Recommendations for the treatment of rheumatoid arthritis in Saudi Arabia: adolopment of the 2021 American College of Rheumatology guidelines
Bibliographic record
Abstract
Abstract Background The 2021 American College of Rheumatology (ACR) rheumatoid arthritis (RA) guideline considers the specific context of the United States which differs from that of Saudi Arabia in many aspects that may impact recommendations. The objective of this project was to adapt a set of prioritized recommendations from the 2021 ACR guideline for the treatment of rheumatoid arthritis RA for the context of Saudi Arabia, by the Saudi Society for Rheumatology (SSR). Methods The process followed the GRADE-ADOLOPMENT methodology, and the reporting adhered to the RIGHT-Ad@pt checklist. Working groups included a coordination group and a 19-member panel representing different stakeholder groups. The Evidence to Decision (EtD) tables included evidence on health effects from the source guideline and contextual information from the Saudi setting. Results The panel prioritized and adapted five recommendations from the source guideline. The process led to modifying two out of the five prioritized recommendations, all listed here. In naive patients with low disease activity, methotrexate (MTX) is conditionally recommended over sulfasalazine (SSZ) (modified direction); hydroxychloroquine (HCQ) is conditionally recommended over SSZ (unmodified). Initiation of csDMARDs with short-term glucocorticoids is conditionally recommended over csDMARDs alone in naive patients with moderate to high disease activity (modified direction). Switch to subcutaneous MTX is conditionally recommended over addition/switch to alternative DMARD(s) in patients taking oral MTX who are not at target (unmodified). Discontinuation of MTX is conditionally recommended over gradual discontinuation of the bDMARD or tsDMARD for patients taking MTX plus a bDMARD or tsDMARD who wish to discontinue a DMARD (unmodified). Conclusion Rheumatologists practicing in Saudi Arabia can use the adoloped recommendations generated by this project while adopting the rest of the recommendations from the 2021 ACR guidelines.
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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 | 0.044 | 0.118 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| 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".