Extrapolating Beyond the Data in a Systematic Review of Spinal Manipulation for Nonmusculoskeletal Disorders: A Fall From the Summit
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article is to discuss a literature review-a recent systematic review of nonmusculoskeletal disorders-that demonstrates the potential for faulty conclusions and misguided policy implications, and to offer an alternate interpretation of the data using present models and criteria. METHODS: We participated in a chiropractic meeting (Global Summit) that aimed to perform a systematic review of the literature on the efficacy and effectiveness of mobilization or spinal manipulative therapy (SMT) for the primary, secondary, and tertiary prevention and treatment of nonmusculoskeletal disorders. After considering an early draft of the resulting manuscript, we identified points of concern and therefore declined authorship. The present article was developed to describe those concerns about the review and its conclusions. RESULTS: Three main concerns were identified: the inherent limitations of a systematic review of 6 articles on the topic of SMT for nonmusculoskeletal disorders, the lack of biological plausibility of collapsing 5 different disorders into a single category, and considerations for best practices when using evidence in policy-making. We propose that the following conclusion is more consistent with a review of the 6 articles. The small cadre of high- or moderate-quality randomized controlled trials reviewed in this study found either no or equivocal effects from SMT as a stand-alone treatment for infantile colic, childhood asthma, hypertension, primary dysmenorrhea, or migraine, and found no or low-quality evidence available to support other nonmusculoskeletal conditions. Therefore, further research is needed to determine if SMT may have an effect in these and other nonmusculoskeletal conditions. Until the results of such research are available, the benefits of SMT for specific or general nonmusculoskeletal disorders should not be promoted as having strong supportive evidence. Further, a lack of evidence cannot be interpreted as counterevidence, nor used as evidence of falsification or verification. CONCLUSION: Based on the available evidence, some statements generated from the Summit were extrapolated beyond the data, have the potential to misrepresent the literature, and should be used with caution. Given that none of the trials included in the literature review were definitively negative, the current evidence suggests that more research on nonmusculoskeletal conditions is warranted before any definitive conclusions can be made. Governments, insurers, payers, regulators, educators, and clinicians should avoid using systematic reviews in decisions where the research is insufficient to determine the clinical appropriateness of specific care.
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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 | 0.556 | 0.834 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.023 | 0.019 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.020 | 0.037 |
| Open science | 0.011 | 0.018 |
| Research integrity | 0.016 | 0.016 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".