Diagnosing, Managing, and Supporting Return to Work of Adults With Rotator Cuff Disorders: A Clinical Practice Guideline
Bibliographic record
Abstract
OBJECTIVE: To develop a clinical practice guideline covering the assessment, management, and return to work of adults with rotator cuff disorders. DESIGN: Clinical practice guideline. METHODS: Using systematic reviews, appraisal of the literature, and an iterative approach to obtain consensus from key stakeholders, clinical recommendations and algorithms were developed in the context of the health care system and work environment of the province of Quebec (Canada). RESULTS: Recommendations (n = 73) and clinical decision algorithms (n = 3) were developed to match the objectives. The initial assessment should include the patient's history, a subjective assessment, and a physical examination. Diagnostic imaging is only necessary in select circumstances. Acetaminophen, nonsteroidal anti-inflammatory drugs, and injection therapies may be useful to reduce pain in the short term. Clinicians should prescribe an active and task-oriented rehabilitation program (exercises and education) to reduce pain and disability in adults with rotator cuff disorders. Subacromial decompression is not recommended to treat rotator cuff tendinopathy. Surgery is appropriate for selected patients with a full-thickness rotator cuff tear. A return-to-work plan should be developed early, in collaboration with the worker and other stakeholders, and must combine multiple strategies to promote return to work. CONCLUSION: This clinical practice guideline was developed to assist the multidisciplinary team of clinicians who provide health care for adults with a rotator cuff disorder. The CPG guides clinical decisionmaking for diagnosis and treatment, and planning for successful return to work. J Orthop Sports Phys Ther 2022;52(10):647–664. Epub: 27 July 2022. doi:10.2519/jospt.2022.11306
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".