Association of Physical Activity and Medication with Enthesitis on Ultrasound in Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Enthesitis is a manifestation of psoriatic arthritis (PsA), but its symptoms are difficult to interpret clinically. We investigated the associations of ultrasonographic changes in entheses with clinical characteristics in patients with PsA, and compared enthesis changes of patients aged 35 to 60 years with healthy volunteers of that age. METHODS: Consecutive patients with PsA participated in this cross-sectional study, irrespective of enthesitis complaints and age. We collected data about complaints, physical activity and activity avoidance, medication, and clinical enthesitis. Inflammatory and structural enthesis changes were scored with the modified MAdrid Sonographic Enthesitis Index (MASEI). Among all patients, associations between ultrasound (US) scores and clinical characteristics were investigated using linear regression. We compared US scores of healthy volunteers and patients with PsA aged 35-60 years using Wilcoxon rank-sum tests. RESULTS: Eighty-four patients with PsA and 25 healthy volunteers participated. In patients with PsA, we found a small association between higher inflammatory-modified MASEI score and older age (β 0.07, 95% CI 0-0.13) and current use of biologics (β 1.56, 95% CI 0.16-2.95). Patients who reported avoiding activities had significantly lower inflammatory-modified MASEI scores (β -1.71, 95% CI -3.1 to -0.32) than those who did not. The patients with PsA aged 35-60 years (n = 50) had similar inflammatory scores as healthy volunteers but higher structural scores (median 6 vs 2; p = 0.01). CONCLUSION: Within patients with PsA, avoiding physical activity, younger age, and not using biologics were associated with less enthesis inflammation. Patients with PsA and healthy volunteers aged 35 to 60 years displayed similar levels of inflammatory changes of the entheses, but patients had more structural damage.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".