A Systematic Review of Clinical Practice Guidelines for Persons With Non-specific Low Back Pain With and Without Radiculopathy: Identification of Best Evidence for Rehabilitation to Develop the WHO's Package of Interventions for Rehabilitation
Bibliographic record
Abstract
OBJECTIVE: To Identify evidence-based rehabilitation interventions for persons with non-specific low back pain (LBP) with and without radiculopathy and to develop recommendations from high-quality clinical practice guidelines (CPGs) to inform the World Health Organization's (WHO) Package of Interventions for Rehabilitation (PIR). DATA SOURCE: We searched MEDLINE, EMBASE, CINAHL, PsycINFO, National Health Services Economic Evaluation Database, Health Technology Assessment Database, PEDro, the Trip Database, the Index to Chiropractic Literature and the gray literature. STUDY SELECTION: Eligible guidelines were (1) published between 2009 and 2019 in English, French, Italian, or Swedish; (2) included adults or children with non-specific LBP with or without radiculopathy; and (3) assessed the benefits of rehabilitation interventions on functioning. Pairs of independent reviewers assessed the quality of the CPGs using AGREE II. DATA SYNTHESIS: We identified 4 high-quality CPGs. Recommended interventions included (1) education about recovery expectations, self-management strategies, and maintenance of usual activities; (2) multimodal approaches incorporating education, exercise, and spinal manipulation; (3) nonsteroidal anti-inflammatory drugs combined with education in the acute stage; and (4) intensive interdisciplinary rehabilitation that includes exercise and cognitive/behavioral interventions for persistent pain. We did not identify high-quality CPGs for people younger than 16 years of age. CONCLUSION: We developed evidence-based recommendations from high-quality CPGs to inform the WHO PIR for people with LBP with and without radiculopathy. These recommendations emphasize the potential benefits of education, exercise, manual therapy, and cognitive/behavioral interventions.
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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 | 0.031 | 0.138 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.012 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".