Computerized Dynamic Posturography-Guided Vestibular Rehabilitation Improves Vestibular Sensory Ratios
Bibliographic record
Abstract
Background: Vestibular deficits are common and debilitating, and many patients struggle with dynamic balance, even after treatment with standard rehabilitation techniques. Objective: The objective of this study was to measure changes in computerized dynamic posturography sensory ratio information after computerized vestibular retraining therapy (CVRT). Methods: This prospective, single-group, interventional study enrolled adult participants with stable, unilateral vestibular deficits. Sensory ratios were obtained from sensory organization test scores before and after 12 twice-weekly sessions of CVRT. Results: Prior to CVRT, sensory organization test ratios indicated significant difficulty maintaining equilibrium on the moving, sway-referenced platform. After CVRT, the visual ratio (VIS) increased by 0.12 (−0.09 to 0.30; P = .0498), the vestibular ration (VEST) increased by 0.10 (−0.060 to 0.25; P = .0122), and the dynamic stability ration (DSR) increased by 0.15 (0.03 to 0.24; P = .0012). The somatosensory and visual preference ratios changed negligibly. Participants with mild disability [Dizziness Handicap Inventory (DHI) ≤30] showed no change while participants with moderate-to-severe disability (DHI >30) had significant improvements in VIS, VEST, and DSR. Conclusions: CVRT was associated with changes in VIS and VEST sensory ratios and improved postural control under conditions that favor use of vestibular information, consistent with increased weighting of vestibular information over vision ( Clinicaltrials.gov registration NCT04875013; April 27, 2021).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".