Investigating Dimensions of Stiffness in Rheumatoid and Psoriatic Arthritis: The Australian Rheumatology Association Database Registry and OMERACT Collaboration
Bibliographic record
Abstract
OBJECTIVE: It is not known how the experience of stiffness varies between diagnoses or how best to measure stiffness. The aims of our study were to (1) compare stiffness in psoriatic arthritis (PsA) and rheumatoid arthritis (RA) using patient-reported outcomes, (2) investigate how dimensions of stiffness are associated with each other and reflect the patient experience, and (3) analyze how different dimensions of stiffness are associated with physical function. METHODS: An online survey was sent to Australian Rheumatology Association Database participants (158 PsA, and 158 age- and sex-matched RA), assessing stiffness severity, duration, impact, importance, coping, and physical function [modified Health Assessment Questionnaire (mHAQ)]. Scores were compared between diagnoses and correlations among stiffness dimensions calculated. Multivariate regression was performed for stiffness severity, impact, and duration on mHAQ, adjusting for age, sex, disease duration, obesity, and pain. Cognitive debriefing was conducted through semistructured telephone interviews. RESULTS: Overall, 240/316 (75.9%) responded [124/158 RA (78.5%) and 116/158 PsA (73.4%)], with no significant difference in stiffness ratings between diagnoses. Scores for all stiffness dimensions were strongly correlated (r = 0.52-0.89), and severity and impact were associated with mHAQ in both diagnoses. Stiffness duration was not associated with mHAQ in RA. In cognitive debriefing, participants described stiffness severity and impact by their effect on daily activities (10/16 and 14/16 participants, respectively). CONCLUSION: Stiffness ratings were similar between PsA and RA. Different dimensions of stiffness were strongly correlated. Stiffness severity and impact both independently predicted mHAQ. Stiffness was important to participants; however, measuring multiple dimensions of stiffness may have minimal additive value.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".