A Systematic Critical Appraisal for Non-Pharmacological Management of Osteoarthritis Using the Appraisal of Guidelines Research and Evaluation II Instrument
Bibliographic record
Abstract
Clinical practice CPGs (CPGs) have been developed to summarize evidence related to the management of osteoarthritis (OA). CPGs facilitate uptake of evidence-based knowledge by consumers, health professionals, health administrators and policy makers. The objectives of the present review were: 1) to assess the quality of the CPGs on non-pharmacological management of OA; using a standardized and validated instrument--the Appraisal of Guidelines Research and Evaluation (AGREE II) tool--by three pairs of trained appraisers; and 2) to summarize the recommendations based on only high-quality existing CPGs. Scientific literature databases from 2001 to 2013 were systematically searched for the state of evidence, with 17 CPGs for OA being identified. Most CPGs effectively addressed only a minority of AGREE II domains. Scope and purpose was effectively addressed in 10 CPGs on the management of OA, stakeholder involvement in 12 CPGs, rigour of development in 10 CPGs, clarity/presentation in 17 CPGs, editorial independence in 2 CPGs, and applicability in none of the OA CPGs. The overall quality of the included CPGs, according to the 7-point AGREE II scoring system, is 4.8 ± 0.41 for OA. Therapeutic exercises, patient education, transcutaneous electrical nerve stimulation, acupuncture, orthoses and insoles, heat and cryotherapy, patellar tapping, and weight control are commonly recommended for the non-pharmacological management of OA by the high-quality CPGs. The general clinical management recommendations tended to be similar among high-quality CPGs, although interventions addressed varied. Non-pharmacological management interventions were superficially addressed in more than half of the selected CPGs. For CPGs to be standardized uniform creators should use the AGREE II criteria when developing CPGs. Innovative and effective methods of CPG implementation to users are needed to ultimately enhance the quality of life of arthritic individuals.
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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 | 0.264 | 0.538 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.021 |
| Bibliometrics | 0.037 | 0.025 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".