Association of 17 Definitions of Remission with Functional Status in a Large Clinical Practice Cohort of Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To compare the association between different remission criteria and physical function in patients with rheumatoid arthritis followed in clinical practice. METHODS: Longitudinal data from the METEOR database were used. Seventeen definitions of remission were tested: American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) Boolean-based; Simplified/Clinical Disease Activity Index (SDAI/CDAI); and 14 Disease Activity Score (DAS)-based definitions. Health Assessment Questionnaire (HAQ) ≤ 0.5 was defined as good functional status. Associations were investigated using generalized estimating equations. Potential confounders were tested and sensitivity analyses performed. RESULTS: Data from 32,915 patients (157,899 visits) were available. The most stringent definition of remission was the ACR/EULAR Boolean-based definition (1.9%). The proportion of patients with HAQ ≤ 0.5 was higher for the most stringent definitions, although it never reached 100%. However, this also meant that, for the most stringent criteria, many patients in nonremission had HAQ ≤ 0.5. All remission definitions were associated with better function, with the strongest degree of association observed for the SDAI (adjusted OR 3.36, 95% CI 3.01-3.74). CONCLUSION: The 17 definitions of remission confirmed their validity against physical function in a large international clinical practice setting. Achievement of remission according to any of the indices may be more important than the use of a specific index. A multidimensional approach, targeted at wider goals than disease control, is necessary to help all patients achieve the best possible functional status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".