Developing an effective treatment algorithm for rheumatoid arthritis
Bibliographic record
Abstract
RA is defined by the interrelated triad of disease activity, joint damage and disability. Although disease activity and its associated disability are reversible, joint damage and its associated disability are not. Thus, an important goal of RA therapy is to maximally reduce disease activity and thereby mitigate the accumulation of irreversible joint damage. Treatment for patients with RA should be initiated early and aggressively, with frequent assessments and a goal of achieving remission as quickly as possible after treatment initiation. We propose a treatment algorithm that recommends early and aggressive therapy with high-dose MTX therapy (15-25 mg/week), which may include moderate doses of glucocorticoids. The goal is to achieve low disease activity (determined by a composite measure that includes joint counts) within 3-6 months. If low disease activity is not achieved by 6 months, another conventional DMARD or a biologic agent should be added to the treatment regimen or patients should be switched to another DMARD plus a glucocorticoid. Once low disease activity is achieved, the treatment goal for the ensuing 3-6 months becomes disease remission.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".