Exercise Therapy for Low Back Pain
Bibliographic record
Abstract
STUDY DESIGN: A systematic review of randomized controlled trials was performed. SUMMARY OF BACKGROUND DATA: Exercise therapy is a widely used treatment for low back pain. OBJECTIVES: To evaluate the effectiveness of exercise therapy for low back pain with regard to pain intensity, functional status, overall improvement, and return to work. METHODS: The Cochrane Controlled Trials Register, Medline, Embase, PsycLIT, and reference lists of articles were searched. Randomized trials testing all types of exercise therapy for subjects with nonspecific low back pain with or without radiation into the legs were included. Two reviewers independently extracted data and assessed trial quality. Because trials were considered heterogeneous with regard to study populations, interventions, and outcomes, it was decided not to perform a meta-analysis, but to summarize the results using a rating system of four levels of evidence: strong, moderate, limited, or none. RESULTS: In this review, 39 trials were identified. There is strong evidence that exercise therapy is not more effective for acute low back pain than inactive or other active treatments with which it has been compared. There is conflicting evidence on the effectiveness of exercise therapy compared with inactive treatments for chronic low back pain. Exercise therapy was more effective than usual care by the general practitioner and just as effective as conventional physiotherapy for chronic low back pain. CONCLUSIONS: The evidence summarized in this systematic review does not indicate that specific exercises are effective for the treatment of acute low back pain. Exercises may be helpful for patients with chronic low back pain to increase return to normal daily activities and work.
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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 | 0.030 | 0.075 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.015 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".