Vestibular Rehabilitation Using Dynamic Posturography: Functional Stability and Fall Risk Outcomes From a Randomized Trial
Bibliographic record
Abstract
OBJECTIVE: To compare computerized vestibular retraining therapy (CVRT) to a home exercise program (HEP) for the treatment of unilateral vestibular deficits. STUDY DESIGN: Randomized, unblinded, interventional study with single crossover. SETTING: This study was performed in a tertiary neurotology clinic. METHODS: Individuals with a stable unilateral vestibular deficit present for greater than 6 months, confirmed with videonystagmography and vestibular evoked myogenic potential testing and scoring >30 on the dizziness handicap inventory, received either 12 twice-weekly sessions of CVRT or 6 weeks of HEP. Outcome measures were the limits of stability test with submeasures: reaction time; directional control; movement velocity; endpoint and maximum excursion; endpoint and maximum functional stability region. RESULTS: CVRT (n = 18), but not HEP (n = 12), was associated with improvement in all measures and with fewer instances of loss of balance during testing. CVRT was superior to HEP for directional control (24.0; 95% CI 4.4-43.6; P = .01), movement velocity (1.5; 95% CI 0.6-2.3; P < .001), and endpoint excursion (21.1; 95% CI 4.8-37.4; P < .01). Improvements in directional control (23.0; 95% CI 1.1-45.0; P = .046) and movement velocity (1.3; 95% CI 0.4-2.2; P = .04) were greater for HEP/CVRT crossover than for HEP alone. There were no adverse effects of either treatment. CONCLUSION: CVRT improved postural stability in the limits of stability test. CVRT was associated with greater improvement than HEP in lean angle, accuracy, and speed of volitional leaning. TRIAL REGISTRATION: Clinicaltrials.gov NCT05115032 (https://clinicaltrials.gov/study/NCT05115032).
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".