Effectiveness of Spinal Manipulation in the Treatment of Non-Musculoskeletal Disorders: A Systematic Review
Bibliographic record
Abstract
Purpose: Perform a systematic review to determine if spinal manipulation (SM) is an effective treatment for non-musculoskeletal disorders.\nSubjects: Four studies from peer-reviewed journals that met inclusion/exclusion criteria were reviewed.\nMaterials & Methods: Pubmed, PEDro, Chiropractic Literature, CINAHL, Cochrane were searched between March and April 2014. In order to assess methodological quality, three raters applied the PEDro scale to included studies.\nResults: The initial search yielded 2,324 articles covering 45 non-musculoskeletal conditions. Four randomized control trials (RCTs), met inclusion criteria. The conditions covered included: inner ear infection, infantile colic, asthma, and chronic obstructive pulmonary disease. Pedro scores ranged from 6-8, with a mean score of 7.25±.957, indicating fair to good methodological quality. Two studies reported significant improvement between groups for forced vital capacity, 6MWT and dyspnea scores for individuals with COPD and self-reported quality of life and symptom severity for individuals with asthma. Two studies found no statistically significant changes in physiologic or self-reported outcomes.\nConclusions: Although, there were significant improvements in some outcome measures, the applicability of these results is limited by the poor methodological design of the studies, making it impossible to attribute these improvements to SM, alone. Therefore, there is no conclusive evidence that supports the use of SM as a treatment for non-musculoskeletal disorders.\nClinical Relevance: It is imperative to investigate the possible benefits of SM in order to provide evidence based treatment to individuals with non-musculoskeletal conditions. This reviews illuminates the need for higher quality research when examining the effect of SM on non-musculoskeletal disorders.
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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| 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".