A Systematic Critical Appraisal of Non-Pharmacological Management of Rheumatoid Arthritis with Appraisal of Guidelines for Research and Evaluation II
Bibliographic record
Abstract
Clinical practice guidelines (CPGs) have been developed to summarize evidence about the management of rheumatoid arthritis (RA) and facilitate the uptake of evidence-based knowledge by consumers, health professionals, health administrators and policy makers. The objectives of this review was to assess the quality of CPGS on non-pharmacological management of RA with a standardized and validated instrument--the Appraisal of Guidelines for Research and Evaluation (AGREE II) tool and summarize the key recommendations from these CPGs. Scientific literature databases from 2001 to 2013 were systematically searched and a total of 13 CPGs for RA was identified. Only a minority of AGREE II domains were effectively addressed by the CPGS. Scope and purpose was effectively addressed in 10 out of 13 CPGs, stakeholder involvement in 11 CPGs, rigor of development in 6 CPGs, clarity/presentation in 9 CPGs, editorial independence in 1 CPGs, and applicability in none of the CPGs. The overall quality of the included CPGs according to the 7-point AGREE II scoring system was 4.8 ± 1.04. Patient education/self-management, aerobic, dynamic and stretching exercises were the commonly recommended for the non-pharmacological management of RA by the high-quality CPGs. The general clinical management recommendations tended to be similar among high-quality CPGs. Non-pharmacological management interventions were superficially addressed in more than half of the selected CPGs. CPGs creators should use the AGREE II criteria when developing guidelines. Innovative and effective methods of CPGs implementation to users are needed to ultimately enhance the quality of life of arthritic individuals. In addition, it was difficult to establish between strongly recommended, recommended and weakly recommended, as there is no consensus between the strength of the recommendations between the appraised CPGs.
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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 | 0.247 | 0.584 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.031 | 0.018 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".