Description of stable pain in rheumatoid arthritis: a 6 year study.
Bibliographic record
Abstract
OBJECTIVE: To study pain quality and variability in patients with rheumatoid arthritis (RA). METHODS: Pain, disease activity, and functional status were assessed 3 times over 6 years in an initial cohort of 120 clinic patients with chronic pain from RA. A pain visual analog scale and the McGill Pain Questionnaire (MPQ) were used to record pain intensity and quality. RA disease activity and function were measured. RESULTS: There was no statistically significant difference in any measure over the 3 assessments. RA pain intensity was moderate. The MPQ showed that sensory components of the pain were described in terms of pressure and constriction. Pain related affect was described with adjectives suggesting positive psychological adaptation to pain. CONCLUSION: The results indicate a general profile of no change in pain sensation, affect, and emotional quality in clinic monitored patients with ongoing RA and ongoing, moderate levels of disease activity and function. The MPQ provides qualitative detail to patient's report of pain severity that could be a useful addition to longterm documentation of RA outcome. Regular MPQ documentation of current pain in outpatients could indicate whether any significant change in pain levels is reflected in altered word selection that reflects physiological or psychological change, and could assist clinicians to select the most appropriate form of therapy for RA pain.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".