PEER simplified chronic pain guideline
Bibliographic record
Abstract
OBJECTIVE: To develop a clinical practice guideline to support the management of chronic pain, including low back, osteoarthritic, and neuropathic pain in primary care. METHODS: The guideline was developed with an emphasis on best available evidence and shared decision-making principles. Ten health professionals (4 generalist family physicians, 1 pain management-focused family physician, 1 anesthesiologist, 1 physical therapist, 1 pharmacist, 1 nurse practitioner, and 1 psychologist), a patient representative, and a nonvoting pharmacist and guideline methodologist comprised the Guideline Committee. Member selection was based on profession, practice setting, and lack of financial conflicts of interest. The guideline process was iterative in identification of key questions, evidence review, and development of guideline recommendations. Three systematic reviews, including a total of 285 randomized controlled trials, were completed. Randomized controlled trials were included only if they reported a responder analysis (eg, how many patients achieved a 30% or greater reduction in pain). The committee directed an Evidence Team (composed of evidence experts) to address an additional 11 complementary questions. Key recommendations were derived through committee consensus. The guideline and shared decision-making tools underwent extensive review by clinicians and patients before publication. RECOMMENDATIONS: Physical activity is recommended as the foundation for managing osteoarthritis and chronic low back pain; evidence of benefit is unclear for neuropathic pain. Cognitive-behavioural therapy or mindfulness-based stress reduction are also suggested as options for managing chronic pain. Treatments for which there is clear, unclear, or no benefit are outlined for each condition. Treatments for which harms likely outweigh benefits for all or most conditions studied include opioids and cannabinoids. CONCLUSION: This guideline for the management of chronic pain, including osteoarthritis, low back pain, and neuropathic pain, highlights best available evidence including both benefits and harms for a number of treatment interventions. A strong recommendation for exercise as the primary treatment for chronic osteoarthritic and low back pain is made based on demonstrated long-term evidence of benefit. This information is intended to assist with, not dictate, shared decision making with patients.
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 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 | 0.009 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.111 | 0.085 |
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".