Clinical Practice Guidelines for Pain Management in Acute Musculoskeletal Injury
Bibliographic record
Abstract
PURPOSE: We aimed to produce comprehensive guidelines and recommendations that can be utilized by orthopaedic practices as well as other specialties to improve the management of acute pain following musculoskeletal injury. METHODS: A panel of 15 members with expertise in orthopaedic trauma, pain management, or both was convened to review the literature and develop recommendations on acute musculoskeletal pain management. The methods described by the Grading of Recommendations Assessment, Development, and Evaluation Working Group were applied to each recommendation. The guideline was submitted to the Orthopaedic Trauma Association (OTA) for review and was approved on October 16, 2018. RESULTS: We present evidence-based best practice recommendations and pain medication recommendations with the hope that they can be utilized by orthopaedic practices as well as other specialties to improve the management of acute pain following musculoskeletal injury. Recommendations are presented regarding pain management, cognitive strategies, physical strategies, strategies for patients on long term opioids at presentation, and system implementation strategies. We recommend the use of multimodal analgesia, prescribing the lowest effective immediate-release opioid for the shortest period possible, and considering regional anesthesia. We also recommend connecting patients to psychosocial interventions as indicated and considering anxiety reduction strategies such as aromatherapy. Finally, we also recommend physical strategies including ice, elevation, and transcutaneous electrical stimulation. Prescribing for patients on long term opioids at presentation should be limited to one prescriber. Both pain and sedation should be assessed regularly for inpatients with short, validated tools. Finally, the group supports querying the relevant regional and state prescription drug monitoring program, development of clinical decision support, opioid education efforts for prescribers and patients, and implementing a department or organization pain medication prescribing strategy or policy. CONCLUSIONS: Balancing comfort and patient safety following acute musculoskeletal injury is possible when utilizing a true multimodal approach including cognitive, physical, and pharmaceutical strategies. In this guideline, we attempt to provide practical, evidence-based guidance for clinicians in both the operative and non-operative settings to address acute pain from musculoskeletal injury. We also organized and graded the evidence to both support recommendations and identify gap areas for future research.
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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 | 0.026 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".