Supplementary Material for: Vertigo and Balance Disorders – The Role of Osteopathic Manipulative Treatment: A Systematic Review
Bibliographic record
Abstract
Background: Balance disorders are among the most frequent reasons for consultation and referral to specialist care. Osteopathic Manipulative Treatment (OMT) can influence the proprioceptive system by inducing alterations in the proprioceptive stimuli, hence affecting postural control. Objective: The present systematic review aimed to explore the effects of OMT in managing patients with vertigo and balance disorders. Methods: MEDLINE (PubMed), ScienceDirect, and Google Scholar were searched. Clinical trials and prospective observational studies were considered. Only studies that considered OMT as the main intervention, provided alone or combined with other interventions, were included. The methodological quality of the evidence was assessed with a modified version of the Newcastle-Ottawa Scale. Results: Five studies that enrolled a total of 114 subjects met our inclusion criteria. Overall, it has been observed that there is a positive effect on balance disorders through different outcomes in all of the included studies. Only two studies (9 subjects) mentioned low to moderate adverse events after OMT. Conclusions: OMT showed weak positive effects on balance function, encouraging the connection of conventional medicine and evidence-based complementary medicine for integrative clinical practice and interprofessional work. However, full-sized adequately powered randomized trials are required to determine the effectiveness of OMT for vertigo and balance disorders.
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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 | 0.005 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.358 | 0.017 |
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".