Impact of osteopathic manipulative techniques on the management of dizziness caused by neuro-otologic disorders: systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Context Osteopathic manipulative treatment (OMT) has been utilized by osteopathic clinicians as primary or adjunctive management for dizziness caused by neuro-otologic disorders. To our knowledge, no current systematic reviews provide pooled estimates that evaluate the impact of OMT on dizziness. Objectives We aimed to systematically evaluate the effectiveness and safety of OMT and analogous techniques in the treatment of dizziness. Methods We performed a literature search in CINAHL, Embase, MEDLINE, Allied and Complementary Medicine Database (AMED), EMCare, Physiotherapy Evidence Database (PEDro), PubMed, PsycINFO, Osteopathic Medicine Digital Library (OSTMED.DR), and Cochrane Central Register of Controlled Trials (CENTRAL) from inception to March 2021 for randomized controlled trials (RCTs) and prospective or retrospective observational studies of adult patients experiencing dizziness from neuro-otological disorders. Eligible studies compared the effectiveness of OMT or OMT analogous techniques with a comparator intervention, such as a sham manipulation, a different manual technique, standard of care, or a nonpharmacological intervention like exercise or behavioral therapy. Assessed outcomes included disability associated with dizziness, dizziness severity, dizziness frequency, risk of fall, improvement in quality of life (QOL), and return to work (RTW). Assessed harm outcomes included all-cause dropout (ACD) rates, dropouts due to inefficacy, and adverse events. The meta-analysis was based on the similarities between the OMT or OMT analogous technique and the comparator interventions. The risk of bias (ROB) was assessed utilizing a modified version of the Cochrane Risk of Bias Tool for RCTs and the Cochrane Risk of Bias in Non-randomized Studies – of Interventions (ROBINS-I) for observational studies. The quality of evidence was determined utilizing the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. Results There were 3,375 studies identified and screened, and the full text of 47 of them were reviewed. Among those, 12 (11 RCTs, 1 observational study, n=367 participants) met the inclusion criteria for data extraction. Moderate-quality evidence showed that articular OMT techniques were associated with decreases (all p<0.01) in disability associated with dizziness (n=141, mean difference [MD]=−11, 95% confidence interval [CI]=−16.2 to −5.9), dizziness severity (n=158, MD=−1.6, 95% CI=−2.4 to −0.7), and dizziness frequency (n=136, MD=−0.6, 95% CI=−1.1 to −0.2). Low-quality evidence showed that articular OMT was not associated with ACD rates (odds ratio [OR]=2.2, 95% CI=0.5 to 10.2, p=0.31). When data were pooled for any type of OMT technique, findings were similar; however, disability associated with dizziness and ACD rates had high heterogeneity (I2=59 and 46%). No studies met all of the criteria for ROB. Conclusions The current review found moderate-quality evidence that treatment with articular OMT techniques was significantly associated with decreased disability associated with dizziness, dizziness severity, and dizziness frequency. However, our findings should be interpreted cautiously because of the high ROB and small sample sizes in the eligible studies.
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".