Patient-reported Outcomes as Predictors of Change in Disease Activity and Disability in Early Rheumatoid Arthritis: Results from the Yorkshire Early Arthritis Register
Bibliographic record
Abstract
OBJECTIVE: To assess patient-reported variables as predictors of change in disease activity and disability in early rheumatoid arthritis (RA). METHODS: Cases were recruited to the Yorkshire Early Arthritis Register (YEAR) between 1997 and 2009 (n = 1415). Predictors of the 28-joint Disease Activity Score (DAS28) and the Health Assessment Questionnaire-Disability Index (HAQ-DI) at baseline and change over 12 months were identified using multilevel models. Baseline predictors were sex, age, symptom duration, autoantibody status, pain and fatigue visual analog scales (VAS), duration of early morning stiffness (EMS), DAS28, and HAQ-DI. RESULTS: Rates of change were slower in women than men: DAS28 fell by 0.19 and 0.17 units/month, and HAQ-DI by 0.028 and 0.023 units/month in men and women, respectively. Baseline pain and EMS had small effects on rates of change, whereas fatigue VAS was only associated with DAS28 and HAQ-DI at baseline. In patients recruited up to 2002, DAS28 reduced more quickly in those with greater pain at baseline (by 0.01 units/mo of DAS28 per cm pain VAS, p = 0.024); in patients recruited after 2002, the effect for pain was stronger (by 0.01 units/mo, p = 0.087). DAS28 reduction was greater with longer EMS. In both cohorts, fall in HAQ-DI (p = 0.006) was greater in patients with longer EMS duration, but pain and fatigue were not significant predictors of change in HAQ-DI. CONCLUSION: Patient-reported fatigue, pain, and stiffness at baseline are of limited value for the prediction of RA change in disease activity (DAS28) and activity limitation (HAQ-DI).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".