More than Just Minutes of Stiffness in the Morning: Report from the OMERACT Rheumatoid Arthritis Flare Group Stiffness Breakout Sessions
Bibliographic record
Abstract
OBJECTIVE: Stiffness was endorsed within the rheumatoid arthritis (RA) flare core domain set at the previous Outcome Measures in Rheumatology meeting (OMERACT 11). Two stiffness breakout groups at the present OMERACT 12 RA flare workshop discussed results of new qualitative studies in RA stiffness. METHODS: Results from 2 independent studies of RA stiffness were presented to breakout group participants, followed by group discussions about stiffness measurement. RESULTS: Both studies identified stiffness as complex, variable with the level of disease activity, and as encompassing concepts of impact, intensity, timing, location, and duration. That stiffness has an effect on multiple dimensions of health was a common finding. Participants agreed that stiffness is an important aspect of RA flare. Whether measuring only morning stiffness duration, the traditional approach in RA, was sufficient in coverage of the concept was unclear. Groups agreed that more research on stiffness measurement is needed considering the importance patients place on the effect of stiffness. CONCLUSION: Results from independent studies highlight stiffness effect as an important feature of RA, in addition to intensity, timing, location, and duration. Additional work is needed to identify optimal ways to assess stiffness in RA and other rheumatologic diseases.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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".