Manipulation and mobilization for treating chronic low back pain: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Context Mobilization and manipulation therapies are widely used to benefit patients with chronic low back pain. However, questions remain about their efficacy, dosing, safety, and how these approaches compare with other therapies. Purpose The present study aims to determine the efficacy, effectiveness, and safety of various mobilization and manipulation therapies for treatment of chronic low back pain. Study Design/Setting This is a systematic literature review and meta-analysis. Outcome Measures The present study measures self-reported pain, function, health-related quality of life, and adverse events. Methods We identified studies by searching multiple electronic databases from January 2000 to March 2017, examining reference lists, and communicating with experts. We selected randomized controlled trials comparing manipulation or mobilization therapies with sham, no treatment, other active therapies, and multimodal therapeutic approaches. We assessed risk of bias using Scottish Intercollegiate Guidelines Network criteria. Where possible, we pooled data using random-effects meta-analysis. Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) was applied to determine the confidence in effect estimates. This project is funded by the National Center for Complementary and Integrative Health under Award Number U19AT007912. Results Fifty-one trials were included in the systematic review. Nine trials (1,176 patients) provided sufficient data and were judged similar enough to be pooled for meta-analysis. The standardized mean difference for a reduction of pain was SMD=−0.28, 95% confidence interval (CI) −0.47 to −0.09, p=.004; I 2 =57% after treatment; within seven trials (923 patients), the reduction in disability was SMD=−0.33, 95% CI −0.63 to −0.03, p=.03; I 2 =78% for manipulation or mobilization compared with other active therapies. Subgroup analyses showed that manipulation significantly reduced pain and disability, compared with other active comparators including exercise and physical therapy (SMD=−0.43, 95% CI −0.86 to 0.00; p=.05, I 2 =79%; SMD=−0.86, 95% CI −1.27 to −0.45; p<.0001, I 2 =46%). Mobilization interventions, compared with other active comparators including exercise regimens, significantly reduced pain (SMD=−0.20, 95% CI −0.35 to −0.04; p=.01; I 2 =0%) but not disability (SMD=−0.10, 95% CI −0.28 to 0.07; p=.25; I 2 =21%). Studies comparing manipulation or mobilization with sham or no treatment were too few or too heterogeneous to allow for pooling as were studies examining relationships between dose and outcomes. Few studies assessed health-related quality of life. Twenty-six of 51 trials were multimodal studies and narratively described. Conclusion There is moderate-quality evidence that manipulation and mobilization are likely to reduce pain and improve function for patients with chronic low back pain; manipulation appears to produce a larger effect than mobilization. Both therapies appear safe. Multimodal programs may be a promising option.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.023 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".