Does Clinical Remission Lead to Normalization of EQ-5D in Patients with Rheumatoid Arthritis and Is Selection of Remission Criteria Important?
Bibliographic record
Abstract
OBJECTIVE: To compare health-related quality of life (HRQOL) of patients with rheumatoid arthritis (RA) to that of the general population and to investigate the association with disease activity, focusing on different clinical remission criteria. METHODS: EQ-5D data from 3156 patients with RA from 11 Danish centers were compared with Danish EQ-5D population norms (n = 16,136). The Disease Activity Score (DAS28) and the Clinical Disease Activity Index score (CDAI) were used as definitions of disease activity and clinical remission. The score difference (DeltaEQ-5D) was calculated in each patient as the difference from the age and sex-matched general population and adjusted for age, marital status, education, body mass index, smoking, exercise habits, disease duration, IgM-rheumatoid factor status, joint surgery, extraarticular features, treatment, and comorbidity in multiple linear regression models. RESULTS: 37% vs 22% fulfilled the DAS28 and CDAI remission criteria, respectively. The DeltaEQ-5D values for women/men in clinical remission were DAS28 0.05/0.06 vs CDAI 0.01/0.02; low disease activity: DAS28 0.12/0.13 vs CDAI 0.11/0.14; moderate disease activity: DAS28 0.18/0.20 vs CDAI 0.20/0.23; and high disease activity: DAS28 0.38/0.28 vs CDAI 0.33/0.26. Adjusting for confounders reduced the DeltaEQ-5D values between 0 and 0.04 units. CONCLUSION: Patients with RA had worse EQ-5D scores than the general population, and the difference was strongly associated with disease activity. The EQ-5D score for patients in clinical remission approached that of the general population, suggesting that strict treatment goals are critical in order to achieve near-normal HRQOL in patients with RA.
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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 | 0.018 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".