Corticosteroid use in rheumatoid arthritis: prevalence, predictors, correlates, and outcomes.
Bibliographic record
Abstract
OBJECTIVE: To determine the rate of current and lifetime use of corticosteroids, the degree of association between corticosteroids and rheumatoid arthritis (RA) activity and outcome, corticosteroid initiation and discontinuation rates, and the predictors associated with initiation and discontinuation. METHODS: A total of 12,749 patients with RA were evaluated semiannually as to corticosteroid use, RA activity measures, RA outcomes, and predictors of initiation and discontinuation of corticosteroids. RESULTS: Current corticosteroid use was 35.5% and lifetime use was 65.5%. Rheumatologists varied substantially in their use of corticosteroids. The primary patient-derived determinant of corticosteroid initiation, current use, and discontinuation was symptom severity, although 21-25% of patients in remission or with minimal disease activity continued taking corticosteroids. Within the pool of current users, 24.3% [95% confidence interval (CI) 23.2-25.3%] discontinued corticosteroids yearly, and among patients newly starting corticosteroids this rate was 56.9% (95% CI 53.4-60.7%). Corticosteroid initiation occurred at a rate of 8.9% (95% CI 8.4-9.3%) per year. Among corticosteroid users, persistent use (> 5 years) occurs in about one-third of patients. Corticosteroid use and duration of use is associated with severe outcomes for current and past users. For current users versus non-current users, covariate adjusted outcomes were: mortality 5.7% versus 2.6%, work disability 28.4% versus 17.2%, and total joint replacement 18.5% versus 13.0%. CONCLUSION: Corticosteroid use is dynamic and is associated with RA severity. Corticosteroid use is also associated with adverse longterm outcomes, but the ability to discern causal associations is severely limited by confounding by indication. The idea of "once on corticosteroids, always on corticosteroids" is incorrect and applies to only a minority of patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".