/265 (18.8%) patients, 34/50 (68%) LoBP and 16/50 (32%) NcBP, were categorized as the non-ASAS/BP group. In comparison with ASAS/BP patients, the mean age was higher, and the prevalence of IBP was lower. Clinical disease activity was similar between the two groups. AxPsA was confirmed in 6/50 (12%) non-ASAS/BP patients, which is a lower incidence than in the ASAS/BP group (29.0%). Finally, non-ASAS/BP axPsA patients showed a similar proportion of inflammatory and post-inflammatory radiographic and/or MRI changes as shown in ASAS/BP axPsA patients. CONCLUSION: This study demonstrates that among psoriatic patients who experience late-onset or non-chronic back pain, thereby not fulfilling ASAS entry pain features, a considerable proportion may be affected by active axPsA.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".