Diagnosing, Managing, and Supporting Return to Work of Adults With Rotator Cuff Disorders: Clinical Practice Guideline Methods
Bibliographic record
Abstract
OBJECTIVES: To present the methods used to develop a clinical practice guideline (CPG) with recommendations endorsed by key stakeholders for assessing, managing, and supporting return to work for adults with rotator cuff disorders. DESIGN: Clinical practice guideline development. METHODS: A steering committee composed of the research team of this project led the development of this CPG in 5 phases, which followed the standards of the NICE and AGREE II collaborations. During the preparation phase (I), a multidisciplinary working committee of experts in managing rotator cuff disorders (n = 20) determined the scope and objectives of the CPG. The recommendations development phase (II) included initial knowledge synthesis, development of preliminary recommendations, systematic consultations with a multidisciplinary panel of key stakeholders (n = 51) using a modified three-round Delphi approach and drafting of the original CPG. In the external evaluation phase (III), an external committee of experts evaluated the original CPG using the AGREE II tool. In the dissemination phase (IV), the strategy for disseminating the CPG was developed and implemented. During the update phase (V), the CPG was revised based on an update of the initial knowledge synthesis. RESULTS: Seventy-three preliminary recommendations were developed from the initial knowledge synthesis. During the Delphi consultation, all of these recommendations were endorsed, and one new recommendation was proposed by panelists. The original CPG received an overall AGREE II score of 83% from the external evaluators. In 2021, an update of the initial 2017 knowledge synthesis was conducted and 13 recommendations were revised. CONCLUSION: The 5-phase consensus methods approach guided the development of a high-quality CPG on assessing, managing, and supporting return to work for adults with rotator cuff disorders. J Orthop Sports Phys Ther 2022;52(10):665–674. Epub: 27 July 2022. doi:10.2519/jospt.2022.11307
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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 | 0.058 | 0.101 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".