“Positive to Negative” Dix-Hallpike test and Benign Paroxysmal Positional Vertigo recurrence in elderly undergoing Canalith Repositioning Maneuver and Vestibular Rehabilitation
Bibliographic record
Abstract
Introduction Benign Paroxysmal Positional Vertigo is the most common cause of dizziness in elderly people. Recent studies have shown that the elderly present higher Benign Paroxysmal Positional Vertigo recurrence and that vertiginous symptomatology remission varies according to comorbidities and the therapeutic techniques applied. Objective To assess the short-term effectiveness of Vestibular Rehabilitation in addition to Canalith Repositioning Maneuver on positive to negative Dix-Hallpike test, on recurrence and number of maneuvers to achieve a negative test in elderly patients with chronic Benign Paroxysmal Positional Vertigo. Methods In this randomized controlled trial, 7 older adults (median age: 69 years, range 65–78) underwent Canalith Repositioning Maneuver and Vestibular Rehabilitation for thirteen weeks. Seven older adults (median age: 73 years, range 65–76) in the control group received only Canalith Repositioning Maneuver. The participants were assessed at baseline (T0), one (T1), five (T5), nine (T9), and thirteen weeks (T13). We assessed the differences between the groups by Mann-Whitney and Fisher exact tests, and used the Friedman and Wilcoxon tests to determine the intragroup differences. Results No significant differences were found between groups for the positive to negative Dix-Hallpike test, recurrence, and number of maneuvers to achieve a negative test. The number of maneuvers to achieve negative Dix-Hallpike test was lower in intragroup comparisons in the experimental group. Conclusion The findings suggest that additional Vestibular Rehabilitation did not influence the positive to negative Dix-Hallpike test, recurrence, or number of maneuvers to achieve a negative test in elderly patients with chronic Benign Paroxysmal Positional Vertigo.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".