Nonpharmacological Spine Pain Management in Clinical Practice Guidelines: A Systematic Review Using AGREE II and AGREE-REX Tools
Bibliographic record
Abstract
OBJECTIVE: To summarize the content and critically appraise the quality and applicability of recent clinical practice guidelines (CPGs) for nonpharmacological, nonsurgical management of spine pain. DESIGN: Systematic review of CPGs. LITERATURE SEARCH: Six databases and seven guideline clearinghouses. STUDY SELECTION CRITERIA: Included de novo CPGs for nonpharmacological, nonsurgical management of spine pain designed for any primary health care providers, published in English, Arabic, French, or traditional Chinese within the past 12 years. DATA SYNTHESIS: Five reviewers independently appraised the guidelines using AGREE II and AGREE-REX. Interrater agreements were calculated for each domain and the total score of these tools using the intraclass correlation coefficient (2, 1) with absolute agreement. RESULTS: We included 30 CPGs, primarily (90%) developed in Western countries, which contained 404 recommendations. High-quality CPGs consistently recommended exercise therapy and multimodal care, encompassing a combination of exercises, mobilization/manipulation, education, alternative medicine, and cognitive-behavioral treatments. Generally, CPGs did not recommend assistive (eg, corsets and orthosis) devices or electro/thermotherapies (eg, therapeutic ultrasound and transcutaneous electrical nerve stimulation). Approximately half of the CPGs demonstrated good methodological quality according to AGREE II, whereas the rest were of poor quality. On the AGREE-REX assessment, one third of the recommendations were of excellent quality. CONCLUSION: Although recent guidelines frequently recommended exercise therapy and multimodal care for the management of spine pain, their recommendations often overlooked demographics and comorbidities. Despite methodological improvements, most CPGs lacked simple clinical applicability and considerations of knowledge users’ values. J Orthop Sports Phys Ther 2025;55(1):12-25. Epub 4 November 2024. doi:10.2519/jospt.2024.12729
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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 | 0.080 | 0.269 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.028 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".